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2,603 results for “Ecological data”
Data from: Spatial structure of ecological opportunity drives adaptation in a bacterium
Abundant ecological opportunity is thought to drive adaptation and diversification. The presence of multiple opportunities leads to divergent selection, which can slow adaptation when niche-specific beneficial mutations have antagonistically pleiotropic effects. Alternately, competition for multiple opportunities can generate divergent selection leading to high rates of adaptive differentiation. Which outcome occurs may depend on the spatial structure of those ecological opportunities. In a mixture of resources, competition for multiple opportunities can drive divergent selection; however if each resource is available in a spatially distinct patch, competition for multiple opportunities simultaneously cannot occur. We report the effects of extent and spatial structure of ecological opportunity on the evolutionary dynamics of populations of Pseudomonas fluorescens over 1000 generations. We varied extent of ecological opportunity by varying the number of sugar resources (mannose, glucose, and xylose), and varied spatial structure by providing resources in either mixtures, or spatially distinct patches. We saw that a particularly novel resource (xylose) drove the rate of adaptation when in a mixture but had no effect on diversity. Instead we saw the evolution of a single adaptive strategy that differed with respect to phenotype and degree of specialization, depending on both the extent and spatial structure of ecological opportunity.
Data from: Ecological character displacement between the sexes
Theory suggests the evolution of sexual dimorphism in ecologically relevant traits can evolve purely through competition between the sexes for a shared resource. Although more parsimonious hypotheses exist for the evolution of ecological sexual dimorphisms, there are some underappreciated reasons to expect that competition may often play some role in the evolution of sexual dimorphism. Here, we build on past work to outline a set of sufficient criteria to demonstrate a role for resource competition in the evolution of sexual dimorphism, the most critical of which is that resource competition can be directly linked to sexual divergence along the axis of ecologically-relevant dimorphism. We then compare the geometry of fitness surfaces across experimental manipulations of density and sex ratio in a semiaquatic salamander (Notophthalmus viridescens). We find consistent disruptive selection on multivariate sexual dimorphism in feeding morphology, which increases in strength with density. Fitness and the strength of divergent selection are negative-frequency dependent in the manner expected under competition-driven divergence between the sexes. Our results constitute direct evidence of resource competition as a driver of sexually-antagonist selection and consequently the evolution of sexual dimorphism, showing how cause and effect can be separated in studies of ecological sexual dimorphism. We suggest resource competition may contribute to sexual divergence jointly with other sources of sex-biased selection, especially when ecological opportunity is sex-specific. EndDryadContent
Data from: Phylogeny, ecology and deep time: 2D outline analysis of anuran skulls from the Early Cretaceous to Recent
Anurans have a long fossil record, spanning from the Early Jurassic to Recent. However, specimens are often severely flattened, limiting their inclusion in quantitative analyses of morphological evolution. We perform a two-dimensional morphometric analysis of anuran skull outlines, incorporating 42 Early Cretaceous to Miocene species, as well as 93 extant species in 32 families. Outlines were traced in tpsDig2 and analysed with elliptical Fourier analysis. Fourier coefficients were used in MANOVAs, phylogenetic MANOVAs (as significant phylogenetic signal was found) and disparity analyses across multiple ecological and life history groupings. The Neotropical realm showed higher disparity than the Australian, Palearctic and Oriental realms (p = 0.007, 0.013, 0.038, respectively), suggesting concordance of disparity and diversity. Developmental strategy had a weak effect on skull shape (R2 = 0.02, p = 0.039), and disparity was similar in metamorphosing and direct developing frogs. Ecological niche was a significant discriminator of skull shape (F = 1.43, p = 0.004), but not after phylogenetic correction. Evolutionary allometry had a small but significant influence on the cranial outlines of the combined extant and fossil dataset (R2 = 0.05, p = 0.004). Finally, morphospace occupation appears to have changed over time (F = 1.59, p = 5 × 10-10). However, as with ecological signal, this shift appears to be largely driven by phylogeny and was not significant after phylogenetic correction (R2 = 0.26, p = 0.22). This study thus suggests that frog skull evolution is shaped more by phylogenetic constraints than by ecology.
Data from: Heterospecific aggression and dominance in a guild of coral-feeding fishes: the roles of dietary ecology and phylogeny
Interspecific competition mediates biodiversity maintenance and is an important selective pressure for evolution. Competition is often conceptualized as being exploitative (indirect) or involving direct interference. However, most empirical studies are phenomenological, focusing on quantifying effects of density manipulations, and most competition theory has characterized exploitation competition systems. The effects on resource use of traits associated with direct, interference competition has received far less attention. Here we examine the relationships of dietary ecology and phylogeny to heterospecific aggression in a guild of corallivorous reef fishes. We find that, among chaetodontids (butterflyfishes), heterospecific aggression depends on a synergistic interaction of dietary overlap and specialization: aggression increases with dietary overlap for interactions between specialists but not for interactions involving generalists. Moreover, behavioral dominance is a monotonically increasing function of dietary specialization. The strong, positive relationship of dominance to specialization suggests that heterospecific aggression may contribute to the maintenance of biodiversity where it promotes resource partitioning. Additionally, we find strong phylogenetic signals in dietary overlap and specialization but not behavioral dominance. Our results support the use of phylogeny as a proxy for ecological similarity among butterflyfishes, but we find that direct measures of dietary overlap and specialization predict heterospecific agression much better than phylogeny.
Data from: Phylogenetic revision of the Strophomenida, a diverse and ecologically important palaeozoic brachiopod order
The order Strophomenida was an ecologically abundant and taxonomically diverse group of Palaeozoic brachiopods that originated in the earliest Ordovician and went extinct in the Carboniferous. During their long geological range, the Strophomenida survived two of the 'Big Five' mass extinction events, the Late Ordovician and the Late Devonian, suggesting that they are potentially informative taxa for studying the evolutionary effects of these two distinct mass extinctions, each with drastically different forcing mechanisms. However, while there have been previous phylogenetic studies on smaller groups within the Strophomenida, the phylogenetic relationships of the whole group are still largely unknown. The group has been divided into two major superfamilies, the Strophomenoidea (strophomenoids) and the Plectambonitoidea (plectambonitoids). Despite being treated as separate clades, the plectambonitoids may form a paraphyletic grade into the strophomenoids. We present a detailed higher-level parsimony-based phylogenetic analysis of the Strophomenida, consisting of 69 characters and 62 exemplar species sampled from the majority of the taxonomically defined families/subfamilies. Several species of basal chonetids (strophochonetids) were also included in this analysis, as they may be closely related to the Strophomenida and share several characters with both the plectambonitoids and strophomenoids. The phylogenetic analysis suggests the plectambonitoids, as originally defined, are paraphyletic to the monophyletic strophomenoids. The basal chonetids are reconstructed as a monophyletic group that is sister to the strophomenoids, suggesting that their proper placement might be within the Strophomenida. The topology also suggests that at least 17 of the taxonomically defined strophomenoid and plectambonitoid families are likely to be monophyletic. The Plectambonitidae and the Taffiidae as defined are paraphyletic, and the Grorudiidae and Leptostrophiidae are polyphyletic. Furthermore, subfamilies Leptodontellinae, Dicoelostrophiinae, Palaeostrophomeninae and Aegiromeninae are raised to the level of family. When analysed within this phylogenetic context, the Late Ordovician mass extinction event had little effect on the large-scale evolution of the group.
Data from: The genetic architecture of a complex ecological trait: host plant use in the specialist moth, Heliothis subflexa
We used genetic mapping to examine the genetic architecture of differences in host plant use between two species of noctuid moths, Heliothis subflexa, a specialist on Physalis spp., and its close relative, the broad generalist H. virescens. We introgressed H. subflexa chromosomes into the H. virescens background and analyzed 1,462 backcross insects. The effects of H. subflexa-origin chromosomes were small when measured as the percent variation explained in backcross populations (0.2 to 5%), but were larger when considered in relation to the interspecific difference explained (1.5 to 165%). Most significant chromosomes had effects on more than one trait, and their effects varied between years, sexes, and genetic backgrounds. Different chromosomes could produce similar phenotypes, suggesting that the same trait might be controlled by different chromosomes in different backcross populations. It appears that many loci of small effect contribute to the use of Physalis by H. subflexa. We hypothesize that behavioral changes may have paved the way for physiological adaptation to Physalis by the generalist ancestor of H. subflexa and H. virescens.
Data from: Linking intra-specific trait variation to community abundance dynamics improves ecological predictability by revealing a growth-defence trade-off
1.Intraspecific trait change, including altered behaviour or morphology, can drive temporal variation in inter-specific interactions and population dynamics. In turn, variation in species' interactions and densities can alter the strength and direction of trait change. The resulting feedback between species′ traits and abundance permits a wide range of community dynamics that would not be expected from ecological theories purely based on species abundances. Despite the theoretical importance of these interrelated processes, unambiguous experimental evidence of how intraspecific trait variation modifies species interactions and population dynamics and how this feeds back to influence trait variation is currently required. 2.We investigate the role of trait-mediated demography in determining community dynamics and examine how ecological interactions influence trait change. We concurrently monitored the dynamics of community abundances and individual traits in an experimental microbial predator-prey-resource system. Using this data, we parameterized a trait dependent community model to identify key ecologically relevant traits and to link trait dynamics with those of species abundances. 3.Our results provide clear evidence of a feedback between trait change, demographic rates and species dynamics. The inclusion of trait-abundance feedbacks into our population model improved the predictability of ecological dynamics from r-squared of 34% to 57% and confirmed theoretical expectations of density dependent population growth and species interactions in the system. 4.Additionally, our model revealed that the feedbacks were underpinned by a trade-off between population growth and anti-predatory defence. High predator abundance was linked to a reduction in prey body size. This prey size decrease was associated with a reduction in its rate of consumption by predators and a decrease in its resource consumption. 5.Modelling trait-abundance feedbacks allowed us to pinpoint the underlying life history trade-off which links trait and abundance dynamics. These results show that accounting for trait-abundance feedbacks has the potential to improve understanding and predictability of ecological dynamics.
Data from: Ungulate predation and ecological roles of wolves and coyotes in eastern North America
Understanding the ecological roles of species that influence ecosystem processes is a central goal of ecology and conservation biology. Eastern coyotes (Canis latrans) have ascended to the role of apex predator across much of eastern North America since the extirpation of wolves (Canis spp.) and there has been considerable confusion regarding their ability to prey on ungulates and their ecological niche relative to wolves. Eastern wolves (C. lycaon) are thought to have been the historical top predator in eastern deciduous forests and have previously been characterized as deer specialists that are inefficient predators of moose because of their smaller size relative to gray wolves (C. lupus). We investigated intrinsic and extrinsic influences on per capita kill rates of white-tailed deer (Odocoileus virginianus) and moose (Alces alces) during winter by sympatric packs of eastern coyotes, eastern wolves, and admixed canids in Ontario, Canada to clarify the predatory ability and ecological roles of the different canid top predators of eastern North America. Eastern coyote ancestry within packs negatively influenced per capita total ungulate (deer and moose combined) and moose kill rates. Furthermore, canids in packs dominated by eastern coyote ancestry consumed significantly less ungulate biomass and more anthropogenic food than packs dominated by wolf ancestry. Similar to gray wolves in previous studies, eastern wolves preyed on deer where they were available. However, in areas were deer were scarce, eastern wolves killed moose at rates similar to those previously documented for gray wolves at comparable moose densities across North America. Eastern coyotes are effective deer predators, but their dietary flexibility and low kill rates on moose suggest they have not replaced the ecological role of wolves in eastern North America.
FIGURE 6 in A revision of the genus Conicofrontia Hampson (Lepidoptera, Noctuidae, Apameini, Sesamiina), with description of a new species: new insights from morphological, ecological and molecular data
FIGURE 6. Distribution map of sampled Conicofrontia and Hygrostola specimens.
FIGURE 1 in A revision of the genus Conicofrontia Hampson (Lepidoptera, Noctuidae, Apameini, Sesamiina), with description of a new species: new insights from morphological, ecological and molecular data
FIGURE 1. Adults of Conicofrontia species (C. bipartita and C. diamesa). Scale bar = 10 mm.
FIGURE 2 in A revision of the genus Conicofrontia Hampson (Lepidoptera, Noctuidae, Apameini, Sesamiina), with description of a new species: new insights from morphological, ecological and molecular data
FIGURE 2. Adults of Conicofrontia species (C. lilomwa and C. sesamoides). Scale bar = 10 mm.
FIGURE 4 in A revision of the genus Conicofrontia Hampson (Lepidoptera, Noctuidae, Apameini, Sesamiina), with description of a new species: new insights from morphological, ecological and molecular data
FIGURE 4. Last instar larvae of Conicofrontia species. Scale bar = 10 mm.
Data from: Refining the trophic diversity, ecological network structure, and bottom-up importance of prey groups for temperate reef fishes
<p>The file "Zarco-Perello et al Temperate Reef Fish Trophic Guilds Complete Diet Dataset.xlsx" contains several spreadsheet tabs related to the analyses carried out in the paper: <i><strong>Refining the trophic diversity, ecological network structure, and bottom-up importance of prey groups for temperate reef fishes: </strong></i><a href="https://doi.org/10.32942/X2CC97">https://doi.org/10.32942/X2CC97</a></p><p>All analyses, with the exception of the network calculations, of the study were carried out in the computer software R. The code is contained in the file "Zarco-Perello et al Temperate Reef Fish Trophic Ecology.R". For trophic network analyses we used the computer program Gephi v0.1 <a href="https://sciwheel.com/work/citation?ids=15257446&amp;pre=&amp;suf=&amp;sa=0">(Bastian et al. 2009).</a></p><p><strong>DATASET DESCRIPTION</strong></p><p><strong>Region of Study</strong></p><p>The region of study encompasses all the temperate reefs of south-western Australia (SWA). Extending along ~1600 km of coast, from Jurien Bay Marine Park (30° 18.6 S, 115° 0.1 E) to the Recherche Archipelago Nature Research (33° 53.7 S, 123° 52.3 E; supplementary Fig. S1), the temperate reefs of SWA are distributed across the Leeuwin and Houtman biogeographical ecoregions <a href="https://sciwheel.com/work/citation?ids=1796477&pre=&suf=&sa=0">(Spalding et al. 2007)</a>, conforming approximately ⅓ of the total distribution of temperate Australia, known as the Great Southern Reef <a href="https://sciwheel.com/work/citation?ids=4498783&pre=&suf=&sa=0">(Bennett et al. 2016).</a></p><p><strong>Species Composition</strong></p><p>The species composition of the metacommunity of temperate reef fishes of the region was obtained from a total of 4589 underwater visual surveys conducted across 206 reefs in 12 locations by the Reef Life Survey (RLS) citizen science program, and the Australian Temperate Reef Collaboration (ATRC, with support from the Department of Biodiversity Conservation and Attractions; https://www.atrc.au) from 1997 to 2021.</p><p><strong>Trophic Information</strong></p><p>All fish species listed in the RLS-ATRC database were classified in trophic guilds based on collected diet information from studies of gut content analyses in SWA, or other Australian and international regions in the absence of local information. A total of 298 fish species composed the metacommunity. For every species, we obtained diet information from the scientific literature reported on Fishbase <a href="https://sciwheel.com/work/citation?ids=10423542&pre=&suf=&sa=0">(Froese and Pauly 2019)</a> and through the search engine Scopus using the search terms: TS = (<i>name of species</i>* OR *<i>common name of species</i>*) AND TS = (diet OR *stomach content* OR *gut content* OR consump* OR herbi* OR predat* OR feeding). Diet information consisted of the average proportions of food items represented as the number of items (%N), percent volume (%V), or biomass (%W) in a population of each species. Preference was given to diet studies conducted in the region of study and those presenting biomass proportions. Species that lacked diet information globally were assigned diet proportions based on phylogenetically related species with similar size and habitat preferences based on the Fish Tree of Life <a href="https://sciwheel.com/work/citation?ids=10720381&pre=&suf=&sa=0&dbf=0">(Chang et al. 2019)</a>.</p><p><i><< The tab "Guilds Complete Diet Dataset" contains all the diet information (stomach content proportions) and its sources for all fish species considered in the study >></i></p><p><strong>Trophic guilds classification</strong></p><p>To quantify the diversity of trophic guilds and identify important fish consumers of specific groups of prey, we classified the fish species into trophic guilds performing a multi-step cluster analysis. Firstly, species were grouped into main trophic guilds using the mutually exclusive major categories of prey items. The diet proportions in these categories were used to create a dissimilarity matrix among species based on the Bray-Curtis linkage method using the function <i>vegdist</i> of the R package Vegan <a href="https://sciwheel.com/work/citation?ids=7457489&pre=&suf=&sa=0">(Oksanen et al. 2022)</a>, which was used to run a sequential divisive hierarchical cluster analysis using the function <i>diana</i> (divisive analysis) of the R package Cluster <a href="https://sciwheel.com/work/citation?ids=15165291&pre=&suf=&sa=0">(Maechler et al. 2022)</a>. Subsequently, because there are mismatches in the resolution of diet identification between species belonging to different trophic levels (<i>e.g.</i> the diets of herbivorous fish tend to have higher resolution on macrophytes, while carnivorous species tend to have higher resolution on animal prey), species within each identified main trophic guild were subject to a cluster analysis with higher definition of prey items to identify groups of species with diet specializations using sequential agglomerative hierarchical cluster analysis based on Ward's Method and Bray-Curtis or Euclidean dissimilarity matrix <a href="https://sciwheel.com/work/citation?ids=205080&pre=&suf=&sa=0">(Pineda‑Munoz and Alroy 2014)</a>.</p><p>The stomach content of most scarid species (parrotfish; Labridae: Scarinae) is very difficult to identify due to their pharyngeal mill, which grinds all food items to indiscernible particles. However, they are well identified as a special group that ingest detritus and algae by scraping the reef substrate with their specialized fused teeth. Thus, for the sake of differentiating their trophic guild, the proportions of diet for species of parrotfish was arbitrarily defined based on field observations as sediment and detritus (90%) and short filamentous algae (10%) <a href="https://sciwheel.com/work/citation?ids=11332249&pre=&suf=&sa=0&dbf=0">(Bonaldo et al. 2014)</a>. Additionally, cleaner fish and false cleaners are a special group of fishes that are difficult to group by diet given that they feed on prey that could be identified as zooplankton or zoobenthos, while in fact true cleaners forage, at least in part, on parasitic invertebrates attached to bigger fish, in addition to fish skin and scales <a href="https://sciwheel.com/work/citation?ids=13921938&pre=&suf=&sa=0">(Grutter 1997)</a>; thus, given their particular trophic ecology these labrid and blenny species were arbitrarily grouped in the major trophic group "fish cleaners" for the subsequent specialized trophic group classifications.</p><p>Visual analysis of the differences in multidimensional space between trophic guilds was done with Non-metric Multidimensional Scaling based on the dissimilarity matrix calculated for clustering using the function <i>metaMDS</i> of the R package vegan (reported in supplementary materials; <a href="https://sciwheel.com/work/citation?ids=7457489&pre=&suf=&sa=0">(Oksanen et al. 2022)</a>. Statistical significance in dietary differences among major and specialized trophic guilds (diet proportions ~ trophic guilds) was tested with permutational analysis of variance (PERMANOVA) using the function <i>adonis2 </i>of the R package vegan <a href="https://sciwheel.com/work/citation?ids=7457489&pre=&suf=&sa=0">(Oksanen et al. 2022)</a>, followed by pairwise comparisons using the function <i>pairwise.adonis2</i> of the R package pairwiseAdonis <a href="https://sciwheel.com/work/citation?ids=15190336&pre=&suf=&sa=0">(Martinez 2017)</a>.</p><p><i><< The tabs in the dataset called "Major Guilds Diet Data", "Herbivores Diet Data", "Cleaners Diet Data", "Zoobenthivores Diet Data, "Zooplanktivores Diet Data", and "Piscivores Diet Data" are the datasets with selected diet categories for each guild without "unidentified diet items" and standardized to 100 proportion which were used for the classification of each major trophic guild into specialized trophic guilds. >></i></p><p><strong>Trophic Network Links Between Specialized Guilds</strong></p><p>The trophic links between fishes and their invertebrate and macrophyte prey groups were identified by our trophic guild classification (Other Guilds Links tab in dataset); however, the trophic role of piscivores is faced with what here we called a "matrioshka paradox", because to know their links with other guilds, we must first know the trophic links of their prey. Moreover, this is not straightforward because the highest taxonomic identification of piscivorous prey is usually limited to family level, which could belong to multiple trophic guilds. This paradox is usually not explicitly stated in the literature, and it is unclear how trophic links have been drawn in previous studies without performing detailed quantitative trophic classifications. Here we estimated the trophic links between piscivorous guilds and the rest of fish guilds by (i) assigning each fish family identified in the diets of piscivorous fishes into their respective specialized guilds based in our trophic classification, (ii) pooling their diet proportions into each specialized trophic guilds they could belong to, (iii) standardizing values by number of species in each piscivorous guild, and (iv) dividing by the total sum of diet proportions to estimate their potential predation (0-100%) on other trophic guilds in the trophic network. Trophic links that had pooled diet proportions with values <5% were discarded for clarity of the network (Piscivores Trophic Links tab in dataset). This information was joined with the trophic information from non-piscivorous trophic guilds and formatted as a list of nodes (guilds and prey groups), and links between nodes (source-target) to create the trophic network of the entire temperate reef fish metacommunity (Nodes Network List and Edges Network Lisk tabs in dataset). All network analyses were done using the computer program for network visualization and analyzes Gephi v0.1 <a href="https://sciwheel.com/work/citation?ids=15257446&pre=&suf=&sa=0">(Bastian et al. 2009)</a>.</p><p><i><< The tabs "Piscivores Trophic Links" and "Other Guilds Links" are datasets containing the calculations of the links between specialized trophic links for Piscivores and other guilds respectively used to create the data of the tabs "Nodes Network List" and "Edges Network List" to create the trophic network of the system of study. >></i></p><p><i><< The tab "Herbivory, Omnivory and Carnivory" contains diet proportion data of all fish species of the study formated to build the barplot (Fig. 4) in the manuscript showing the distribution of consumption of macrophytes, invertebrates and fishes >></i></p><p> </p>
Data and Scripts for Anonymous et al. "How to optimally allocate sampling effort in experimental ecology"
Open the record for dataset details and reuse information.
Data and Code for: Proximal microclimate: moving beyond spatiotemporal resolution improves ecological predictions
<p>Data and code corresponding to analyses and figures for the paper in review.</p>
Data for: Ecological associations distribution modelling of marine plankton at global scale (2024)
<p>Datasets used to generate and project ADMs.</p> <p><a href="https://gitlab.univ-nantes.fr/combi-ls2n/adm">Click here to access to the git repository</a></p>
Raw data sharing for the study of land usecover change and ecological effects in Lanxi urban agglomeration
Open the record for dataset details and reuse information.
Data and code for: "Mixed evidence for species diversity affecting ecological forecasts in constant versus declining light "
<p>Data and code for the article "<strong><span>Mixed evidence for species diversity affecting ecological forecasts in constant versus declining light </span></strong>"</p>
Data from: A migratory divide spanning two continents is associated with genomic and ecological divergence
<p>Migratory divides are contact zones between breeding populations with divergent migratory strategies during the non-breeding season. These locations provide an opportunity to evaluate the role of seasonal migration in the maintenance of reproductive isolation, particularly the relationship between population structure and features associated with distinct migratory strategies. We combine light-level geolocators, genomic sequencing, and stable isotopes to investigate the timing of migration and migratory routes of individuals breeding on either side of a migratory divide coinciding with genomic differentiation across a hybrid zone between barn swallow (<i>Hirundo rustica</i>) subspecies in China. Individuals west of the hybrid zone, with <i>H. r. rustica</i> ancestry, had comparatively enriched carbon isotope values and overwintered in eastern Africa, while birds east of the hybrid zone, with <i>H. r. gutturalis </i>ancestry, had depleted isotope values and migrated to southern India. The two subspecies took divergent migratory routes around the high-altitude Karakoram Range and arrived on the breeding grounds over three weeks apart. These results indicate that assortative mating by timing of arrival and/or selection against hybrids with intermediate migratory traits may maintain reproductive isolation between the subspecies, and that inhospitable geographic features may have contributed to the diversification of Asian avifauna by influencing migratory patterns.</p>
Data from: The ecological implications of intra- and inter-species variation in phenological sensitivity
<p>This dataset comprises phenology of flowering time of Claytonia virginica collected from iNaturalist and occurrence time of Andrena erigeniae collected from natural history collection and iNaturalist with associated climate derived from ClimateNA v7.3 and regions including Level III ecoregions, NEON domains, and plant hardiness zones. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.