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1,271 results for “Tropical forests”
Long-term dynamics of tropical rain forests in permanent inventory plots, La Selva, Costa Rica (1969-1995)
Three permanent plots comprising a total of 12.4 ha were established in 1969 in tropical rain forest at La Selva Biological Station, near Puerto Viejo de Sarapiquí, in the Caribbean lowlands of Costa Rica. The plots were established in old-growth forest on three contrasting landforms: Plot 1 (4.4 ha) on old alluvial terrace; Plot 2 (4.0 ha) in swamp forest and rolling hills; and Plot 3 (4.0 ha) on steeply dissected terrain with residual soils. The data archived here include plot inventories carried out at five census dates over a period of 27 years. The inventory starting dates were 1969; 1982; 1985; 1989; and 1995. All stems 10 cm dbh or greater were tagged with a permanent numbered tag; measured in diameter at breast height and above buttresses to the nearest mm; mapped on the ground to the nearest m; and identified to species. At each census, live trees were re-measured, dead trees were recorded along with information on the manner of death, other details on the condition of the tree were noted, and new recruits were tagged, mapped, measured, and identified. The archived data include these five components: (1) The master data file, including comprehensive data on all tagged individuals in the three plots for the five censuses from 1969-1995. Each line in the data set represents an individual tagged tree or liana. The data array comprises 8689 lines (the number of tagged individuals) x 48 columns of data. The lines in the data set are ordered first by Plot number (1, 2, 3); next by subplot within each plot; and then by tag number within each subplot. (2) A list of column identifiers, describing in detail the information represented in each of the 48 columns within the master data file. The list gives a description of the data in each column, the units of measurement, and a guide to the interpretation of zeroes in the data. (3) A key to codes used in the field to describe the condition of individual trees. (4) A taxonomic reference list, including all species found
Seedling composition, growth, and dynamics in tropical rain forest, La Selva, Costa Rica (1983-1996)
Recruitment, growth, and survivorship of the regeneration stages of trees and lianas were studied in old-growth tropical rain forest at La Selva Biological Station of the Organization for Tropical Studies (OTS), near Puerto Viejo de Sarapiquí, Heredia Province, in the Caribbean lowlands of Costa Rica. A total of 48 permanent seedling transects each measuring 10 m x 0.5 m were established at random locations within three La Selva permanent forest inventory plots. The forest plots occupy contrasting landforms: Plot 1 (4.4 ha), old alluvial terrace; Plot 2 (4.0 ha), swamp forest and low hills; and Plot 3 (4.0 ha), steeply dissected terrain with residual volcanic soils. Seedling locations are georeferenced within the grid system of the permanent forest inventory plots, facilitating spatial analysis of seedling populations with respect to adult cohorts. Beginning in June 1983, all seedlings ≤ 0.5 m in height belonging to tree and liana species capable of reaching 10 cm diameter at breast height (dbh) at maturity were tagged, identified to species or morphospecies, mapped to the nearest cm, and measured in height to the nearest cm. Over a period of 18 months, a total of 6403 seedlings belonging to 167 species were tagged. Monitoring and re-measurement of all tagged individuals continued through November 1996. Data include 17 census dates over a period of 13.5 years. At the time of the final census, only 97 individuals (1.52% of the tagged seedlings) were still alive, representing 43 species (25.7% of the initial number). The largest surviving seedling had grown in height from 4 cm to 13 meters during the study period. This dataset on the regeneration stages in old-growth tropical rain forest in the La Selva permanent inventory plots forms a complement to the studies of long-term growth and demography of these species and assemblages at adult stages within the plots. Forest inventory data for trees and lianas ≥ 10 cm dbh in the permanent plots in which the seedling transec
Natural Regeneration of Puerto Rican Tropical Dry Forest Sites with Limited Burn History, Guánica Forest, 2012
This dataset documents the natural regeneration of tropical dry forest sites with limited burn history in Guánica Forest, Puerto Rico, following fire disturbance. Featuring a 29-year chronosequence, the dataset encompasses both short-term (2–5 months) and long-term (2–29 years) recovery, alongside mature forest control sites (including forest sites containing native grass). Data collection was conducted between May and August 2012 and focuses on woody tree species only. The dataset includes tree census data from seven sites (chrono_census.csv), recording species identity, stem diameter, aboveground biomass destruction, and resprouting dynamics. Additional data include species mean trait values, such as relative bark thickness and specific leaf area, to examine relationships with post-fire resprouting (chrono_traits.csv), and a species abundance matrix for evaluating community composition shifts over time (chrono_ndmsmatrix.csv). Field data were collected from circular 100 m² plots randomly placed at each site, with all woody plants tagged and identified. Stem diameters (≥1 cm) were measured at breast height (DBH) or ground height (DGH) in new-burn sites. Tree mortality was assessed, and aboveground biomass loss (0–100%) was estimated in new-burn sites. Resprouting was also quantified in short-term regeneration sites in mid-August 2012. In long-term sites, tree height was measured for the five tallest individuals. The dataset is relevant for researchers investigating tropical dry forest dynamics, fire ecology, and regeneration processes in Caribbean forest ecosystems. The dataset is complete and not ongoing.
Life History Traits of Resprouting Puerto Rican Tropical Dry Forest Trees, Guánica Forest, 1981-2018
This dataset provides trait and demographic data for 44 tropical dry forest tree species from the Guánica State Forest in southwest Puerto Rico. The study area spans 4,500 ha of semi-deciduous TDF, where the sampled species represent over 90% of all individuals with a diameter at breast height (dbh) ≥2.5 cm. The dataset integrates ten functional traits, combining newly collected measurements (2017–2018) with previously published data (Vargas et al. 2021b). Previously published data includes xylem-specific hydraulic conductivity (ks), Huber value (hv), and hydraulic safety margin (HSM), with species-level data availability ranging from 19 to 44 species, except for HSM, which was measured for six species. Trait measurements were primarily collected during the wet season (August–November), except stomatal behaviour traits (psimax, psidv, and gsmax), which were assessed during the winter dry season before leaf fall. Demographic data encompass species-specific growth rates and annual survival rates for adult trees, derived from four permanent census plots (625 m² to 10,000 m²) distributed across the forest. These plots, established in mature upland TDF on limestone substrates with mollisol soils, were monitored between 1992 and 2019. Growth rate estimates are based on diameter increments recorded at regular censuses over 20.4–26.4 years. Survival rates were calculated over a 21-year period (1998–2019), mitigating the influence of extreme drought events. Standardised measurement protocols ensured data consistency, including repeated diameter assessments at multiple stem locations and the exclusion of wet-season measurements to prevent water-related swelling artifacts. Growth rates were derived from the regression slope of dbh against time, incorporating a minimum of two dbh measurements per individual (following Poorter et al. 2010). Annual survival rate was calculated over a 21-year timespan (1998–2019) to avoid bias introduced by an intense drought in 1997. The followin
Tree Census Data of Tropical Dry Forest Succession in Permanent Plots at Palo Verde National Park, Costa Rica (1999–2004), Organization for Tropical Studies (OTS)
This data package contains tree census data from eight permanent forest plots established in 1999 across four successional sites within the tropical dry forest of Palo Verde National Park, Guanacaste, Costa Rica (10°21’N, 85°21’W). The plots were established to study forest structure, composition, and successional dynamics under different disturbance histories in the lowland dry forest ecosystem of northwestern Costa Rica. Each site represents a distinct successional stage, ranging from an early grass-dominated field (Jaragua) to an older partially disturbed remnant forest stand (Varillal). Two permanent 50×50 m plots were established at each site and subdivided into 10×10 m subplots. All woody stems with diameter at breast height (DBH) ≥ 10 cm were tagged, identified to species, and spatially referenced using X–Y coordinates within each plot. For multi-stemmed individuals, all stems meeting the diameter threshold were measured separately. Tree diameter, condition, and taxonomic identification were recorded during four measurement campaigns in 1999, 2001, 2002, and 2004. The dataset includes species identity, DBH, measurement year, individual condition, and subplot coordinates for each stem. These data provide a baseline for understanding forest regeneration, mortality, recruitment, and species composition changes in tropical dry forest succession under varying land-use histories. The dataset represents the historical component of an ongoing long-term monitoring program of forest succession conducted by the Organization for Tropical Studies at Palo Verde National Park, led, developed and supported by Eugenio González since its establishment in 1999.
Steady state carbon, nitrogen, phosphorus, and water budgets for twelve mature ecosystems ranging from prairie to forest and from the arctic to the tropics
We use the Multiple Element Limitation (MEL) model to examine the responses of twelve ecosystems - from the arctic to the tropics and from grasslands to forests - to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in annual precipitation. The ecosystems we simulated include moist acidic tundra, shrub tundra, and wet sedge tundra near Toolik Lake, Alaska, alpine dry meadow tundra near Niwot Ridge, Colorado, restored tallgrass prairie near Kellogg Biological Station, Michigan, native tallgrass prairie at the Konza Prairie, Kansas, upland and lowland boreal forest near Bonanza Creek, Alaska, temperate coniferous forest in HJ Andrews Experimental Forest, Oregon, a northern hardwood forest in Hubbard Brook Experimental Forest, New Hampshire, a transition oak-maple forest in Harvard Forest, Massachusetts, and lowland tropical rainforest near Caxiuanã National Forest, Pará, Brazil. For each of the twelve sites, we run six 100-year simulations beginning from the calibrated steady state (72 simulations total). The six simulations are: (1) increasing CO2 from 400 to 800 μmol mol-1, (2) warming from current temperatures to current plus 3.5oC, (3) decreasing precipitation from 100% to 80% of the current annual rate, (4) increasing precipitation from 100% to 120% of the current annual rate, (5) doubling of CO2, 3.5oC warming, and 20% decrease in precipitation, and (6) doubling of CO2, 3.5oC warming, and 20% increase in precipitation. The carbon, nitrogen, phosphorus, and water budgets presented here are used to calibrate the MEL model prior to running the climate change simulations. Citations and calculations for the data presented here are described in the individual site html files included in this dataset.
Ecosystem responses to changes in climate and carbon dioxide in twelve mature ecosystems ranging from prairie to forest and from the arctic to the tropics
We use the Multiple Element Limitation (MEL) model to examine the responses of twelve ecosystems - from the arctic to the tropics and from grasslands to forests - to elevated carbon dioxide (CO2), warming, and 20% decreases or increases in annual precipitation. The ecosystems we simulated include moist acidic tundra, shrub tundra, and wet sedge tundra near Toolik Lake, Alaska, alpine dry meadow tundra near Niwot Ridge, Colorado, restored tallgrass prairie near Kellogg Biological Station, Michigan, native tallgrass prairie at the Konza Prairie, Kansas, upland and lowland boreal forest near Bonanza Creek, Alaska, temperate coniferous forest in HJ Andrews Experimental Forest, Oregon, a northern hardwood forest in Hubbard Brook Experimental Forest, New Hampshire, a transition oak-maple forest in Harvard Forest, Massachusetts, and lowland tropical rainforest near Caxiuanã National Forest, Pará, Brazil. For each of the twelve sites, we run six 100-year simulations beginning from the calibrated steady state (72 simulations total). The six simulations are: (1) increasing CO2 from 400 to 800 μmol mol-1, (2) warming from current temperatures to current plus 3.5oC, (3) decreasing precipitation from 100% to 80% of the current annual rate, (4) increasing precipitation from 100% to 120% of the current annual rate, (5) doubling of CO2, 3.5oC warming, and 20% decrease in precipitation, and (6) doubling of CO2, 3.5oC warming, and 20% increase in precipitation. This dataset consists of the MEL model Windows executable, the driver and parameter file for each site, and the output files for each of the six simulations listed above.
Dataset to manuscript: Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India
<p>Raw data to the manuscript entitled "Soil organic carbon stocks and quality in small-scale tropical, sub-humid and semi-arid watersheds under shrubland and dry deciduous forest in southwestern India" by Severin-Luca Bellè, Jean Riotte, Muddu Sekhar, Laurent Ruiz, Marcus Schiedung and Samuel Abiven.</p> <p>Data files include all raw data of soil cores (20211111_Raw_data.zip), data measured on composited samples (20211111_Composite_data.zip) and DRIFT spectra (20211111_DRIFT_data.zip).</p> <p>Files ending with var_names are the README files.</p>
Annual tropical forest loss during 2001-2021 in the Congo Basin
<p>The loaded dataset in Zenodo includes the following parts:</p> <p>(1) Shp file of the Congo Basin;</p> <p>(2) GeoTIFF image of the evergreen forest cover map in the Congo Basin (file name 'Congo_EvergreenForest2000_TCC70_Height5_Clip');</p> <p>(3) GeoTIFF image of the annual forest loss map produced by us (file name 'Congo_log2001_2021_L78S2_w300_cb300_theta0p2_clean120_5_new');</p> <p>(4) GeoTIFF image of the post-forest loss recovery index map produced by us (file name 'Congo_RI_Log2001_2021_L78S2_w300_cb300_400_theta0p2_clean120_5_new.tif'), and it is noted that the industrial plantation map (file name 'JRC_TMF_plantations_2022.tif') should be used to exclude any plantations in our post-forest loss recovery index map, as industrial plantations is not regarded as forest recovery.</p>
Indicative distribution map for Ecosystem Functional Group TF1.1 Tropical flooded forests and peat forests
<p>This archive contains indicative distribution maps and profiles for <strong>TF1.1 Tropical flooded forests and peat forests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Detecting small changes in tropical forests from space... data and code for thesis chapter 4
<p>SAR and UAV-LiDAR data used in chapter 4 of my thesis <em>Detecting small changes in tropical forests from space: experiments using synthetic aperture radar. </em>This content has also been submitted for peer review in Frontiers in Remote Sensing.</p> <p>DEM_timeseries_3m contains phase height and coherence from TanDEM-X InSAR high-resolution spolight images, processed by Jose-Luis Bueso-Bello at DLR. NetCDF format, dimensions latitude, longitude, time.</p> <p>TDX_descending_intensity contains intensity from the same TanDEM-X time series, covering an area of the Madre de Dios region in Peru. These data were processed by Harry Carstairs using ESA's SNAP software.</p> <p>UAV_change_1m_mask is a raster showing the change in canopy height at the study site between June 2019 and July 2021, according to two UAV LiDAR campaigns, with 1m pixels, and with areas with low point density masked out.</p> <p>CODE.zip contains python scripts and notebooks used to collate the data, create change detection metrics, develop SAR models of canopy height, and produce the figures.</p> <p>Funded by European Research Council (ERC) grant to the Tropical Forest Degradation Experiment (FODEX).</p>
Indicative distribution map for Ecosystem Functional Group T1.4 Tropical heath forests
<p>This archive contains indicative distribution maps and profiles for <strong>T1.4 Tropical heath forests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Earthworms in tropical tree plantations and secondary forests
We compared patterns of earthworm abundance and species composition in tree plantations and secondary forests of Puerto Rico. Tree plantations included pine (Pinus caribaea Morelet) and mahogany (Swietenia macrophylla King) established in the 1930s, 1960s, and 1970s; secondary forests were naturally regenerated in areas adjacent to these plantations. We found that (1) earthworm density and fresh weight in the secondary forests were twice those in either of the tree plantations, and did not differ between the plantations, and (2) the exotic earthworm species, Pontoscolex corethrurus M ller, dominated both plantations and the secondary forests, but native earthworm species, Pontoscolex spiralis Borges & Moreno, Estherella montana Gates, and E. gatesi Borges & Moreno, occurred only in the secondary forests. Our results suggest that naturally-regenerated secondary forests are preferable to pine and mahogany plantations for maintaining a high level of earthworm density, fresh weight, and native species. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Data from: Trade-off between standing biomass and productivity in species-rich tropical forest: evidence, explanations and implications
<p>These files are the R code and plot data files used for calculating species population turnover of biomass and abundance in a tropical forest plot.</p> <p>This dataset is a processed subset of the original dataset used in our analysis of biomass turnover across tree populations as demonstrated in <a href="https://doi.org/10.1111/1365-2745.13485">the main paper</a>. Readers interested in using the Pasoh 50-ha plot data for purposes other than reviewing our analysis are advised to contact the <a href="https://www.frim.gov.my/">Forest Research Institute Malaysia (FRIM)</a> and the <a href="https://forestgeo.si.edu/">Center for Tropical Forest Science-Forest Global Earth Observatory (CTFS-Forest GEO)</a>, Smithsonian Tropical Research Institute.</p>
CamTrapAsia: a dataset of tropical forest vertebrate communities from 239 camera trapping studies
<p>Dataset containing data from 239 camera trap studies conducted in tropical Asia. A total of 278,260 independent records were compiled, from 371 distinct species, comprising 232 mammals, 132 birds, and 7 reptiles. The accumulated trapping effort was 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal and far-eastern India.</p>
Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest
<p>Dataset was used for the article "Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest".</p> <p>The related work proposes to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic).</p> <p>Abstract of the paper:</p> <p>A better knowledge of tree vegetative growth patterns and their relationship to environmental variables is crucial in understanding forest growth dynamics and how climate change may affect them. Generally less studied than reproductive structures, the phenology of tree vegetative growth mainly focuses on the analysis of growing shoots, from vegetative buds development to leaf fall. This growth process usually strongly differs between temperate and tropical regions. In temperate regions, this pattern is quite well known. Low winter temperatures impose a stop of the vegetative growth shoots and lead to the typical expression of an annual growth cycle for the vast majority of tree species. In moist tropical regions, on the other hand, the seasonality is much less marked. In addition, these regions contain a much wider variety of tree species. These two aspects lead to a tremendous diversity of phenological patterns that are still poorly known and understood. In particular, not much is known on the periodicity and timing of growth at individual trees, population, or community levels.</p> <p>The work carried out in this study aims to advance knowledge in this area, focusing more particularly on herbarium scans, as herbarium collections offer the promise of monitoring plant phenology over long time periods. However, such a study requires the ability to detect a sufficiently large number of growing shoots in herbarium collections to draw statistically relevant conclusions, which can be very costly if the work is done manually. Furthermore, herbarium collections traditionally focus on reproductive organs, and herbarium specimens showing growing shoots are pretty rare.</p> <p>We propose in this paper to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect these relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Our results show the relevance of using herbarium data for vegetative phenology research, as well as the potential of deep learning approaches for growth shoot detection.</p>
Data from: Lianas decelerate tropical forest thinning during succession
<p>The well-established pattern of forest thinning during succession predicts an<br> increase in mean tree biomass with decreasing tree density. The forest thinning<br> pattern is commonly assumed to be driven solely by tree-tree competition. The<br> presence of non-tree competitors could alter thinning trajectories, thus<br> altering the rate of forest succession and carbon uptake. We used a large-scale<br> liana removal experiment over 7 years in a 60-to-70-year-old Panamanian forest<br> to test the hypothesis that lianas reduce the rate of forest thinning during<br> succession. We found that lianas slowed forest thinning by reducing tree growth,<br> not by altering tree recruitment or mortality. Without lianas, trees grew and<br> presumably competed more, ultimately reducing tree density while increasing mean<br> tree biomass. Our findings challenge the assumption that forest thinning is<br> driven solely by tree-tree interactions; instead, they demonstrate that<br> competition from other growth forms, such as lianas, slow forest thinning and<br> ultimately delay forest succession.<br> </p>
Variation in the Composition of Understory Vegetation in a Tropical Rain Forest as a Function of Soil and Topographic Position. 1986 - 1990
Understory plants are a major contribution to the high plant species diversity of Neotropical rain forests. Shrubs, understory trees, saplings of overstory trees, and herbs occupy a habitat of generally low light levels and high humidity in which there seem to be few obvious mechanisms to support habitat partitioning. Moreover several plant families are characterized by a high number of co-occurring understory species. In 1987-1989 we sampled understory vegetation in 18 sites at the La Selva Biological Station of the Organization for Tropical Studies in Heredia Province, Costa Rica. At each site we used 20 nested quadrats to investigate the effects of soil type on replicated sites of mapped alluvial and residual volcanic soils (5 map units) and topographic positions (ridges, midslopes and flats) on composition, density and diversity of small (1m tall to 5cm dbh, 25 m2 quadrat) and large(5-10cm dbh, 100 m2 quadrat) understory plants. We also measured fine litter dry mass, extractable P, total organic matter, percent slope and percent incident light radiation in each quadrat.
Canopy opening increased leaf shredding arthropods and nutrient mineralization but not mass loss in a wet tropical forest
Canopy opening increased leaf shredding arthropods and nutrient mineralization but not mass loss in a wet tropical forest Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Meteorological and Ecosystem Flux Data for: Net ecosystem production in an old-growth tropical dry forest in Northwestern Mexico
<p>This dataset accompanies the paper: Net ecosystem production in an old-growth tropical dry forest in Northwestern México which is submitted for publication at the Journal of Geophysical Research - Biogeosciences</p> <p>With this data set, we explore the functionality as a carbon source or sink of an old-growth tropical dry forest in the carbon cycle and its functional relationship with water and light across years with different precipitation patterns in Northwestern México, using 3 continuous years of water, energy, and carbon flux measurements from an eddy covariance tower and also a meteorological arrangement.</p>
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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.