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.
3,583
datasets available to search
ShareScore release 0.9.0
Dataset results
3,583 results for “elevations”
Adaptation to lower latitudes and lower elevations precedes the evolution of hummingbird pollination in western North American Penstemon
<p>Premise: A switch in pollinator can occur when a plant lineage enters a new habitat where the ancestral pollinator is less common and a novel pollinator is more common. Since pollinator communities vary according to environmental tolerances and availability of resources, there may be consistent associations between pollination mode and specific regions and habitats. Such associations can be studied in lineages that have experienced multiple pollinator transitions, representing evolutionary replicates.</p> <p>Methods: Our study focused on a large clade of Penstemon wildflower species in western North America that has repeatedly evolved hummingbird-adapted flowers from ancestral bee-adapted flowers. For each species, we estimated geographic ranges from occurrence data and inferred environmental niches from climate, topographical, and soil data. Using a phylogenetic comparative approach, we investigated whether hummingbird-adapted species occupy distinct geographic regions or habitats relative to beeadapted species.</p> <p>Results: Hummingbird-adapted species occur at lower latitudes and lower elevations than bee-adapted species, resulting in a difference in their environmental niche. Hummingbird-adapted species seem to evolve in lineages that previously adapted to lower latitudes and elevations, since bee-adapted species sister to hummingbird-adapted species also occur in these regions and habitats. Sister species pairs – regardless of whether they differ in pollinator – show relatively little geographic range overlap.</p> <p>Conclusions: Adaptation to a novel pollinator may often occur in geographic and ecological isolation from ancestral populations. The ability of a given lineage to adapt to novel pollinators may critically depend on its ability to colonize regions and habitats associated with novel pollinator communities.</p>
Code and data for "Species traits associated with rapid shifts in elevational distributions of Swiss birds"
<p><strong>Abstract</strong><br> Global change in climate and land use have profound effects on species’ geographic and elevational distributions. In European birds, while species are predicted to track their climatic niches upslope, lowland agricultural intensification and high elevation land abandonment can drive elevational shifts. Species traits that can predict response to change in climate and land use can inform conservation, but thorough examination of their relationships with elevational shifts in European birds are lacking. We estimate change in the elevational distributions of 71 species from 1996 to 2016 in a region of the western Palearctic with wide elevational gradients (approximately 3,000 m) and large changes in temperature. We model the relationships between elevational shifts and species traits associated with resource preference and adaptive capacity at five reference points including the cool edge, warm edge, and the core of species’ elevational distributions. When intermediate reference points were removed changes to the results were negligible, indicating that three reference points are likely sufficient. We found significant upslope and downslope shifts in 56% and 23% of our study species, respectively. Asymmetric rates of shifts in the cool and warm edges caused significant contractions in elevational extent in 30% of our study species. The effect of elevational preference (i.e. midpoint elevation) was habitat dependent. Movement in alpine birds was unidirectionally upslope, with nearly half displaying significant or apparent elevational range contractions. In woodland birds, asymmetries of shifts in reference points led to expansions in extent in low elevation species and contractions in high elevation species. Generally, migrants, species with smaller mass, smaller relative brain size, smaller hand-wing index, and generalists in diet, habitat, and elevation had greater upslope shifts. While elevational shifts in European birds were heterogenous and species-specific, many were rapid, and species traits associated with resource preference and adaptive capacity were associated with common patterns of elevation.</p>
Unexpected microbial metabolic responses to elevated temperatures and nitrogen addition in subarctic soils under different land-use
<p>This repository contains all necessary raw data as well as the R code used to conduct statistical analysis and create figures of the publication<br> <br><strong>Unexpected microbial metabolic responses to elevated temperatures and nitrogen addition in subarctic soils under different land-use</strong></p><p>Julia Schroeder1, Tino Peplau1, Edward Gregorich2, Christoph C. Tebbe3, Christopher Poeplau1</p><p>1 Thünen Institute of Climate-Smart Agriculture, Bundesallee 68, 38116 Braunschweig, Germany<br>2 Research and Development Centre, Central Experimental Farm, Agriculture and Agri-Food Canada, Ottawa, Canada<br>3 Thünen Institute of Biodiversity, Bundesallee 65, 38116 Braunschweig, Germany</p><p>DOI: https://doi.org/10.1007/s10533-022-00943-7 </p><p>This study investigated how subarctic soils under different land use will respond to warming and increasing N availability to allow for better predictions of C cycling under global change. The short-term temperature sensitivity as well as N-input effects on microbial CUE, respiration, growth and turnover were assessed in a one-day incubation experiment according to the 18O-CUE approach. The warming and N response of SOM decomposition were assessed in a 50-days incubation experiment via measurement of cumulative respiration. Both experiments were conducted with the following three treatments: incubation at 10 °C, incubation at 20 °C, and incubation at 20 °C plus N-fertiliser addition at an amendment rate of 100 kg N ha-1. The response to warming or N addition were expressed as response ratios RRT = 20°C/10°C and RRN = 20°C+N/20°C for warming and N response, respectively.</p><p>The R code was developed under R v3.6.3 and adapted to work under version R v.4.1.2.</p><p>The repository includes the following files:</p><ul><li>general_soil_parameters_per_sample.csv - general soil data for each field sample (n=27)</li><li>general_soil_parameters_per_plot.csv - general soil data assessed on pooled replicated field samples (n=9)</li><li>respiration_over_50d_incubation.csv - respiration rate and cumulative respiration for each time-point and laboratory sample over the 50-days incubation</li><li>sample_data.csv - data measured for each laboratory sample (n=81)</li></ul><p> </p><ul><li>Warming_and_nitrogen_response_of_CUE_in_subarctic_soils.Rproj - Rproject (load project to work on provided scripts and data)</li><li>load_data_script.R - loads required data</li><li>absolute_values_script.R - summary of absolute ranges of parameters per land-use type and site</li><li>absolute_linear_mixed_effects_model_script.R - run statistical analysis</li><li>correlograms_absolute_soil_params_script.R - correlation analysis to identify what drives absolute values</li><li>plot_correlations_absolute_soil_params_script.R - plot drivers of CUE and cumulative respiration</li><li>RRT_RRN_calculation_script.R - calculates response ratios</li><li>plot_RRT_RRN_script.R - plot response ratios</li><li>RRT_RRN_linear_mixed_effects_models_script.R - run statistical analysis</li><li>correlograms_RRT_RRN_soil_param_script.R - correlation analysis to identify drivers of response ratios</li><li>plot_correlations_RRT_RRN_soil_params_script.R - plot drivers of response ratios</li><li>RRT_RRN_resprate_cumulresp_over_time_50d_incubation_script.R - plot response ratios over time course</li></ul>
High elevation forest age structure across an elevational gradient in the Greater Yellowstone Ecosystem
<p>Dataset for Blomdahl et al. 2022. Drivers of forest change in the Greater Yellowstone Ecosystem. Journal of Vegetation Science. </p> <p>See publication for site description and methods. </p> <p>Descriptions for variables in “trees_seedlings.csv”:</p> <p><strong>Plot_ID: </strong>Plot identifier. Nomeclature follows transect name and plot number. ECO="Ecotone" transect, SBM="South Bird Mountain" transect.</p> <p><strong>Year_Sampled: </strong>Samples collected 2017-2019.</p> <p><strong>Tree_ID: </strong>Identifier for unique trees and seedlings. </p> <p><strong>Core: </strong>Tree core sample identifier. Applies only to trees (cores not taken from seedlings). Generally, 2 cores were taken per Tree >5 cm DCH, though sometimes up to 4 were collected if a sample was rotten.</p> <p><strong>Sample_ID: </strong>Identifier for unique samples, some of which come from the same tree (for unique individuals: "Tree_ID"). Applies to trees and seedlings.</p> <p><strong>Form: </strong>Stems >5 cm diameter at coring height (DCH), coring height=30 cm; Seedlings >30: Stems <5 cm DCH and >30 cm in height (sometimes referred to as "saplings"); Seedlings <30: Stems <30 cm in height</p> <p><strong>Species: </strong>ABLA=<em>Abies</em> <em>lasiocarpa</em>, PIAL=Pinus <em>albicaulis</em>, PICO=<em>Pinus</em> <em>contorta</em>, PIEN=<em>Picea</em> <em>engelmannii</em>, PSME=<em>Pseudotsuga</em> <em>menziesii</em></p> <p><strong>Diam_30_cm: </strong>Diameter (cm) at 30 cm sample height.</p> <p><strong>Diam_0_cm: </strong>Diameter (cm) at 0 cm sample height (i.e., the base). Only seedlings were measured at base, not trees.</p> <p><strong>Seedling_Ht_cm: </strong>Length of seedling stem (cm).</p> <p><strong>Bark_Thick_cm: </strong> Bark thickness (cm). Not recorded in 2018. Bark thickness assumed to be <0.1 cm for seedlings.</p> <p><strong>Live_Dead: </strong>Live/Dead status when sampled. L=Live, D=Dead.</p> <p><strong>Canopy: </strong>Canopy position. D=Dominant, C=Codominant. S=Suppressed. Not recorded in 2017. All seedlings assumed suppressed.</p> <p><strong>Outer_Ring: </strong>Last complete year of growth, generally one year prior to Year_Sampled for live trees. Mortality year for dead trees.</p> <p><strong>Inner_Ring:</strong> Year of innermost ring measured in tree core sample measured at 30 cm sample height. Does not apply to seedlings, which were sampled as cross sections, and therefore the pith was always measureable.</p> <p><strong>Pith_30: </strong>Year of the first ring of the tree or sapling, measured at 30 cm sampling height. </p> <p><strong>Pith_0: </strong>Year of the first ring of the seedling, measuring at 0 cm sampling height (i.e., the base). Applies only to seedlings, which were destructively sampled at the base.</p> <p><strong>Estab_Year: </strong>Estimated year of establishment for trees and saplings, same as Pith_0 for seedlings. See methods of Blomdahl et al., 2022, for how establishment year was estimated.</p> <p><strong>Age:</strong> Estimated age of the tree.</p>
Supplementary data for "How adequately are elevated moist layers represented in reanalysis and satellite observations?"
<p>The NetCDF files are the collocation datasets over Manus Island between GRUAN radiosondes, ERA5, the CLIMCAPS Aqua Level 2 retrieval dataset and the IASI L2 Climate Data Record (CDR). The collocation criteria are 30 minutes and 50 km. Additional filter criteria for the individual datasets and processing steps are described in the manuscript.</p> <p>The datasets are created using the collocation toolkit included in the python package "typhon". Variables in each dataset are split into two groups that represent the two collocated datasets. Each group contains a selection of the original dataset's variables, which are used in the manuscript such as H2O VMR, temperature, cloud fraction, etc. The variables are organized along the dimension "collocation" and along dataset and variable specific additional dimensions. Further documentation about the collocation toolkit and the structure of the resulting datasets can be found at https://github.com/atmtools/typhon.</p> <p> </p> <p> </p>
Dataset of blow fly (Diptera: Calliphoridae) species observed along an elevational gradient on Mt. Etna, Sicily.
<p>This dataset contains count data for blow flies (Diptera: Calliphoridae) collected at four different elevations along an altitudinal gradient around Mt. Etna, in Sicily (Italy). Samples were collected to determine changes in blow fly community assembly as elevation changes.</p> <p>BlowflyAltitudeSicily_Data.csv is a file that contains the raw count data for species separated by both elevation and sex of the identified specimens.</p> <p>BlowflyAltitudeSicily_Methods.docx is a summarized version of the sampling method relevant to interpreting the data.</p> <p>BlowflyAltitudeSicily_Descriptive.txt is a file describing the column headers in "BlowflyAltitudeSicily_Data.csv".</p>
Data associated with: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water
<p>Elevated atmospheric CO<sub>2</sub> (eCO<sub>2</sub>) influences the carbon assimilation rate and stomatal conductance of plants and thereby can affect the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO<sub>2</sub> in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO<sub>2</sub> effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO<sub>2</sub> effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO<sub>2</sub> concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO<sub>2</sub> effects. The signal in gross primary production (GPP) emerges at relatively low CO<sub>2</sub> increase (Δ[CO<span>2</span>] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO<sub>2</sub> effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO<sub>2</sub> increase (Δ[CO<sub>2</sub>] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO<sub>2</sub> is detectable earlier for variables of the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO<sub>2</sub> effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.</p>
Data on elevation of Heixiluo gully after a debris flow event
<p>The data is the elevation of gully after the debris flow in the Heixiluo, which is used in the paper submitted to Geophysical Research Letters (Modeling Progressive Erosion of Consolidated Landslide Dams by Debris Flows, [Paper # 2022GL101764]). </p>
The Response of Bed Elevation to Small-Scale Hydrodynamics within Coastal Mangroves
<p>Dataset for the paper titled "The Response of Bed Elevation to Small-Scale Hydrodynamics within Coastal Mangroves", including raw and processed data.</p>
Simulating flow forming/spinning of as-cast aluminum at elevated temperature: example implicit & explicit FEA
<p>This collection of files largely automates the creation and running of FEA models of rotary forming at temperature. The modelling approaches are detailed further here:</p> <p>M.J. Roy, D.M. Maijer, Analysis and modelling of a rotary forming process for cast aluminium alloy A356, Journal of Materials Processing Technology, Volume 226, 2015, Pages 188-204, ISSN 0924-0136, http://dx.doi.org/10.1016/j.jmatprotec.2015.06.036.<br> </p> <p>Briefly, the multi-stage model was developed with MATLAB 7.2 and Abaqus 11.2 and configured to run on a Linux-based system with PBS functionality, last tested on a muti-node CentOS 5 system. The main script is <strong>FFauto.m</strong>, which will write input files and user subroutines and call <strong>FFauto_Abaqus11Submit.m</strong> to run the input files or intermediate post-processing to set up the next job. More specifically:</p> <ol> <li>FFauto will write an input deck based on 2D implicit heat transfer and then run it.</li> <li>Once the analysis is complete, it will perform some cursory post processing by writing an Abaqus Python script and then submitting that.</li> <li>Based on the post-processing of the implicit analysis, it will then generate a 3D explicit forming analysis input file. Depending on the operator's input, this can include an explicit cooling step as well.</li> <li>It will then submit the 3D analysis.</li> </ol> <p>Note that steps can be skipped - that is, if the results for an implicit heat transfer calculation are available, then it will use those results to generate the explicit step(s).</p> <p>Note that the implicit user subroutine *uhard.f contains a DFLUX subroutine in addition to the UHARD subroutine. This was not employed in the published work. Leave the <em>ArtHeat</em> variable as <em>True</em> to both speed up simulation times and get similar results as published.</p> <p>Running <strong>FFauto.m</strong> is accomplished by submitting the <strong>FFauto4.pbs</strong> file.</p>
Data from: Extreme elevational migration spurred cryptic speciation in giant hummingbirds
<p>The eco-evolutionary drivers of species niche expansion or contraction are critical for biodiversity but challenging to infer. Niche expansion may be promoted by local adaptation or constrained by physiological performance trade-offs. For birds, evolutionary shifts in migratory behavior permit broadening of the climatic niche by expansion into varied, seasonal environments. Broader niches can be short-lived if diversifying selection and geography promote speciation and niche subdivision across climatic gradients. To illuminate niche breadth dynamics, we can ask how 'outlier' species defy constraints. Of the 363 hummingbird species, the giant hummingbird (<em>Patagona gigas</em>) has the broadest climatic niche by a large margin. To test the roles of migratory behavior, performance trade-offs, and genetic structure in maintaining its exceptional niche breadth, we studied its movements, respiratory traits, and population genomics. Satellite and light-level geolocator tracks revealed an >8,300-km loop migration over the Central Andean Plateau. This migration included a three-week, ~4,100 m ascent punctuated by upward bursts and pauses, resembling the acclimatization routines of human mountain climbers, and accompanied by surging blood-hemoglobin concentrations. Extreme migration was accompanied by deep genomic divergence from high-elevation resident populations, with decisive postzygotic barriers to gene flow. The two forms occur side-by-side but differ almost imperceptibly in size, plumage, and respiratory traits. The high-elevation resident taxon is the world's largest hummingbird, a new species that we describe and name here. The giant hummingbirds demonstrate evolutionary limits on niche breadth: When the ancestral niche expanded due to evolution (or loss) of an extreme migratory behavior, speciation followed.</p>
Data from: Higher spatial than seasonal beta diversity of soil protists along elevation gradients
<p>This data package contain the data and R script to reproduce the analyses of the paper from Bruni <em>et al.</em> (in press).</p> <p>It contains:</p> <ul> <li><strong>protist_spatiotemporal_turnover_site_parameters.xlsx</strong>: the list of sites used in this study with their (label, location, geography coordinates, habitat, ENA project and sample accessions) and soil abiotic parameters. Abbreviations and units are as follows: Res_hum, residual humidity [%]; Org_mat, soil organic matter [%]; C_org, organic carbon [mg ∙ g-1]; N_org, organic nitrogen [mg ∙ g-1]; P_bio, bioavailable phosphate [mg ∙ g-1]; C_N_ratio, carbon org. / nitrogen org. ratio; N_P_ratio: nitrogen org. / phosphorus bioavailable ratio.</li> <li><strong>protist_spatiotemporal_turnover_data.RData</strong>: dataset in rda format (R core team, 2024) containing the ASV read's abundance per site matrix (object "mat"), the ASV taxonomic assignments (object "taxo"), the ASV sequences (object "asv") and the CRU-TS monthly climatic data corresponding to the sampled site's location and dates (object "cruts").</li> <li><strong>protist_spatiotemporal_turnover_analyses.R</strong>: R script to reproduce all analyses and figures of Bruni <em>et al.</em> (in press)</li> </ul> <p> </p> <p>References:</p> <p>Bruni, E. P., Lorite, J., Peñas, J., Mulot, M., Fournier, B., Vittoz, P., Mitchell, E. A. D., & Lentendu, G. (2024). Higher spatial than seasonal beta diversity of soil protists along elevation gradients. Frontiers of Biogeography, 17, 1–17. DOI:<a href="https://doi.org/10.21425/fob.17.132637">10.21425/fob.17.132637</a></p> <div> <div>R Core Team. (2024). <em>R: a language and environment for statistical computing</em> (4.2.2) R Foundation for Statistical Computing. <a href="https://www.r-project.org/">https://www.r-project.org/</a></div> </div>
Fig. 4 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 4. Cnemaspis anslemi sp. nov. male holotype (NMSL.2019.14.01) in life in-situ. (A) Dorsal view of the full body displaying the typical color pattern and a straight black middorsal dash over midpoint of neck, (B) Ventral aspect showing gular and femoral colorations, (C) lateral view showing labial coloration and zigzag pattern, (D) dorsal view of the full body of female paratype (NMSL.2019.14.02) in life in-situ from Udamaliboda, Samanala Nature Reserve, Sri Lanka. Photos: Kanishka Ukuwela and Suranjan Karunarathna.
Fig. 5 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 5. General habitat of Cnemaspis anslemi sp. nov. at Udamaliboda, Samanala Nature Reserve, Kegalle District, Sri Lanka. (A) Complete view of the forest hill, (B) shady forest with thick leaf litter, (C) hundred years old house made using clay and bricks, also with wattle and daub, (D) communal egg laying site on a clay wall. Photos: Madhava Botejue and Suranjan Karunarathna.
Fig. 3 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 3. Dorsal and ventral aspects of the type series of Cnemaspis anslemi sp. nov. (A) Male holotype, NMSL.2019.14.01, (B) female paratype, NMSL.2019.14.02, and (C) female paratype, NMSL.2019.14.03 from Udamaliboda, Samanala Nature Reserve, Sri Lanka. Photos: Suranjan Karunarathna.
Fig. 2 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 2. Close-ups of Cnemaspis anslemi sp. nov. male holotype (NMSL.2019.14.01): (A) dorsal, (B) lateral, (C) ventral aspects of head, (D) scales on lateral surface of trunk, (E) smooth ventral scales, (F) homogeneous dorsal scales, (G) cloacal characters with femoral pores, (H) subdigital lamellae on pes, (I) subdigital lamellae on manus, (J) lateral side of tail, (K) oval shaped subcaudals, and (L) dorsal scalation of tail. Photos: Suranjan Karunarathna.
Fig. 6 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 6. Morphological characters that differentiate the species of podihuna and kandiana clades. (A) Scales and pores around vent in podihuna clade, (B) scales and pores around vent in kandiana clade, (C) keeled and imbricate belly scales, (D) smooth and imbricate belly scales, (E) heterogeneous keeled dorsal granules, (F) homogeneous smooth dorsal granules, (G) smooth sub-hexagonal subcaudals in podihuna clade, (H) smooth, solid hexagonal subcaudals in podihuna clade, (I) smooth, small, and irregular subcaudals in kandiana clade, (J) keeled, small, and irregular subcaudals in kandiana clade (yellow arrows: unpored posterior femoral scales in males; blue arrows: femoral pores in males; green arrows: unpored anterior femoral scales in males; red arrows: precloacal pores in males; white arrows: unpored interfemoral scales in males).
Fig. 1 in A new species of dwarf day gecko (Reptilia: Gekkonidae: Cnemaspis) from lower-elevations of Samanala Nature Reserve in Central massif, Sri Lanka
Fig. 1. Currently known distribution of Cnemaspis anslemi sp. nov. (Udamaliboda–star), and related species: C. phillipsi (Gammaduwa–traingle), C. scalpensis (Gannoruwa–square), C. gemunu (Haggala–circle), and C. godagedarai (Ensalwatte– diamond) in Sri Lanka.
Species-specific differences in bumblebee worker body size between elevations: Implications for pollinator community structure under climate change
<p>Code and dataset for manuscript titled "<span>Species-specific differences in bumblebee worker body size between elevations: Implications for pollinator community structure under climate change". Authors: Caterina Massa, Janneke Hille Ris Lambers, Sarah K. Richman. Manuscript accepted to Journal of Pollination Ecology in May 2024. All data collected and analyzed by the authors.<br></span></p>
Figure 1 in Why may the same species have different elevational ranges at different sites in New Guinea?
Figure 1. Example of the Massenerhebung effect: variation in the elevational ceiling and floor of the Island Leaf Warbler Seicercus poliocephalus on New Guinea mountains. Note that the warbler's ceiling (upper graph) and floor (lower graph) are higher on Central Range peaks than on outlier peaks; that they tend to be higher on higher peaks (summit elevation, abscissa); that they tend to be higher on inland-facing or interior-facing outlier transects than on coast-facing outlier transects; and that they tend to be higher on outlier transects further from the coast than on outlier transects nearer the coast. Data from Table 4.
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.