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491 results for “population modelling”
Modeling Viability of Avian Populations in the Southern Appalachians: Potential impacts of Climate Change from 2002 to 2004
There is a general consensus that the global climate has slowly warmed (0.6 degrees C) over the past 100 years and that this trend will continue at an accelerated rate over the next 100 years (1 degree to 6 degrees C) (Kattenburg et al. 1996). Aside from the mean annual increase in temperature, the frequency of weather extremes, such as heat waves, drought, and tropical storms are projected to increase across North America over the next century (Easterling et al. 2000). Past changes in temperature and precipitation have been accompanied by changes in insect and vertebrate distributions from both tropical and temperate environments (Parmesan 1996, Pounds et. Al 1999). We have developed bird-habitat models that allow us to predict the occurrences of species in specific forest types within and across national forests within the Blue Ridge physiographic province with a high degree of accuracy (Linder et al. submitted). These models categorize habitat as unsuitable, marginal or high quality as determined by the rate of occupancy over five years of point count data. We will validate our occurrence models with reproductive data. We hypothesize that reproductive success will correspond to predicted habitat quality. While stochastic events may obscure patterns in the short-term, long-term reproductive trends should reflect site quality.
Data from: Estimating fish population abundance by integrating quantitative data on environmental DNA and hydrodynamic modeling
<p>Molecular analysis of DNA left in the environment, known as environmental DNA (eDNA), has proven to be a powerful and cost-effective approach to infer occurrence of species. Nonetheless, relating measurements of eDNA concentration to population abundance remains difficult because detailed knowledge on the processes that govern spatial and temporal distribution of eDNA should be integrated to reconstruct the underlying distribution and abundance of a target species. In this study, we propose a general framework of abundance estimation for aquatic systems on the basis of spatially replicated measurements of eDNA. The proposed method explicitly accounts for production, transport, and degradation of eDNA by utilizing numerical hydrodynamic models that can simulate the distribution of eDNA concentrations within an aquatic area. It turns out that, under certain assumptions, population abundance can be estimated via a Bayesian inference of a generalized linear model. Application to a Japanese jack mackerel (<em>Trachurus japonicus</em>) population in Maizuru Bay revealed that the proposed method gives an estimate of population abundance comparable to that of a quantitative echo sounder method. Furthermore, the method successfully identified a source of exogenous input of eDNA (a fish market), which may render a quantitative application of eDNA difficult to interpret unless its effect is taken into account. These findings indicate the ability of eDNA to reliably reflect population abundance of aquatic macroorganisms; when the "ecology of eDNA" is adequately accounted for, population abundance can be quantified on the basis of measurements of eDNA concentration.</p>
Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
<p>Multi-locus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multi-locus genetic processes in arbitrarily complex scenarios. However, the use of forward-in-time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, <span>MetaPopGen</span> 2.0, to model multi-locus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed <span>MetaPopGen</span> 2.0 in the R environment to facilitate its use by non-modeler ecologists and evolutionary biologists. We illustrate the capabilities of <span>MetaPopGen</span> 2.0 for studying adaptation to water salinity in the striped red mullet <i>Mullus surmuletus</i>.</p>
Data for: Coevolution fails to maintain genetic variation in a host-parasite model with constant finite population size
<p>Coevolutionary negative frequency-dependent selection has been hypothesized to maintain genetic variation in host and parasites. <br> Despite the extensive literature pertaining to host-parasite coevolution, the dynamics of genetic variation has not been examined in a matching-alleles model (MAM) with a finite population size relative to the expectation under neutral genetic drift alone. The dynamics of the MA coevolution in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally. By comparing host heterozygosity to the expectation in a single-species model of neutral genetic drift we find that while this is also largely true in finite populations two additional phenomena arise. First, reciprocal natural selection acting on stochastic perturbations in host and pathogen allele frequencies results in a slight increase or decrease in genetic variation depending on the parameter conditions. Second, following the fixation of an allele in the parasite, selection in the MAM becomes directional, which then rapidly erodes genetic variation in the host. Hence, rather than maintain it, we find that, on average, matching-alleles coevolution depletes genetic variation.</p>
Data from: Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements
Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space, and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi-state mark recapture methods using a hierarchical N-mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state-space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N-mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.
Data from: Evaluating population viability and efficacy of conservation management using integrated population models
Predicting population responses to environmental conditions or management scenarios is a fundamental challenge for conservation. Proper consideration of demographic, environmental and parameter uncertainties is essential for projecting population trends and optimal conservation strategies. We developed a coupled integrated population model-Bayesian population viability analysis to assess the (1) impact of demographic rates (survival, fecundity, immigration) on past population dynamics; (2) population viability 10 years into the future; and (3) efficacy of possible management strategies for the federally endangered Great Lakes piping plover Charadrius melodus population. Our model synthesizes long-term population survey, nest monitoring and mark–resight data, while accounting for multiple sources of uncertainty. We incorporated latent abundance of eastern North American merlins Falco columbarius, a primary predator of adult plovers, as a covariate on adult survival via a parallel state-space model, accounting for the influence of an imperfectly observed process (i.e. predation pressure) on population viability. Mean plover abundance increased from 18 pairs in 1993 to 75 pairs in 2016, but annual population growth (math formula) was projected to be 0.95 (95% CI 0.72–1.12), suggesting a potential decline to 67 pairs within 10 years. Without accounting for an expanding merlin population, we would have concluded that the plover population was projected to increase (math formula = 1.02; 95% CI 0.94–1.09) to 91 pairs by 2026. We compared four conservation scenarios: (1) no proposed management; (2) increased control of chick predators (e.g. Corvidae, Laridae, mammals); (3) increased merlin control; and (4) simultaneous chick predator and merlin control. Compared to the null scenario, chick predator control reduced quasi-extinction probability from 11.9% to 8.7%, merlin control more than halved (3.5%) the probability and simultaneous control reduced quasi-extinction probability to 2.6%. Synthesis and applications. Piping plover recovery actions should consider systematic predator control, rather than current ad hoc protocols, especially given the predicted increase in regional merlin abundance. This approach of combining integrated population models with Bayesian population viability analysis to identify limiting components of the population cycle and evaluate alternative management strategies for conservation decision-making shows great utility for aiding recovery of threatened populations.
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
A proactive approach to conservation must be predictive, anticipating how habitats will change and which species are likely to decline or prosper. We use composite species distribution modeling to identify suitable habitats for 18 members of the North American Atlantic Coastal Plain Flora (ACPF) since the Last Glacial Maximum and project these into the future. We then use Scirpus longii (Cyperaceae), a globally imperiled ACPF sedge with many of the characteristics of extinction vulnerability, as a case study. We integrate phylogeographic and population genetic analyses and species distribution modeling to develop a broad view of its current condition and prognosis for conservation. We use genotyping-by-sequencing to characterize the genomes of 142 S. longii individuals from twenty populations distributed throughout its range (New Jersey to Nova Scotia). We measure the distribution of genetic diversity in the species and reconstruct its phylogeographic history using SNAPP and RASE. Extant populations of S. longii originated from a single refugium south of the Laurentide ice sheet around 25 thousand years ago. The genetic diversity of S. longii is exceedingly low, populations exhibit little genetic structure, and the species is slightly inbred. Projected climate scenarios indicate that nearly half of extant populations of S. longii will be exposed to unsuitable climate by 2070. Similar changes in suitable habitat will occur for many other northern ACPF species – centers of diversity will shift northward and Nova Scotia may become the last refuges for those species not extinguished.
Data from: The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defense tradeoffs
Quantitatively linking individual variation in functional traits to demography is a necessary step to advance our understanding of trait-based ecological processes. We constructed a population model for Asclepias syriaca to identify how functional traits affect vital rates and population growth and whether tradeoffs in chemical defense and demography alter population growth. Plants with higher foliar cardenolides had lower fiber, cellulose, and lignin levels, as well as decreased sexual and clonal reproduction. Average cardenolide concentrations had the strongest effect on population growth. In both the sexual and clonal pathway, the tradeoff between reproduction and defense affected population growth. We found that both increasing the mean of the distribution of individual plant values for cardenolides and herbivory decreased population growth. However, increasing the variance in both defense and herbivory increased population growth. Functional traits can impact population growth and quantifying individual-level variation in traits should be included in assessments of population-level processes.
Data from: Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales
<p>Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual-level data are available for some species. Integrated population modelling (IPM) offers a mechanism for leveraging these datasets into a single estimation framework. IPMs that incorporate both population- and individual-level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population-level visual survey data, individual-level capture-recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; <i>Delphinapterus leucas</i>) as a case study. Our state-space IPM included a population process model and three observational submodels: 1) a group detection model to describe group size estimates from aerial survey data; 2) a capture-recapture model to describe individual photographic capture-recapture data; and 3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three datasets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect datasets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.</p>
Combining bioenergetics and movement models to improve understanding of the population consequences of disturbance
<p>We developed dynamic bioenergetics models to investigate how behavioural responses to anthropogenic disturbance events might affect the population dynamics of three marine mammal species (harbour porpoise, grey seal and harbour seal) with contrasting life-history traits (capital vs income breeders) and movement behaviour (resident vs nomadic). We used these models to analyse how individual vital rates were affected by differences in the probability of disturbance and the duration of any behavioural response, while taking account of uncertainty in the model parameters and heterogeneity in behaviour. The outputs of individual movement models and telemetry data were then used to determine how the probability of exposure might vary among species, individuals, and geographical locations. We then demonstrate how these estimated probabilities of exposure can be translated into probabilities of disturbance. For illustrative purposes, we modelled the potential effects of a temporary decrease in energy assimilation associated with a series of disturbance events that might realistically occur during the construction of an offshore windfarm. Offspring starvation mortality was the vital rate that was most affected by these disturbance events. Monitoring of rates should be considered as standard practice so that populations' responses can be detected as early as possible. Predicted effects on individual vital rates depended on the species' movement behaviour and the likely density of animals where the modelled construction activity was assumed to take place. The magnitude of these effects also depended critically on the assumed duration of the reduction in energy assimilation. No direct estimates of this variable are currently available, but we suggest some ways in which it could be estimated. The described approach could be extended to other species and activities, given sufficient information to parameterise the component models. However, we emphasise the need to account for among-individual heterogeneities and uncertainties in the values of the many model parameters.</p>
Dataset of paper "Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations"
<p>Dataset of paper "Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations"</p>
Data from: Abundance models of endemic birds of the Sierra Nevada de Santa Marta, northern South America, suggest small population sizes and dependence on montane elevations
<p>Abundance measures are almost non-existent for several bird species threatened with extinction, particularly range-restricted Neotropical taxa, for which estimating population sizes can be challenging. Here we use data collected over nine years to explore the abundance of 11 endemic birds from the Sierra Nevada de Santa Marta (SNSM), one of Earth's most irreplaceable ecosystems. We established 99 transects in the "Cuchilla de San Lorenzo" Important Bird Area within native forest, early successional vegetation, and areas of transformed vegetation by human activities. A total of 763 bird counts were carried out covering the entire elevation range in the study area (~175–2650 m). We applied hierarchical distance-sampling models to assess elevation- and habitat-related variation in local abundance and obtain values of population density and total and effective population size. Most species were more abundant in the montane elevational range (1800–2650 m). Habitat-related differences in abundance were only detected for five species, which were more numerous in either early succession, secondary forest, or transformed areas. Inferences of effective population size indicated that at least four endemics likely maintain populations no larger than 15,000–20,000 mature individuals. Estimates of species' area of occupancy and effective population size were lower than most values previously described, a possible consequence of increasing anthropogenic threats. At least four of the endemics exceeded criteria for threatened species listing and a thorough evaluation of their extinction risk should be conducted. Population strongholds for most of the study species were located on the northern and western slopes of the SNSM between 1500–2700 m. We highlight the urgent need for facilitating effective protection of native vegetation in premontane and montane ecosystems to safeguard critical habitats for the SNSM's endemic avifauna. Follow-up studies collecting abundance data across the SNSM are needed to obtain precise range-wide density estimations for all species.</p>
Data from: using camera traps and N-mixture models to estimate population abundance: model selection really matters
<p>Estimating the abundance or density of wildlife populations is a critical part of species conservation and management, but estimates can vary greatly in precision and accuracy according to the data collection and statistical methods, sampling and ecological variation, and sample size. N-mixture models are a common method which has been applied to a wide range of taxa for estimating population abundance from non-invasive data representing the distribution of the species. We used population estimates from an aerial survey of moose and videos from camera traps to assess the sensitivity of N-mixture models to ecological conditions, the spatial scale at which they were measured, the criteria used to define independent detections, and model choice based on the common statistical criterion of parsimony. The most parsimonious N-mixture models were considerably biased, producing implausibly large and considerably imprecise estimates of the abundance of moose. Most of the other models produced estimates of abundance that were ecologically realistic and relatively accurate. The accuracy of population estimates produced by N-mixture models were not overly sensitive to the formulation of models, the scale at which ecological conditions were measured, or the criteria used to define independent detection and by extension sample size. Our results suggest that parsimony was a poor measure of the predictive accuracy of the population estimates produced with the N-mixture model. Collecting and processing data from the aerial survey was less expensive and took less time, but data from camera traps can provide valuable information on behavior of the target species as well as insights into multiple species in the community.</p>
Counterintuitive scaling between population abundance and local density: implications for modelling transmission of infectious diseases in bat populations
<p>1. Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density.</p> <p>2. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogenous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated.</p> <p>3. We collected a 13-month dataset of tree-roosting <i>Pteropus </i>spp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree-level measures of abundance and density – the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost-level, subplot-level, tree-level) are predictive of these local density dynamics.</p> <p>4. Roost-level features were not representative of tree-level abundance (bats per tree) or tree-level density (bats per m<sup>2</sup> or m<sup>3</sup>), with roost-level models explaining minimal variation in tree-level measures. Total roost abundance itself was either not a significant predictor (tree-level 3-D density) or only weakly predictive (tree-level abundance).</p> <p>5. This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree.</p> <p>6. Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.</p>
Divergence time estimation using ddRAD data and an isolation-with-migration model applied to water vole populations of Arvicola
<p>Molecular dating methods of population splits are crucial in evolutionary biology, but they present important difficulties due to the complexity of the genealogical relationships of genes and past migrations between populations. Using the double digest restriction-site associated DNA (ddRAD) technique and an isolation-with-migration (IM) model, we studied the evolutionary history of water vole populations of the genus <em>Arvicola</em>, a group of complex evolution with fossorial and semi-aquatic ecotypes. To do this, we first estimated mutation rates of ddRAD loci using a phylogenetic approach. An IM model was then used to estimate split times and other relevant demographic parameters. A set of 300 ddRAD loci that included 85 calibrated loci resulted in good mixing and model convergence. The results showed that the two populations of <em>A. scherman</em> present in the Iberian Peninsula split 34 thousand years ago, during the last glaciation. In addition, the much greater divergence from its sister species, <em>A. amphibius</em>, may help to clarify the controversial taxonomy of the genus. We conclude that this approach, based on ddRAD data and an IM model, is highly useful for analyzing the origin of populations and species.</p>
Data from: Modeling the impact of birth control policies on China's population and age: effects of delayed births and minimum birth age constraints
<p>We consider age-structured models with an imposed refractory period between births. These models can be used to formulate alternative population control strategies to China's one-child policy. By allowing any number of births, but with an imposed delay between births, we show how the total population can be decreased and how a relatively older age distribution can be generated. This delay represents a more "continuous" form of population management for which the strict one-child policy is a limiting case. Such a policy approach could be more easily accepted by society. Our analyses provide an initial framework for studying demographics and how social constraints influence population structure.</p> <p>This dataset includes the raw population data for 1981 China and 2000 Japan, and some Matlab code files used to process such raw data and produce predictions.</p>
Population Models of Rotating Field Stars in Kepler
<p>Model populations are constructed using TRILEGAL galaxy models coupled to YREC stellar evolutionary models and a magnetic braking law, and are described in van Saders, Pinsonneault, & Barbieri, "Forward Modeling of the Kepler Stellar Rotation Period Distribution: Interpreting Periods from Mixed and Biased Stellar Populations," 2019, ApJ, 872, 128 and updated in Hall et al. 2021 (Nature Astronomy, 5, 707) to incorporate the Berger et al. 2020 (AJ, 159, 280) Kepler Stellar Properties Catalog. </p> <p>Two model populations are provided: one in which rotation is modeled with a "standard" magnetic braking law of the form in van Saders et al. 2013, and a second in which stars are subject to weakened magnetic braking past a critical Rossby number, Rocrit. </p> <p>Models can be unpacked with the hdf with pandas functionality, using key='sample'. The keys should be self-explanatory with the possible exception of "evo", which is the evolutionary state. Choose evo = 1 to select only the main sequence.</p> <p>If you use these models in your work, please cite van Saders et al. 2019, with an additional citation to Hall et al. 2021 appreciated. </p> <p> </p>
Estimated population exposed to floods with a global flood model (CaMa-Flood v4.00)
<p>This is a repository for data and codes to analyze the population exposed to floods at grid level (0.25deg) and country level. The flood hazard map is modeled from the global hydrodynamic model - Catchment-based Macro-scale Floodplain (CaMa-Flood) model. </p>
Data from: When can model-based estimates replace surveys of wildlife populations that span many discrete management units?
<p>Monitoring widely distributed species on a budget presents challenges for the spatio-temporal allocation of survey effort. When there are multiple discrete units to monitor, survey alternatives such as model-based estimates can be useful to fill information-gaps but may not reliably reflect biological complexity and change. The spatio-temporal allocation of survey effort that minimizes uncertainty for the greatest number of units within a budget can help to ensure monitoring efforts are optimized.</p> <p>We used aerial survey-based population estimates of moose (Alces alces) across 30 Wildlife Management Units (WMUs) in Ontario, Canada to parameterize simulated populations and test the performance of different monitoring scenarios in capturing WMU-specific annual variation and trends. Firstly, we tested scenarios that prioritized conducting a survey for a unit based on one of three management criteria: population state, population uncertainty, or number of years between surveys. Also incorporated in the decision framework were WMU-specific costs and annual budget constraints. Secondly, we tested how using model-based estimates to fill information-gaps improved population and trend estimates. Lastly, we assessed how the utility (based on minimizing population uncertainty) of using a model-based estimate rather than conducting a survey was impacted by population density, severity of environmental stressors, and years since the last survey.</p> <p>Interval-based monitoring that minimized the number of years between surveys captured accurate trends for the highest number of WMUs, but annual variation was poorly captured regardless of management criteria prioritized. Using model-based estimates to fill information gaps improved trend estimation. Further, the utility of conducting a survey increased with time since the last survey and was greater for populations with low densities when the severity of environmental stressors was high, while being greater for populations with high densities when environmental severity was low.</p> <p>Overall, the utility of aerial survey monitoring was strongly associated with WMU-specific monitoring precision and the predictive power of model-based estimates. If long-term trends are evident then there is greater value in using alternatives such as model-based predictions to replace surveys, but model-based estimates may be a poor substitute when there is strong annual variation and when using a simple model.</p>
South-East US historical and projected population per county for FUTURES urban growth modeling in GRASS GIS
<p>South East US historical (2001-2019) and projected (2020-2100) population per county for 6 states (NC, SC, TN, GA, AL, FL). Historical data come from The National Vital Statistics System (https://seer.cancer.gov/popdata/download.html) and future data are projected by Hauer 2019 (https://doi.org/10.1038/sdata.2019.5) for SSP2 scenario. Data are formatted for r.futures.demand module, which is a GRASS GIS addon for computing future land demand for FUTURES urban growth model. </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.