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4,276 results for “Estimation”
Spartina alterniflora above- and belowground biomass predictions and inundation intensity as estimated by the Belowground Ecosystem Resiliency Model for U.S. Georgia marshes from 2014 to 2023.
We applied the Belowground Ecosystem Resiliency Model (BERM) to estimate monthly aboveground biomass (AGB) and belowground biomass (BGB) in U.S. Georgia Spartina alterniflora marshes from 2014 to 2023 at 30 m scale. This application involved BERM version 2.0 (https://doi.org/10.5281/zenodo.13306821), which was built using data in the PLT-GCET-2308 dataset (https://dx.doi.org/10.6073/pasta/4a0b715104849d98320fcc34e7cd63a4). Data sources for BERM application included Landsat-8/9, NOAA CO-OPS Station ID: 8670870, Daymet, and USGS 3DEP 2018 DEM. Download and processing steps are described in the BERM code and in metadata methods section. Specific descriptions of data processing are available in model code: https://doi.org/10.5281/zenodo.13306821. Data provided here include model output of AGB estimates, BGB estimates, and calculated inundation intensity. See "Data reporting" method in the metadata for description of data files. For logisitical purposes here we present only select data from the model input and output. All model input data sources as listed in the abstract are publicly available. Model calibration data and code are published as well. Additional predictions not published here include foliar chlorophyll, foliar nitrogen, and leaf area index.
Pelagic, epilimnetic production estimates in Sparkling, Trout (Wisconsin), Acton (Ohio), and Castle (California) Lakes (USA) calculated using 14C and free-water O2 metabolism methods, 2007 - 2017
Concurrent daily estimates of pelagic, eplilimnetic production (mmol C m3 d) generated from 14C incubations and diel changes in high frequency dissolved oxygen data (free-water). Original data derived from the North Temperate Lakes Long Term Ecological Research program (Sparkling [2007-2013], Trout [2007-2012] Lakes), Castle Lake Research Station (Castle Lake [2014-2017]), and Center for Aquatic and Watershed Sciences (Acton Lake [2010-2014]). 14C production estimates were generated as part of each research programs core data collection. Free-water production estimates generated using high frequency sensor data provided by research programs and Phillips (2020) time-varying, Bayesian metabolism model.
Lower Altamaha River Spartna alterniflora aboveground biomass estimates from Landsat 5 TM imagery
We used gap-filled monthly observations of Spartina alterniflora aboveground biomass derived from Landsat 5 and Landsat 8 satellite imagery from 1984-2018 to analyze temporal patterns in biomass in comparison to air temperature, precipitation, river discharge, nutrient input, sea level, and drought index for a southeastern US salt marsh. Satellite imagery data were downloaded from the USGS Earth Explorer data portal and initially processed with L3Harris Geospatial ENVI software. This database contains the estimates of above-ground Spartina alterniflora biomass within the freshwater tidal reach of the Altamaha River estuary on the Southeastern Atlantic coast of Georiga, USA. Work is ongoing to expand these data to cover the entire Georgia coast.
Plant and litter cover estimates derived from overhead microplot photos in the Cross-Scale Interactions Study (CSIS) at Jornada Basin LTER, 2013-ongoing
This dataset contains plant and litter cover estimates derived from overhead photos collected from microplots in a long-term experiment (2013-present) of cross-scale interactions (CSIs) at the Jornada Basin LTER site in southern New Mexico, U.S.A. Experimental treatments were initiated in 2013 at 15 experimental blocks, each with 4 treatment plots: plant-scale herbicide of mesquite shrubs, patch-scale connectivity modifiers (ConMods), herbicide + ConMods, control without manipulations. Repeat, overhead (downward-looking) photographs of ten "microplots" in each plot were taken for estimation of litter, soil, and vegetation cover in the experimental treatment and control plots over time. Photographs were rotated and then cropped to provide standardized areas, and then were analyzed with USDA SamplePoint software to determine coverage by ~27 plant, litter or other cover classes on a 100 point grid. Raw and corrected cover estimates are provided. This study is ongoing and new data will be added annually. Cover estimates are derived from photos in EDI dataset knb-lter-jrn.210413004.
Litter and soil accumulation estimates derived from lateral microplot photos in the Cross-Scale Interactions Study (CSIS) at Jornada Basin LTER, 2013-2017
This dataset contains litter and soil vertical accumulation estimates derived from lateral photos of microplots in a long-term experiment (2013-2017) of cross-scale interactions (CSIs) at the Jornada Basin LTER site in southern New Mexico, U.S.A. Experimental treatments were initiated in 2013 at 15 experimental blocks, each with 4 treatment plots: plant-scale herbicide of mesquite shrubs, patch-scale connectivity modifiers (ConMods), herbicide + ConMods, control without manipulations. Repeat, lateral (side-looking) photographs of ten "microplots" in each ConMods and herbicide+ConMods plot were taken for estimation of litter, soil, and vegetation cover in the experimental treatment and control plots over time. Photographs were analyzed with SigmaScan software to determine vertical accumulation of litter and soil withing the microplots. This study is complete and ended in 2017. These vertical accumulation estimates are derived from photos in EDI dataset knb-lter-jrn.210413006.
WSC - Gridded sample points at Wibu field site including yield, soil texture, water table depth, and estimated soil water retention parameters
A variety of data from gridded sampling points at the Wibu field site. The gridded sampling scheme is described in the Point Locations dataset. This dataset includes 2012 and 2013 absolute and normalized yield, soil textural characteristics (organic content, porosity, bulk density, particle size metrics, % sand/silt/clay), a variety of water table depth metrics (mean, percentiles, sum exceedance values, moving averages), and soil water retention parameters estimated using the Rosetta pedotransfer function. It was collected as part of a study of the impacts of water table depth, soil texture, and growing season weather conditions on corn production at the Wibu field site, described in Zipper et al. (in review). The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site.
North Temperate Lakes LTER Estimated winter inputs of stream water and groundwater to primary study lakes 1982 - 2014
This data set integrates and summarizes daily surface and groundwater inputs to 5 primary study lakes, using model estimates from a data-driven USGS hydrologic model (Hunt et al. 2013; Hunt and Walker 2017), and ice phenology data (number of days since ice-on). The lakes are Allequash, Big Muskellunge, Crystal, Sparkling, and Trout. Powers et al. (2017) used these data to estimate upper and lower bounds for exogenous chemical inputs to the lakes during winter. For a given lake and winter year, cumulative surface water and groundwater inputs were calculated across the ice cover period. For each lake, this data set reports the mean, maximum, and minimum winter water inputs observed across years, in units of water volume, % of average lake volume, and volume per winter day. Sampling Frequency: 1 per lake, with multiple summary values reported (i.e., mean, min, max). Number of sites: 5. Hunt, R.J. et al., 2013. Simulation of Climate - Change effects on streamflow, Lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin. USGS Scientific Investigations Report., pp.2013-5159. Available at: https://www.researchgate.net/publication/258363719_Simulation_of_Climate... Hunt, R.J., and Walker, J.F., 2017, GSFLOW groundwater-surface water model 2016 update for the Trout Lake Watershed, Wisconsin: U.S. Geological Survey data release, https://dx.doi.org/10.5066/F7M32SZ2. Powers SM, Labou SG, Baulch HM, Hunt RJ, Lottig NR, Hampton SE, Stanley EH. In press (expected 2017). Ice duration drives winter nitrate accumulation in north temperate lakes. Limnology and Oceanography Letters.
Cuneiform Inscriptions Geographical Site - Assemblage Estimates (CIGS-AE)
<p>The <em>Cuneiform Inscriptions Geographical Site - Assemblage Estimates </em>(CIGS-AE) provides basic overall estimates of and bibliographical references for the approximate number of cuneiform inscriptions derived from individual archaeological locations. In use across the wider Middle East from c. 3,400 BCE until 100 CE, cuneiform is one of the earliest and most extensively documented ancient scripts in world history. The CIGS-AE is a component of the <a href="https://doi.org/10.5281/zenodo.4960710">Cuneiform Inscriptions Geographial Site (CIGS)</a> index, a digital geospatial register of archaeological sites with finds of cuneiform inscriptions across Europe, Asia, and Africa.</p> <p>CIGS-AE provides a first comprehensive quantitative overview of the approximate number of cuneiform inscriptions unearthed from known archaeological locations. It does not provide an overview of the entire corpus of cuneiform inscriptions known, as the index disregards all inscriptions with no verifiable archaeological origin, estimated to be between fifteen and twenty per cent of the overall corpus according to the catalogue of the <a href="https://cdli.mpiwg-berlin.mpg.de/heatmap">Cuneiform Digital Library Initiative</a>. The present resource then offers a lower threshold for the size of the full cuneiform corpus and a fairly reliable overview of its general distribution. The accompanying bibliography offers a basic set of references for all known archaeological sites with finds of cuneiform inscriptions. This information is intended as a starting point for further study, and should not be considered an exhaustive nor authoritative bibliography.</p> <p>This resource has been prepared by researchers of the <a href="http://lingfil.uu.se/">Department of Linguistics and Philology</a> of <a href="http://uu.se/">Uppsala University</a>. The index is intended as a tool for students and researchers in cuneiform studies and related areas and as an aid to cultural heritage managers and educators in communicating and safeguarding this unique body of world written heritage. The index remains under development and is regularly updated. The authors will very much appreciate notices of any omissions, errors, or inaccuracies. For any inquiries, please contact <a href="https://www.katalog.uu.se/profile/?id=N18-1120">Rune Rattenborg</a> (<a href="mailto:rune.rattenborg@lingfil.uu.se?subject=%5BCIGS-AE%5D%3A">rune.rattenborg@lingfil.uu.se</a>).</p> <p>The version 1.1 index contains 603 entries with a total five fields, including one primary ID, two integer fields for assemblage size and grouping, and two string fields for bibliographical references and notes. Record identifiers are matched with primary IDs in <a href="https://doi.org/10.5281/zenodo.4960710">Cuneiform Inscriptions Geographial Site (CIGS)</a> index to allow for geospatial visualisation of quantitative data. Reference short titles are matched with short titles contained in the accompanying .bibtex.</p>
High-frequency dissolved oxygen, water temperature, wind speed, and radiation data; stream and in-lake nutrient concentration data; and daily metabolism and nutrient loading estimates for 16 lakes in North America and Northern Europe.
In lakes, ecosystem structure and processes are influenced by gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP). The rates of these metabolic processes are often controlled by resource availability, which often reflects catchment loads. Although the relationship between catchment loads and in-lake nutrient concentrations may be well defined in specific lakes, we explored how watershed vs. in-lake predictors of metabolism compare across lake types. To do this, we combined stream loads of carbon (C), nitrogen (N), and phosphorus (P) with high frequency in situ monitoring of lake metabolism and in-lake C, N, and P concentrations from 16 lakes spanning a range of latitudes (39 to 64 degrees N), inflowing stream (0 - 6 streams), and trophic status (oligotrophic to eutrophic). The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP, R, and NEP derived from those data. In addition, the data package includes in-lake and stream concentrations of dissolved organic carbon, total nitrogen, and total phosphorus and stream discharge data. The package also includes estimates of daily carbon, nitrogen and phosphorus loading to each lake derived from the stream concentrations and discharge.
Estimated Inundation Periods in the Yolo Bypass, California, 1998 – 2024
Largely supported by the Interagency Ecological Program (IEP), California Department of Water Resources (DWR) has operated a fish monitoring program in the Yolo Bypass, a seasonal floodplain and tidal slough, since 1998. The objectives of the Yolo Bypass Fish Monitoring Program (YBFMP) are to: 1. Collect baseline data on water quality, chlorophyll, lower trophic level biota, and fish in the Yolo Bypass to monitor spatial and temporal changes in trends and abundance. 2. Analyze and communicate Yolo Bypass data with interested parties and the scientific and management communities to address pertinent management-related questions. 3. Provide technical expertise on Yolo Bypass aquatic ecology and monitoring and sampling methods. The YBFMP operates a rotary screw trap and fyke trap and conducts biweekly beach seine and lower trophic surveys in addition to maintaining water quality instrumentation in the bypass. The YBFMP serves to fill information gaps regarding environmental conditions in the bypass that trigger migrations and enhanced survival and growth of native fishes, as well as provide data for IEP synthesis efforts. YBFMP staff also conduct analyses of YBFMP monitoring data to address pertinent management related questions as identified by IEP. The Yolo Bypass has been identified as a high restoration priority by the National Marine Fisheries Service and US Fish and Wildlife Service Biological Opinions for Delta Smelt, Winter and Spring-run Chinook salmon and by California EcoRestore. The YBFMP informs the restoration actions that are mandated or recommended in these plans and provides critical baseline data on the ecology of the bypass and how it interacts with the broader San Francisco Estuary. YBFMP’s data is often accompanied by information on whether the Yolo Bypass is inundated, as water quality, and species composition and abundance can be greatly altered during inundation. This dataset was created to consistently estimate inundation over time. Estimating
Model simulated hydrological estimates for the North Slope drainage basin, Alaska, 1980-2010
Estimates of runoff, river discharge, snow water equivalent (SWE), subsurface runoff, and soil temperatures are drawn from the Permafrost Water Balance Model (PWBM). The simulation and derived data span the period 1980-2010. The model was forced with daily gridded meteorological data obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis (version 5.2.0). The estimates of total runoff (daily), soil temperature (daily), subsurface runoff (monthly), and SWE (monthly) are expressed on a spatial grid (N=312; 25x25 km EASE-Grid version 1, Northern Hemisphere) over the North Slope drainage basin, with the coastline extending from Utqiagvik (formerly Barrow) to just west of the Mackenzie River delta. River discharge, calculated as a volume flux of runoff at each grid cell, was routed through the river network defined on a simulated topological network (STN). Archived files contain discharge flux through the grid cell representing the outlet of each of forty-two basins defined across the region on the 25 km resolution EASE-Grid. Details of the PWBM, forcing variables, model validation and results of analysis are described in Rawlins et al. (2019).
Estimating Forest Productivity Using Carbon Isotopes in Tree Rings at Harvard Forest 1992-2010
We investigated relationships between tree-ring δ13C and growth, and flux tower estimates of gross primary productivity (GPP) at Harvard Forest from 1992 to 2010. Seasonal variations of derived photosynthetic isotope discrimination (Δ13C) and leaf intercellular CO2 concentration (ci) showed significant increasing trends for the dominant deciduous and coniferous species. Δ13C was positively correlated to growing-season GPP and is primarily controlled by precipitation and soil moisture indicating that site conditions maintained high stomatal conductance under increasing atmospheric CO2 levels. Increasing Δ13C over the 1992-2010 period is attributed to increasing annual and summer water availability identified at Harvard Forest and across the region. Higher Δ13C is coincident with an enhancement in growth and ecosystem-level net carbon uptake. This work suggests that tree-ring δ13C could serve as a measure of forest GPP and be used to improve the calibration and predictive skill of ecosystem and carbon cycle models.
EXPOS Model for Estimating Topographic Exposure to Wind
EXPOS is a simple model of topographic exposure to wind that utilizes digital elevation data to predict which points on a landscape are exposed to or protected from a given wind direction. The model was developed to approximate the effects of topography on hurricane wind flow at a landscape scale (~ 10 km). The model requires an accurate digital elevation map and a specified wind direction. Each point on the elevation map is then classified as protected or exposed, depending on whether or not it falls within the wind shadow cast by points upwind. The wind shadow is estimated by assuming that the wind bends downward no more than a fixed inflection angle from the horizontal as it passes over a height of land. The effects of topographic features beyond the margins of the input elevation map are of course not predicted by the model. For a given landscape and wind direction, predicted protected areas decrease in size as the inflection angle increases. Application of the model in studies of two recent hurricanes suggests that the probability of wind damage in protected areas also decreases as the inflection angle increases. An inflection angle of about 5 to 10 degrees was found to give good results. For more information on the EXPOS model, please see the published paper (Boose, E. R., D. R. Foster, and M. Fluet. 1994. Hurricane impacts to tropical and temperate forest landscapes. Ecological Monographs 64: 369-400). Additional information is contained in the documentation that accompanies the program. For an updated version of the EXPOS model in R and Python, please see HF447.
HURRECON Model for Estimating Hurricane Wind Speed, Direction and Damage
HURRECON is a simple meteorological model that estimates hurricane surface wind speed and direction based on the track, size, and intensity of a hurricane and the surface type (land or water). The model also estimates Fujita-scale wind damage as a function of peak 1/4 mile wind speed and wind gust factor. Estimates can be generated for a single site or a rectangular region. The model is based on published empirical studies of many hurricanes. HURRECON can be used to study the impacts of individual hurricanes or to reconstruct the hurricane disturbance regime for a particular region. For more information on the most recent version of the model please see the published paper (Boose, E. R., K. E. Chamberlin and D. R. Foster. 2001. Landscape and regional impacts of hurricanes in New England. Ecological Monographs 71: 27-48). Additional information is contained in the documentation that accompanies the program. For an updated version of the HURRECON model in R and Python, please see HF446.
Seasonal aboveground plant biomass estimates at 15 net primary production (NPP) study sites at Jornada Basin LTER from 1989-ongoing
This data package contains aboveground vegetation cover, volume, and calculated biomass values at the 15 Net Primary Production (NPP) study sites on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Sites were selected to represent the 5 major ecosystem types in the Chihuahuan Desert (upland grasslands, playa grasslands, mesquite-dominated shrublands, creosotebush-dominated shrublands, tarbush-dominated shrublands). For each ecosystem type, three sites were selected to represent the range in variability in production and plant diversity; thus the locations are not replicates. All sites are excluded from domestic grazing. Eleven sites are in non-grazed pastures, and at the other four sites 1 hectare areas around the observational plots were fenced in 1988. At all sites a grid of 49 (48 at one playa location) 1m x 1m replicate quadrats was laid out when sampling began in 1989. For each quadrat, aboveground biomass has been calculated from two data sources: 1) non-destructive horizontal cover and vertical height measurements of individual plants, or plant parts, within each quadrat, and 2) linear regression coefficients for each plant species derived from off-quadrat cover, height, and harvested biomass measurements. Non-destructive measurements (1) are taken during winter, spring, and fall measurement campaigns, then aggregated by species for each quadrat, and resulting dimensions are used to calculate species biomass (grams) by quadrat and season using using the species-specific regression coefficients derived from dataset 2. This is the most detailed biomass dataset available and can be used to derive values of net primary production between seasons or annually. Each dataset record contains calculated biomass (and related variables) by species, quadrat, season, and site. Data collection is ongoing with new observations in spring, fall, and winter of each year, but this data package may be updated less frequently. Attenti
Annual mean estimates of aboveground net primary production (NPP) at 15 sites at Jornada Basin LTER, 1989-ongoing
This package contains values of mean annual aboveground net primary production (NPP, in grams per square meter per year) at 15 NPP study sites on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Sites were selected to represent the 5 major ecosystem types in the Chihuahuan Desert (upland grasslands, playa grasslands, mesquite-dominated shrublands, creosotebush-dominated shrublands, tarbush-dominated shrublands). For each ecosystem type, three sites were selected to represent the range in variability in production and plant diversity; thus the locations are not replicates. All sites are excluded from domestic grazing. Eleven sites are in non-grazed pastures, and at the other four sites 1 hectare areas around the observational plots were fenced in 1988. At all sites a grid of 49 (48 at one playa location) 1m x 1m replicate quadrats was laid out when sampling began in 1989. In fall, winter, and spring periods aboveground biomass was calculated for each species and quadrat at each NPP site. These calculations rely on two data sources: 1) non-destructive horizontal cover and vertical height measurements of individual plants, or plant parts, within each quadrat, and 2) linear regression coefficients for each plant species derived from off-quadrat cover, height, and harvested biomass measurements. NPP is then calculated as the positive biomass increment between seasons. The annual totals in this dataset are derived by summing mean site NPP values for winter (October - February), spring (February - May), and fall (May - October) increments for a single calendar year. Data collection is ongoing with new annual NPP values calculated after the conclusion of each growing season. Attention: 1) Calculated values in this data package have changed over time as the methodology for estimating biomass has changed. If you are updating or adding to an earlier analysis of these data we recommend consulting with the dataset authors or a Jorna
North Temperate Lakes LTER Wisconsin Estimated Secchi Depths
This data set contains the estimated Secchi depth (water clarity) measurements for 8645 Wisconsin lakes, derived from Landsat-5 and -7 satellite imagery acquired during the 1999-2001 time period. For details of the process used to create these data, see: Chipman, J. W., T. M. Lillesand, J. E. Schmaltz, J. E. Leale, and M. J. Nordheim. 2004. “Mapping Lake Water Clarity with Landsat Images in Wisconsin, USA.” Invited paper, Canadian Journal of Remote Sensing, Special Issue on Remote Sensing and Resource Management in Nearshore and Inland Waters, 30(1):1-7. Polygons for each lake were taken from the WDNR 1:24,000-scale Hydrography GIS data set (version 2). Several existing fields were deleted, and new ones were added.
Production, biomass, and yield estimates for walleye populations in the Ceded Territory of Wisconsin from 1990-2017
Recreational fisheries are valued at $190B globally and constitute the predominant use of wild fish stocks in developed countries, with inland systems contributing the dominant fraction of recreational fisheries. Although inland recreational fisheries are thought to be highly resilient and self-regulating, the rapid pace of environmental change is increasing the vulnerability of these fisheries to overharvest and collapse. We evaluate an approach for detecting hidden overharvest of inland recreational fisheries based on empirical comparisons of harvest and biomass production. Using an extensive 28-year dataset of the walleye fisheries in Northern Wisconsin, USA, we compare empirical biomass harvest (Y) and calculated production (P) and biomass (B) for 390 lake-year combinations. Overharvest occurs when harvest exceeds production in that year. Biomass and biomass turnover (P/B) both declined by about 30% and about 20% over time while biomass harvest did not change, causing overharvest to increase. Our analysis revealed 40% of populations were production-overharvested, a rate about 10x higher than current estimates based on numerical harvest used by fisheries managers. Our study highlights the need for novel approaches to evaluate and conserve inland fisheries in the face of global change.
Wisconsin creel dataset as well as predictor variables for lakes from 1990 to 2017 to estimate statewide recreational fisheries harvest
Recreational fisheries have high economic worth, valued at $190B globally. An important, but underappreciated, secondary value of recreational catch is its role as a source of food. This contribution is poorly understood due to difficulty in estimating recreational harvest at spatial scales beyond an individual system, as traditionally estimated from angler creel surveys. Here, we address this gap using a 28-year creel survey of ~300 Wisconsin inland lakes. We develop a statistical model of recreational harvest for individual lakes and then scale-up to unsurveyed lakes (3769 lakes; 73% of statewide lake surface area) to generate a statewide estimate of recreational lake harvest of ~4200 t and an estimated annual angler consumption rate of ~3 kg, nearly double estimated United States per capita freshwater fish consumption. Recreational fishing harvest makes significant contributions to human diets, is critical for discussions on food security, and the multiple ecosystem services of freshwater systems.
Resilience estimates of Amazon and Congo rainforests based on mean annual precipitation and root zone storage capacity
<p>Resilience refers to the capacity of the ecosystem to absorb perturbations and remain in its native stable state. Here, we quantified forest resilience of South American and African ecosystems using mean annual precipitation and root zone storage capacity (2000-2019). We adopted Hirota et al. (2011) methodology for calculating resilience using logistic regression. This logistic regression predicts the probability of forest (tree cover > 50%) as a function of the independent variable. The predicted resilience estimates range between 0 to 1, where 1 represents the highest probability of finding forest – interpreted as highly resilient forest ecosystems.</p> <p>For more information, check: <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115">https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115</a></p>
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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.