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Data: Applying stochastic and Bayesian integral projection modeling to amphibian population viability analysis
<p>Integral projection models (IPMs) can estimate the population dynamics of species for which both discrete life stages and continuous variables influence demographic rates. Stochastic IPMs for imperiled species, in turn, can facilitate population viability analyses (PVAs) to guide conservation decision-making. Biphasic amphibians are globally distributed, often highly imperiled, and ecologically well-suited to the IPM approach. Herein, we present the first stochastic size- and stage-structured IPM for a biphasic amphibian, the U.S. federally threatened California tiger salamander (<em>Ambystoma</em> <em>californiense</em>; CTS). This Bayesian model reveals that CTS population dynamics show the greatest elasticity to changes in juvenile and metamorph growth and that populations are likely to experience rapid growth at low density. We integrated this IPM with climatic drivers of CTS demography to develop a PVA and examined CTS extinction risk under the primary threats of habitat loss and climate change. The PVA indicates that long-term viability is possible with surprisingly high (20–50%) terrestrial mortality, but simultaneously identified likely minimum terrestrial buffer requirements of 600–1000 m while accounting for numerous parameter uncertainties through the Bayesian framework. These analyses underscore the value of stochastic and Bayesian IPMs for understanding both climate-dependent taxa and those with cryptic life histories (e.g., biphasic amphibians) in service of ecological discovery and biodiversity conservation. In addition to providing guidance for CTS recovery, the contributed IPM and PVA supply a framework for applying these tools to investigations of ecologically-similar species.</p>
Database on Projects, Programmes, and Institutions (PPIs) related to agroecology
<p>This database holds the list of projects, funding programmes, and institutions (PPIs) dealing with agroecology research in Europe identified in the mapping activities carried out in the Task 1.3 of AE4EU project (https://www.ae4eu.eu/). The final version of the database was released as annex of the project Deliverable D 1.3 “Report on agroecological research development”. In this public version all sensitive data (eg., email contacts) were removed from the file.</p> <p>The database is composed by the following different sheets including:</p> <ul> <li><strong>European projects</strong> with the list of the identified research projects related to agroecology funded by the European Union under the Horizon 2020 framework programme from 2014 onwards</li> <li><strong>Transnational projects</strong> with research projects funded by programmes co-framed and co-funded by Member States and European Union (i.e., ERA-NETs in the past Horizon framework and European Partnerships of Horizon Europe)</li> <li><strong>National projects</strong> on agroecology funded by national funding programmes in the different European countries from 2014 onwards</li> <li><strong>European programmes</strong>. This list reports the topics and calls from which the selected European projects were funded. The list was also enriched including topics and calls from the new working programme 2021-2022 (Horizon Europe Programme);</li> <li><strong>Transnational programmes</strong> which financed the identified transnational research projects</li> <li><strong>National programmes</strong>. Here the information on the national agroecology programmes provided by relevant key informants (i.e., national funding agencies and bodies, AE4EU partners) were included,</li> <li><strong>Participants</strong> with the list of public or private research institutions, organizations, and enterprises involved as partners of the identified European, Transnational and National research projects</li> </ul>
Re-projection alignment for trajectory perturbation estimation in micro-tomography: simulation data
<p>Simulation cone-beam-tomography data sets including:</p> <p>a) Synthetic phantom tomogram (3 spheres + random ellipsoids)</p> <p>b) Forward projection of phantom using low-pitch-helix (LPH) trajectory</p> <p>c) Forward projection of phantom using space-filling (SF) trajectory</p> <p>d) Synthetic per-projection perturbations</p>
TNO-CO2_CIRCE projections (2018-2050)
<p>To provide modellers with an emission dataset that is indicative of the possible future emissions in Europe under two different policy pathways we use two global emission scenarios developed by the EDGAR team in the CIRCE project (Doering et al., 2010). The selected scenarios are a business-as-usual (BAU) and a climate change (CC) scenario. The two CIRCE scenarios contain detailed information about the development of individual source sector categories. By coupling these scenarios to TNO-CAMS gridded CO2 data, the emission changes in each grid-cell and for each region can be estimated in a spatially explicit manner. The projections start from the latest historic year in the the TNO_CAMS-CO2 data set, being 2014. The emission data can be used for e.g. for sensitivity tests, for example when designing a possible future observational system. The years covered in the data set are 2018, 2020, 2023, 2028, 2030, 2033, 2050. This selection has been made to include the 5-year time steps fro the global stocktake in the Paris Agreement. </p> <p>The emission grid consists of UNECE-Europe in WGS84 projection (lon-lat) with a spatial resolution of 1/8 x 1/16 degrees (lon x lat). The lower left of the grid is at lon = -60, lat = 30 and the upper right is at lon = 60, lat = 72.</p> <p>The netcdf grid files (.nc) contain annual total emissions per grid cell for the years 2018, 2020, 2023, 2028, 2030, 2033, 2050. A separate file has been prepared for each year and each scenario (BAU or CC). The unit in the .nc files is kg/gridcell/yr</p> <p>Sectoral breakdown uses the SNAP classification. Compared to the default SNAP1 sectors (1 to 10), the following change was made:</p> <ul> <li> <p>SNAP 3 and SNAP 4 are grouped as SNAP 34</p> </li> <li> <p>SNAP 7 is split in SNAP 71 to 75</p> </li> </ul> <p>The dataset is described in </p> <p>Denier van der Gon, H.A.C., J.J.P. Kuenen, G. Janssens-Maenhout, U. Döring, S. Jonkers, A.J.H. Visschedijk., TNO_CAMS high resolution European emission inventory for anthropogenic and biogenic CO<sub>2</sub> for 2000-2014 and future years following two different pathways, ESSD, in preparation, 2017.</p> <p> </p>
MolSSI Reference Integral Project - Reference Datafiles
<p>These files contain integral data calculated as part of the MolSSI Integral Reference Project (MIRP).</p> <p>As part of MIRP, integrals are computed via arbitrary-precision interval arithmetic. These values are then rounded to the nearest double-precision value, and stored in these data files. The files are compressed with bzip2, and should be uncompressed before use.</p> <p>Currently, only ERI for gaussian-type orbitals are computed. The basis set data is included within the reference files themselves.</p> <p>Software for creating these files (including documentation), and examples of reading from them, can be found at DOI 10.5281/zenodo.1063526</p> <p>More information about the reference project can be found at http://molssi.org and at https://github.com/MolSSI/MIRP</p>
Figure 2. Catadioptric projection modelled by the unit sphere-Design and Implementation of a Fully Autonomous UAV's Navigator Based on Omni-directional Vision System
<p>Since the beginning of UAV, the map building was one of the most addressed problems by<br> researchers. Several researchers used Omni directional vision for robot navigation and map<br> building. Because of the wide field of view in Omni directional sensors, the robot does not need to<br> look around using moving parts (cameras or mirrors) or turning the moving parts. The global view<br> offered by Omni directional vision is especially suitable for highly dynamic environments. The<br> Omni directional vision system consists of a hyperbolic mirror, a USB color digital camera<br> (Logitech C905) and a regulation device.</p>
FIGURE 3 in Freshwater fish richness baseline from the São Francisco Interbasin Water Transfer Project in the Brazilian Semiarid
FIGURE 3 | Freshwater fish species from the São Francisco Interbasin Water Transfer Project basins in the Brazilian semiarid. A = Hemigrammus brevis, endemic species of São Francisco Ecoregion (SFRE); B = Moenkhausia costae and C = Psellogrammus kennedyi, shared species between SFRE and Mid-Northeastern Caatinga Ecoregion (MNCE); D = Aspidoras menezesi, endemic species of Jaguaribe basin (JAG); E = Hypostomus sertanejo, endemic species of MNCE; F = Parotocinclus spilurus, endemic and endangered species of JAG; G = Tatia bockmanni, endemic species of SFRE; H = Cichlasoma orientale, shared species from all basins of SFR-IWT; I = Geophagus brasiliensis, shared species between SFRE and MNCE; J = Colossoma macropomum, non-native species shared between SFRE and Piranhas-Açu basin; K = Parachromis managuensis, non-native species shared between SFRE and Paraíba do Norte basin; L = Xiphophorus helleri, non-native species of JAG.
FIGURE 2 in Freshwater fish richness baseline from the São Francisco Interbasin Water Transfer Project in the Brazilian Semiarid
FIGURE 2 | Sampling sites in the São Francisco Interbasin Water Transfer Project basins in the Brazilian semiarid. A = Canals under construction near the rio São Francisco main channel, and B = near Sertânia, Pernambuco State (PE), C = Rio Pajeú, tributary of the São Francisco basin, PE, D = Rio São Francisco near Petrolina, PE, E = Temporary pool in rio Jaguaribe basin in Russas, Ceará State (CE), F = Rio Jaguaribe in Crato, CE, G = Rio Apodi-Mossoró in Pau dos Ferros, Rio Grande do Norte State (RN), H = Rio Apodi-Mossoró in Pau dos Ferros, RN, I = Rio Seridó, tributary of the Piranhas-Açu basin in Caicó, RN, J = Rio Piranhas-Açu, Jardim de Piranhas, RN, K = Rio Paraíba do Norte in Barra de Santana, Paraíba State (PB), L = Rio Paraíba do Norte in São João do Cariri, PB.
FIGURE 1 in Freshwater fish richness baseline from the São Francisco Interbasin Water Transfer Project in the Brazilian Semiarid
FIGURE 1 | Sampling sites of the freshwater fish species in the São Francisco Interbasin Water Transfer Project basins in the Brazilian semiarid.
# Replication code and data for: Global projections of heat exposure of older adults
<p># Replication code and data for: Global projections of heat exposure of older adults<br>By Giacomo Falchetta, Enrica De Cian, Ian Sue Wing and Deborah Carr<br>Nature Communications. DOI: 10.1038/s41467-024-47197-5</p> <p>An output data file, containing grid-cell level counts of people by age group, of climate hazard indicators, and of heat exposure metrics for both the historical climate and current demography and for future scenarios and projections is contained in the repository ("aging_climate_output_data.csv"). </p> <p>Software requirements:<br>- R v4.3+: https://cran.r-project.org/bin/windows/base/<br>- RStudio: v2023.06.0+: https://posit.co/download/rstudio-desktop/<br>- Package dependencies: raster, sf, tidyverse, rasterVis, rgdal, maptools, pbapply, terra, knitr, kableExtra, modelsummary, openxlsx, xtable, ggforce, maptools, weights, spatstat, rworldmap, scales, patchwork, stars, viridis, devtools, stargazer, readxl, nominatimlite, urbnmapr</p> <p>To replicate the analysis:<br>- Clone the replication code repository from https://github.com/giacfalk/aging_climate<br>- Download input data from this Zenodo data repository<br>- Download all the 1km age and gender-stratified global population counts rasters from the following WorldPop page https://hub.worldpop.org/geodata/summary?id=24798 and put them in a subdirectory of the working directory called "AGEPOP"<br>- Run the "project_pop.R" script to generate gridded age-stratified population data for each SSP scenario<br>- Run the "compare_pop_projections.R" file to compare the generated gridded age-stratified population data with an array of pre-existing sources from different countries and produce a summary comparison table (NOTE: before running the script, decompress the "new_comparison_data.zip" folder into the working directory)<br>- Run "projections_exposure_m.R" to quantify heat exposure and generate the figures and tables reported in the paper</p> <p>To process the data and run succesfully, the script requires a computer with at least 32GB RAM. The running time varies based on CPU characteristics, but a runtime of at least 2 hours should be expected to generate all the output data, figures, and tables. All output files are saved in the working directory.</p> <p>___</p> <p>This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.</p> <div> <div> <div> </div> <div> <div> <div> </div> <div> <p> </p> <p> </p> </div> </div> </div> </div> </div>
Рис. 7. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска B. cylindrica (А), фитомассы (В), проективного покрытиЯ (С), твердости грунта на глубине 5–10 см (D) на участке № 1 в 2010 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 7. 3D–diagrams of the abundance spatial distribution of the snail B. cylindrica (A), phytomass (B), plants projective cover (C), 0–10 cm layer soil penetration resistance (D) at the site 1 in 2010. (axes X and Y presented in meters). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach
Рис. 7. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска B. cylindrica (А), фитомассы (В), проективного покрытиЯ (С), твердости грунта на глубине 5–10 см (D) на участке № 1 в 2010 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 7. 3D–diagrams of the abundance spatial distribution of the snail B. cylindrica (A), phytomass (B), plants projective cover (C), 0–10 cm layer soil penetration resistance (D) at the site 1 in 2010. (axes X and Y presented in meters).
Data from: Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA
<p><span>Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m<sup>3</sup> of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.</span></p> <p><span>The database is organized in five datasets in a csv format (columns separated by commas): (1) metadata providing the location, date, and time for each sample, along with sequencing depth and other essential information (metadata.csv); (2) species-level OTU tables per sample describing the number of sequences assigned to each species (otu.table.csv 3); (3) taxonomic classification of each species-level OTU (taxonomy.csv); (4) closest matching sequences and their taxonomy for ASVs in putatively fungal pseudophyla, which are included in (2) and (3) (fungi_pseudophyla.csv); and (5) closest matching sequences and their taxonomy for ASVs in putatively non-fungal pseudophyla, which are not included in the other datasets (nonfungi_pseudophyla.csv). The first four datasets can be linked to each other using the unique sample codes and the unique identifiers for species-level OTUs. </span><span>The three first datafiles are also provided in allData.RData which can be read into R as load("allData.RData").</span></p>
IR analysis of ([Hmim][OTf])3Zn - NCN project OPUS, grant no. 2020/37/B/ST8/00693.
<p>Dataset contains results obtained during the NCN project OPUS, grant no. 2020/37/B/ST8/00693. The file presents IR analysis of ([Hmim][OTf])3Zn.</p>
Po delta to Gulf of Trieste: Microbiological connectivity study and field testing of a Video-CTD probe prototype (JERICO-S3 PoGo project)
<p>ADCP and CTD data from field campaigns at S1-GB site (Po delta, Italy) performed in the scope of the JERICO-S3 PoGo project. This is raw data as collected by both instruments. The CTD prototype is under development at National Institute of Biology, Marine Biology Station Piran and hasn't been fully calibrated. The new recalibrated values have been added to mini-CTD-recalibrated archive.<br>The project report is available in this repository and at: https://www.jerico-ri.eu/ta/call-program/third-call/</p>
Рис. 6. Ювенильные раковины Laternula elliptica: А1, А3 – левые створки, внешний вид, H×L=3.0×4.4 мм; А2 – вид со стороны дорсального краЯ на сдвоенные створки, обраЗуюЩие по Заднему краю ЗиЯние; А4 – Замок, соединЯюЩий фрагменты раЗрушенных створок (штриховка); Б1 – праваЯ створка, внешний вид, H×L=8.5×14.0 мм; Б2 – внутреннЯЯ поверхность правой створки. Фрагменты раковины вЗрослого моллюска (L=69.7 мм): В1 – вид со стороны дорсального краЯ; В2 – фрагмент правой створки, вид сбоку. ОбоЗначениЯ: ЗК – Задний край; дК – дорсальный край; сКп – складки периостракума; м – макушка; мщ – макушечнаЯ Щель; пр – продиссоконх; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; дпЛ – дополнительнаЯ пластинка; син – синус. Fig. 6. Juvenile shells of Laternula elliptica: A1, A3 – left valves, external view, H×L=3.0×4.4 mm; A2 – paired valves, dorsal view, showing gape through which the siphon project; A4 – hinge with chondrophore and buttress, internal view; Б1– right valve, external view, H×L=8.5×14.0 mm; Б2 – right valve, internal view. Adult shell (L=69.7 мм): B1 – fragment of right valve, dorsal view; B2 – fragment of right valve, lateral view on umbo. Notes: ЗК – posterior margin; дК – dorsal margin; сКп – periostracal wrinkles; м – umbo; мщ – umbonal crack; пр – prodissoconch; хр – chondrophore; ппЛ – buttress; дпЛ – additional supporting plate; син – sinus. in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 6. Ювенильные раковины Laternula elliptica: А1, А3 – левые створки, внешний вид, H×L=3.0×4.4 мм; А2 – вид со стороны дорсального краЯ на сдвоенные створки, обраЗуюЩие по Заднему краю ЗиЯние; А4 – Замок, соединЯюЩий фрагменты раЗрушенных створок (штриховка); Б1 – праваЯ створка, внешний вид, H×L=8.5×14.0 мм; Б2 – внутреннЯЯ поверхность правой створки. Фрагменты раковины вЗрослого моллюска (L=69.7 мм): В1 – вид со стороны дорсального краЯ; В2 – фрагмент правой створки, вид сбоку. ОбоЗначениЯ: ЗК – Задний край; дК – дорсальный край; сКп – складки периостракума; м – макушка; мщ – макушечнаЯ Щель; пр – продиссоконх; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; дпЛ – дополнительнаЯ пластинка; син – синус. Fig. 6. Juvenile shells of Laternula elliptica: A1, A3 – left valves, external view, H×L=3.0×4.4 mm; A2 – paired valves, dorsal view, showing gape through which the siphon project; A4 – hinge with chondrophore and buttress, internal view; Б1– right valve, external view, H×L=8.5×14.0 mm; Б2 – right valve, internal view. Adult shell (L=69.7 мм): B1 – fragment of right valve, dorsal view; B2 – fragment of right valve, lateral view on umbo. Notes: ЗК – posterior margin; дК – dorsal margin; сКп – periostracal wrinkles; м – umbo; мщ – umbonal crack; пр – prodissoconch; хр – chondrophore; ппЛ – buttress; дпЛ – additional supporting plate; син – sinus.
High-end projections of Southern Ocean warming and Antarctic ice shelf melting in conditions typical of the end of the 23rd century
<h2><strong>High-end projections of Southern Ocean warming and Antarctic ice shelf melting in conditions typical of the end of the 23rd century</strong></h2> <p>To evaluate the response of the Southern Ocean and Antarctic ice shelf cavities to an abrupt change to high-end atmospheric<br>conditions typical of the late 23rd century under the SSP5-8.5 scenario, in Mathiot and Jourdain (2023, submitted soon), we conducted 2 experiments. Our reference experiment (called REF) is driven by present day atmospheric condition. In the 23rd century simulation (called PERT), the present day atmospheric forcing is perturbed by the anomaly (2260-2299 minus 1975-2014) extracted from monthly outputs of the IPSL-CM6A-LR projections under the SSP5-8.5 emission scenario. REF is run over the latest 40 years and PERT is run for 100y starting from PERT at year 1999.</p> <p><strong>This data set contains:</strong></p> <ul> <li>The atmospheric forcing anomalies used to perturbed our reference atmospheric forcing in the PERT simulation;</li> <li>30y monthly climatologies of multiple variables (ocean temperature, salinity, ssh, velocities, barotropic stream function, iceberg melt, ice shelf melt, sea ice concentration, thickness, velocities and snow thickness) for PERT and REF.</li> </ul> <p>All the details on each dataset have been added in separated README in ATMO_ANOMALIES and OCEAN_CLIMATOLOGIES directory.</p> <p>As stated in each README, all the detailed on the simulations and atmospheric perturbation are available in Mathiot and Jourdain (2023).</p> <p><strong>Changes with respect to v1.0.0:</strong> iceberg melt and ice shelf melt climatologies for REF and PERT has been added to the dataset (*flxT.nc files).</p> <p><strong>Reference paper:</strong> Mathiot, P. and Jourdain, N. C.: Southern Ocean warming and Antarctic ice shelf melting in conditions plausible by late 23rd century in a high-end scenario, Ocean Sci., 19, 1595–1615, https://doi.org/10.5194/os-19-1595-2023, 2023.</p> <div> <div><strong>Acknowledgements:</strong> This study was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement no. 820575 (TiPACCs) and by the French National Research Agency under grant no. ANR-19-CE01-0015 (EIS). N. Jourdain was also supported by EU-H2020 grant nos. 101003536 (ESM2025) and 869304 (PROTECT). This work was granted access to the high-performance computing (HPC) resources of CINES and TGCC under allocations A0100106035 and A0120106035 attributed by GENCI.</div> </div>
Stream temperature data for Alaska Sustainable Salmon Fund project 53007 Assessing Thermal Habitat Variability to Identify Refugia in SE Alaska Subsistence Salmon Watersheds
<p>Hourly stream temperature data were collected in eight watersheds in southeast Alaska to better understand within-watershed thermal heterogeneity. Watersheds include: Chilkat, Chilkoot, Klag, Cowee, Peterson (Juneau road system), Saltery, Kadashan, and Klawock. Site latitude and longitude are recorded in the metadata file. Data were collected with HOBO Onset Pro V2 or HOBO TidbiT MX 400 temperature loggers following the protocols in <a href="https://doi.org/10.1016/j.ejrh.2015.07.008">Mauger et al, 2015</a>. Data collection dates range from January 1, 2020 to November 2, 2023, although not all sites cover this entire date range. </p>
SSP1 and SSP3 population projections with demographic categories
<p>Demographic projections for the Shared Socioeconomic Pathways SSP1 and SSP3 scenarios with demographic breakdown for "young", "adult" and "old" populations, defined as <15 years old, 15-65 years old, and >65 years old, at 10 year intervals. Projections are calculated combining SSP population projections, UN WPP country wide demographic trends, and SEDAC demographic spatial distributions.</p> <p> </p> <p>The "interp" version of the files includes linear interpolationed values for each grid cell for every year.</p>
Supplementary Data of the project "Cross Cultural Tears - A Systematic Investigation of the Interpersonal Effects of Emotional Crying Across Different Cultural Backgrounds"
<p>Supplementary Data related to the publication: </p> <div> <p>Zickfeld, J. et al. (2021). Tears evoke the intention to offer social support: A systematic investigation of the interpersonal effects of emotional crying across 41 countries. Journal of Experimental Social Psychology, 95, 104137. <a href="https://doi.org/10.1016/j.jesp.2021.104137" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jesp.2021.104137 </a></p> </div>
A global database of nature-based carbon offset project boundaries
<p><strong>Overview</strong></p> <p>Nature-based climate solutions (NBS) have become an important component of strategies aiming to reduce atmospheric CO2 and mitigate climate change impacts. Carbon offsets have emerged as one of the most widely implemented NBS strategies, however, these projects have also been criticized for exaggerating offsets. Verifying the efficacy of NBS-derived carbon offset is complicated by a lack of readily available geospatial boundary data. Herein, we detail methods and present a database of nature-based offset project boundaries. This database provides the locations of 575 NBS projects distributed across 55 countries. Geospatial boundaries were aggregated using a combination of scraping data from carbon project registries (<em>n</em>=433, 75.3%) as well as manual georeferencing and digitization (<em>n</em>=127, 22.1%). Database entries include three varieties of carbon projects: avoided deforestation, afforestation, reforestation and re-vegetation, and improved forest management. An accuracy assessment of the georeferencing and digitizing process indicated a high degree of accuracy (intersection over union score of 0.98 +/- 0.015).</p> <p>Details about using the database are provided in the README.txt file.</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.