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451 results for “outbreaks”
Data from: Small beetle, large-scale drivers: how regional and landscape factors affect outbreaks of the European spruce bark beetle
Unprecedented bark beetle outbreaks have been observed for a variety of forest ecosystems recently, and damage is expected to further intensify as a consequence of climate change. In Central Europe, the response of ecosystem management to increasing infestation risk has hitherto focused largely on the stand level, while the contingency of outbreak dynamics on large-scale drivers remains poorly understood. To investigate how factors beyond the local scale contribute to the infestation risk from Ips typographus (Col., Scol.), we analysed drivers across seven orders of magnitude in scale (from 103 to 1010 m²) over a 23-year period, focusing on the Bavarian Forest National Park. Time-discrete hazard modelling was used to account for local factors and temporal dependencies. Subsequently, beta regression was applied to determine the influence of regional and landscape factors, the latter characterized by means of graph theory. We found that in addition to stand variables, large-scale drivers also strongly influenced bark beetle infestation risk. Outbreak waves were closely related to landscape-scale connectedness of both host and beetle populations as well as to regional bark beetle infestation levels. Furthermore, regional summer drought was identified as an important trigger for infestation pulses. Large-scale synchrony and connectivity are thus key drivers of the recently observed bark beetle outbreak in the area. Synthesis and applications. Our multiscale analysis provides evidence that the risk for biotic disturbances is highly dependent on drivers beyond the control of traditional stand-scale management. This finding highlights the importance of fostering the ability to cope with and recover from disturbance. It furthermore suggests that a stronger consideration of landscape and regional processes is needed to address changing disturbance regimes in ecosystem management.
Data from: The return of the frogs: the importance of habitat refugia in maintaining diversity during a disease outbreak
Recent decades have seen the emergence and spread of numerous infectious diseases, often with severe negative consequences for wildlife populations. Nevertheless, many populations survive the initial outbreaks, and even undergo recoveries. Unfortunately, the long-term effects of these outbreaks on host population genetics are poorly understood; to increase this understanding, we examined the population genetics of two species of rainforest frogs (Litoria nannotis and Litoria serrata) that have largely recovered from a chytridiomycosis outbreak at two national parks in the Wet Tropics of northern Australia. At the wetter, northern park there was little evidence of decreased genetic diversity in either species, and all of the sampled sites had high minor allele frequencies (mean MAF = 0.230–0.235), high heterozygosity (0.318–0.325), and few monomorphic markers (1.4–4.0%); however, some recovered L. nannotis populations had low Ne values (59.3–683.8) compared to populations that did not decline during the outbreak (1537.4–1756.5). At the drier, southern park, both species exhibited lower diversity (mean MAF = 0.084–0.180; heterozygosity = 0.126–0.257; monomorphic markers = 3.7–43.5%; Ne = 18.4–676.1). The diversity patterns in this park matched habitat patterns, with both species having higher diversity levels and fewer closely related individuals at sites with higher quality habitat. These patterns were more pronounced for L. nannotis, which has lower dispersal rates than L. serrata. These results suggest that refugia with high quality habitat are important for retaining genetic diversity during disease outbreaks, and that gene flow following disease outbreaks is important for restabilising diversity in populations where it was reduced.
Data from: Intraspecific predator inhibition, not a prey size refuge, enables oyster population persistence during predator outbreaks
Predators commonly structure natural communities, but predation effects can vary greatly. For example, increasing predator densities may not reduce prey populations as expected if intraspecific predator interactions suppress foraging efficiency or if prey size refuges exist. In northeastern Florida (USA), outbreaks of the predatory crown conch Melongena corona have contributed to declines in oyster populations and the commercial oyster fishery. However, despite expectations of oyster population collapse, reefs have persisted, albeit with reduced adult oyster size and living reef biomass. To investigate the mechanism(s) underlying this unexpected persistence, we used field observations and experiments to examine the effects of predator density and prey size on predation rates. Multi-year surveys indicated that large oysters did not experience a predation size refuge, and further suggested that predation rates declined with increased predator density. Consistent with field surveys, field experiments demonstrated that conchs selectively consumed larger oysters (potentially explaining the absence of large oysters on natural reefs) and that high conch densities suppressed per capita predation rates, likely due to intraspecific antagonistic interactions. A Type III ratio-dependent model best described the experimental conch functional response, explaining >50% of the variation in per capita prey consumption and including a signal of reduced attack rates at high predator densities. Thus, although large aggregations of predators have the potential to deplete prey populations, our study illustrates intraspecific predator interactions that possibly prevent the local extirpation of an important habitat-forming prey species.
Data from: Seasonal difference in temporal transferability of an ecological model: near-term predictions of lemming outbreak abundances
Ecological models have been criticized for a lack of validation of their temporal transferability. Here we answer this call by investigating the temporal transferability of a dynamic state-space model developed to estimate season-dependent biotic and climatic predictors of spatial variability in outbreak abundance of the Norwegian lemming. Modelled summer and winter dynamics parametrized by spatial trapping data from one cyclic outbreak were validated with data from a subsequent outbreak. There was a distinct difference in model transferability between seasons. Summer dynamics had good temporal transferability, displaying ecological models' potential to be temporally transferable. However, the winter dynamics transferred poorly. This discrepancy is likely due to a temporal inconsistency in the ability of the climate predictor (i.e. elevation) to reflect the winter conditions affecting lemmings both directly and indirectly. We conclude that there is an urgent need for data and models that yield better predictions of winter processes, in particular in face of the expected rapid climate change in the Arctic.
Within-host priority effects and epidemic timing determine outbreak severity in coinfected populations
Coinfections of hosts by multiple pathogen species are ubiquitous, but predicting their impact on disease remains challenging. Interactions between coinfecting pathogens within hosts can alter pathogen transmission, with the impact on transmission typically dependent on the relative arrival order of pathogens within hosts (within-host priority effects). However, it is unclear how these within-host priority effects influence multi-pathogen epidemics, particularly when the arrival order of pathogens at the host population scale varies. Here we combined models and experiments with zooplankton and their naturally co-occurring fungal and bacterial pathogens to examine how within-host priority effects influence multi-pathogen epidemics. Epidemiological models parameterized with within-host priority effects measured at the single host scale predicted that advancing the start date of bacterial epidemics relative to fungal epidemics would decrease mean bacterial prevalence in a multi-pathogen setting, while models without within-host priority effects predicted the opposite effect. We tested these predictions with experimental multi-pathogen epidemics. Empirical dynamics matched predictions from the model including within-host priority effects, providing evidence that within-host priority effects influenced epidemic dynamics. Overall, within-host priority effects may be a key element of predicting multi-pathogen epidemic dynamics in the future, particularly as shifting disease phenology alters the order of infection within hosts.
Data from: Multi-temporal analysis reveals that predictors of mountain pine beetle infestation change during outbreak cycles
Over the past two decades, severe mountain pine beetle (MPB) outbreaks have affected several million hectares of forest in western North America. The extensive ecological and economic damage caused by widespread insect infestations make understanding the development and spread of MPB outbreaks critical. This study uses a time series of Landsat5 TM and Landsat7 ETM + images to map the spread of mortality due to MPB infestation in Arapaho–Roosevelt National Forest, Colorado, between 2003 and 2010. The Normalized Difference Vegetation Index (NDVI) and change in the Normalized Difference Moisture Index (NDMI) were used to classify red attack and non-red attack stands based on a maximum likelihood algorithm with manually selected training classes. The classification was validated by comparison with independent interpretations of aerial photography and high-resolution satellite imagery. The classification had good agreement (84.5–90.5% total accuracy). Cluster analysis for time series showed infestations originating in several different locations on the landscape early in the time series and subsequent infestations likely represent a combination of dispersal from outbreak populations and independent population growth. Analysis using conditional inference trees suggested that a combination of forest composition, topography, and dispersal predicted the distribution of MPB infestation on the landscape and that the importance of these variables changed as the outbreak developed. In early years, red attack was associated with forest and topographic characteristics known to influence susceptibility to MPB. Over time, beetle pressure became an increasingly important predictor of red attack, but in later years host tree availability played an important role in outbreak spread. If this pattern occurs consistently in MPB outbreaks, knowledge of these patterns could aid managers in targeting their efforts to reduce damage resulting from MPB outbreaks.
Data from: Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli
Background: In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Methods: Specific peaks in the outbreak strain's spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Results: Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. Conclusions: MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.
Host plant phenology, insect outbreaks and herbivore communities – the importance of timing
1. Climate change may alter the dynamics of outbreak species by changing the phenological synchrony between herbivores and their host plants. As host plant phenology has a genotypic component that may interact with climate, infestation levels among genotypes might change accordingly. When the outbreaking herbivore is active early in the season, its infestation levels may also leave a detectable imprint on herbivores colonizing the plant later in the season. 2. In this study, we first investigated how the spring phenology and genotype of Quercus robur influenced the density of the spring-active, outbreaking leaf miner Acrocercops brongniardellus. We then assessed how intraspecific density affected the performance of A. brongniardellus and how oak genotype and density of A. brongniardellus affected the insect herbivore community. 3. We found that Q. robur individuals of late spring phenology were more strongly infested by A. brongniardellus. Conspecific pupae on heavily infested oaks tended to be lighter, and fewer heterospecific insect herbivores colonized the oak later in the season. Beyond its effects through phenology, plant genotype left an imprint on herbivore species richness and on two insect herbivores. 4. Our results suggest a chain of knock-on effects from plant phenology, through the outbreaking species to the insect herbivore community. Given the finding of how phenological synchrony between the outbreak species and its host plant influences infestation levels, a shift in synchrony may then change outbreak dynamics and cause cascading effects on the insect community. 29-Oct-2019
Data from: Combinations of plant water-stress and neonicotinoids can lead to secondary outbreaks of Banks grass mite (Oligonychus pratensis Banks)
Spider mites, a cosmopolitan pest of agricultural and landscape plants, thrive under hot and dry conditions, which could become more frequent and extreme due to climate change. Recent work has shown that neonicotinoids, a widely used class of systemic insecticides that have come under scrutiny for non-target effects, can elevate spider mite populations. Both water-stress and neonicotinoids independently alter plant resistance against herbivores. Yet, the interaction between these two factors on spider mites is unclear, particularly for Banks grass mite (Oligonychus pratensis; BGM). We conducted a field study to examine the effects of water-stress (optimal irrigation = 100% estimated evapotranspiration (ET) replacement, water stress = 25% of the water provided to optimally irrigated plants) and neonicotinoid seed treatments (control, clothianidin, thiamethoxam) on resident mite populations in corn (Zea mays, hybrid KSC7112). Our field study was followed by a manipulative field cage study and a parallel greenhouse study, where we tested the effects of water-stress and neonicotinoids on BGM and plant responses. We found that water-stress and clothianidin consistently increased BGM densities, while thiamethoxam-treated plants only had this effect when plants were mature. Water-stress and BGM herbivory had a greater effect on plant defenses than neonicotinoids alone, and the combination of BGM herbivory with the two abiotic factors increased the concentration of total soluble proteins. These results suggest that spider mite outbreaks by combinations of changes in plant defenses and protein concentration are triggered by water-stress and neonicotinoids, but the severity of the infestations varies depending on the insecticide active ingredient.
Data from: Adaptive nowcasting of influenza outbreaks using Google searches
Seasonal influenza outbreaks and pandemics of new strains of the influenza virus affect humans around the globe. However, traditional systems for measuring the spread of flu infections deliver results with one or two weeks delay. Recent research suggests that data on queries made to the search engine Google can be used to address this problem, providing real-time estimates of levels of influenza-like illness in a population. Others have however argued that equally good estimates of current flu levels can be forecast using historic flu measurements. Here, we build dynamic 'nowcasting' models; in other words, forecasting models that estimate current levels of influenza, before the release of official data one week later. We find that when using Google Flu Trends data in combination with historic flu levels, the mean absolute error (MAE) of in-sample 'nowcasts' can be significantly reduced by 14.4%, compared with a baseline model that uses historic data on flu levels only. We further demonstrate that the MAE of out-of-sample nowcasts can also be significantly reduced by between 16.0% and 52.7%, depending on the length of the sliding training interval. We conclude that, using adaptive models, Google Flu Trends data can indeed be used to improve real-time influenza monitoring, even when official reports of flu infections are available with only one week's delay.
Data from: Anthrax outbreaks in the humans-livestock and wildlife interface areas of northern Tanzania: a retrospective review 2006 - 2016
BACKGROUND: Anthrax outbreaks in Tanzania have been reported from the human, livestock and wildlife sectors over several years, and is among the notifiable diseases. Despite frequent anthrax outbreaks, there is no comprehensive dataset indicating the magnitude and distribution of the disease in susceptible species. This study is a retrospective review of anthrax outbreaks from the human, livestock, and wildlife surveillance systems from 2006 to 2016. The objectives were to identify hotspot districts, describe anthrax epidemiology in the hotspot areas, evaluate the efficiency of the anthrax response systems and identify potential areas for further observational studies. METHODS: We prepared a spreadsheet template for a retrospective comprehensive record review at different surveillance levels in Tanzania. We captured data elements including demographic characteristics of different species, the name of health facility, and date of anthrax diagnosis. Also, we collected data on the date of specimen collection, species screened, type of laboratory test, laboratory results and the outcome recorded at the end of treatment in humans. After establishing the database, we produced maps in Quantum GIS software and transferred cleaned data to Stata software for supportive statistical analysis. RESULTS: Anthrax reported incidences over 4 years in humans were much higher in the Arusha region (7.88/100,000) followed by Kilimanjaro region (6.64/100,000) than other regions of Tanzania Mainland. The health facility based review from hotspot districts in parts of Arusha and Kilimanjaro regions from 2006 to 2016, identified 330 human anthrax cases from the selected health facilities in the two regions. Out of 161 livestock and 57 wildlife specimen tested, 103 and 18 respectively, were positive for anthrax. CONCLUSION: This study revealed that there is gross under-reporting in the existing surveillance systems which is an obstacle for estimating a true burden of anthrax in the hotspot districts. Repeated occurrences of anthrax in livestock, wildlife and humans in the same locations at the same time calls for the need to strengthen links and promote inter-disciplinary and multi-sectoral collaboration to enhance prevention and control measures under a One Health approach.
Data from: Prescribed fire does not promote outbreaks of a primary bark beetle at low-density populations
The causes of bark beetle outbreaks – particularly the role of disturbances – are poorly understood. Stand-scale disturbances, like fires, can suddenly improve local host susceptibility and may attract beetles; however, whether such increases can lead to outbreaks in post-disturbance stands is unclear. Using low-density Dendroctonus ponderosae mountain pine beetle populations in Pinus contorta lodgepole pine forests in western Canada, we investigated whether prescribed fires promote outbreaks or provide only short-term resources. Proportionally more burned than non-burned trees were attacked. At one site, beetle attacks increased in response to a resource pulse, but the proportions of attacked trees and numbers of attacks per tree declined over four years after fire. Elsewhere, beetle attacks remained very low. As the resource (phloem) quality of burned trees remained high three years after fire, we propose that post-fire mortality, resulting in fewer available host trees, can at least partially explain why D. ponderosae did not build up populations in burned stands. Synthesis and applications. Our study emphasizes the importance of examining long-term trends in fire–bark beetle interactions, and of understanding low-density beetle populations. Because fire does not seem to promote mountain pine beetle outbreaks, we recommend the continued use of prescribed fire for the general management of P. contorta forests with low-density beetle populations.
Data from: Occurrence and phylogenetic analysis of bovine respiratory syncytial virus in outbreaks of respiratory disease in Norway
Background: Bovine respiratory syncytial virus (BRSV) is one of the major pathogens involved in the bovine respiratory disease (BRD) complex. The seroprevalence to BRSV in Norwegian cattle herds is high, but its role in epidemics of respiratory disease is unclear. The aims of the study were to investigate the etiological role of BRSV and other respiratory viruses in epidemics of BRD and to perform phylogenetic analysis of Norwegian BRSV strains. Results: BRSV infection was detected either serologically and/or virologically in 18 (86%) of 21 outbreaks and in most cases as a single viral agent. When serology indicated that bovine coronavirus and/or bovine parainfluenza virus 3 were present, the number of BRSV positive animals in the herd was always higher, supporting the view of BRSV as the main pathogen. Sequencing of the G gene of BRSV positive samples showed that the current circulating Norwegian BRSVs belong to genetic subgroup II, along with other North European isolates. One isolate from an outbreak in Norway in 1976 was also investigated. This strain formed a separate branch in subgroup II, clearly different from the current Scandinavian sequences. The currently circulating BRSV could be divided into two different strains that were present in the same geographical area at the same time. The sequence variations between the two strains were in an antigenic important part of the G protein. Conclusion: The results demonstrated that BRSV is the most important etiological agent of epidemics of BRD in Norway and that it often acts as the only viral agent. The phylogenetic analysis of the Norwegian strains of BRSV and several previously published isolates supported the theory of geographical and temporal clustering of BRSV.
Data from: Insecticides promote viral outbreaks by altering herbivore competition
While the management of biological invasions is often characterized by a series of single-species decisions, invasive species exist within larger food webs. These biotic interactions can alter the impact of control/eradication programs and may cause suppression efforts to inadvertently facilitate invasion spread and impact. We document the rapid replacement of the invasive Bemisia MEAM1 cryptic species by the cryptic MED species throughout China, and demonstrate that MED is more tolerant of insecticides and a better vector of tomato yellow leaf curl virus ('TYLCV') than MEAM1. While MEAM1 usually excludes MED under natural conditions, insecticide application reverses the MEAM1-MED competitive hierarchy and allows MED to exclude MEAM1. The insecticide-mediated success of MED has led to TYLCV outbreaks throughout China. Our work strongly supports the hypothesis that insecticide use in China reverses the MEAM1-MED competitive hierarchy and allows MED to displace MEAM1 in managed landscapes. By promoting the dominance of a Bemisia species that is a competent viral vector, insecticides thus increase the spread and impact of TYLCV in heterogeneous agroecosystems.
Data from: Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks
Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes.
Data from: Human-mediated disturbance in multitrophic interactions results in outbreak levels of North America's most venomous caterpillar
Abstract Anthropogenic environmental change is predicted to disrupt multitrophic interactions, which may have drastic consequences for population-level processes. Here, we investigate how a large-scale human-mediated disturbance affects the abundance of North America's most venomous caterpillar species, Megalopyge opercularis. Specifically, we used a natural experiment where netting was deployed to cover the entire canopies of a subset of mature southern live oak trees (Quercus virginiana) to exclude urban pest birds (grackles and pigeons), throughout an 8.1-km2 area encompassing a medical center in Houston, Texas. We used this experimental exclusion to test the following hypothesis: release from avian predators increases caterpillar abundance to outbreak levels, which increases the risk to human health. Results from a multi-year survey show that caterpillar abundance increased, on average, >7300% on netted versus non-netted trees. Thus, increases in caterpillar abundance, due to anthropogenic enemy release, increase human exposure to this venomous pest, and should be considered a health threat in the area. This study emphasizes the unforeseen consequences of ecological disturbance for species interactions and highlights the importance of considering ecology in urban planning.
Data from: Descriptive epidemiology of the 2018 cholera outbreak in Nigeria: implications for the global roadmap strategies
Introduction: The 2018 cholera outbreak in Nigeria indicates that the disease remains an enormous public health threat. This paper, therefore, provides an epidemiological description of the outbreak, with a view to provide current evidence for public health planning and interventions towards cholera elimination in the country. Methods/Principal Findings: This was a retrospective analysis of surveillance data from January 1st to November 19th, 2018. A cholera case was defined as an individual aged 2 years or older with acute watery diarrhoea, and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed in terms of person, time and place. Overall, there were 43,996 cases with an attack rate (AR) of 127.43/100,000 population, and 836 deaths with a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) recorded the highest number of cases, while the proportion of males (49.00%) and females (51.00%) was nearly equal. The outbreak was characterised by four distinct epidemic waves, with higher records of deaths towards the end of the outbreak (296 and 295 deaths in the third and fourth waves, respectively). States from the north-west and north-east regions reported the highest ARs, while those from the north-central region reported the highest CFRs. Conclusion: The distribution of the 2018 cholera outbreak in Nigeria indicates an elevated burden, especially in the northern part of the country, and the influence of diverse and interrelated drivers; thus, underlining the need to adopt a multi-sectoral approach to cholera prevention and control in the country as outlined in the Global Roadmap strategies.
Data from: Aggregation and a strong Allee effect in a cooperative outbreak insect
Most species that are negatively impacted when their densities are low aggregate to minimize this effect. Aggregation has the potential to change how Allee effects are expressed at the population level. We studied the interplay between aggregation and Allee effects in the mountain pine beetle (Dendroctonus ponderosae Hopkins), an irruptive bark beetle that aggregates to overcome tree defenses. By cooperating to surpass a critical number of attacks per tree, the mountain pine beetle is able to breach host defenses,oviposit and reproduce. Mountain pine beetles and Hymenopteran parasitoids share some biological features, the most notable of which is obligatory host death as a consequence of parasitoid attack and development. We developed spatiotemporal models of mountain pine beetle dynamics that were based on the Nicholson-Bailey framework but which featured beetle aggregation and a tree-level attack threshold. By fitting our models to data from a local mountain pine beetle outbreak, we demonstrate that due to aggregation, attack thresholds at the tree level can be overcome by a surprisingly low ratio of beetles per susceptible tree at the stand level. This results confirms the importance of considering aggregation in models of organisms that are subject to strong Allee effects.
Immunity levels to poliovirus in Lao children and adults before the vaccine-derived poliovirus outbreak
<p>Immunity levels to poliovirus in Lao children and adults before the vaccine-derived poliovirus outbreak: a retrospective study</p>
Supplementary material from "Utilising citizen science data to rapidly assess changing associations between wild birds and avian influenza outbreaks in poultry."
<p>Stephen H. Vickers, Jayna Raghwani, Ashley C. Banyard, Ian H. Brown, Guillaume Fournie and Sarah C. Hill </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.