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565 results for “Herbivory”
Ornithogenic alteration of a tundra ecosystem from decades of intense herbivory and dense nesting
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Data from: Insect herbivory in novel Quercus ilex L. forests: the role of landscape attributes, forest composition and host traits
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Herbivory of a biocontrol agent on a native plant causes an indirect trait-mediated non-target effect on a native insect
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Data from: Leaf herbivory imposes fitness costs mediated by hummingbird and insect pollinators
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Data from: Herbivory promotes dental disparification and macroevolutionary dynamics in grunters (Teleostei: Terapontidae), a freshwater adaptive radiation
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Data from: Effect of insect herbivory on plant community dynamics under contrasting water availability levels
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Data from: Self-fertilization and herbivory in a rare alpine plant in California, Claytonia megarhiza (Montiaceae)
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Data from: The effect of rhizosphere microbes outweighs host plant genotype in reducing insect herbivory
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Data from: Snail herbivory affects seedling establishment in a temperate forest in the Ozark region
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Data to accompany 'New evidence suggests no sex bias in herbivory or plant defence'
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Data from: Contrasting patterns of insect herbivory and predation pressure across a tropical rainfall gradient
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Does the munch affect the bunch? Using community science to explore insect herbivory and fruit production in an understory plant
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Dynamic effects of insect herbivory and climate on tundra shrub growth: roles of browsing and ramet age
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Effects of insect herbivory on seedling mortality in restored and remnant tropical forest
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LeafByte: A mobile application that measures leaf area and herbivory quickly and accurately
<ol> <li>In both basic and applied studies, quantification of herbivory on foliage is a key metric in characterizing plant-herbivore interactions, which underpin many ecological, evolutionary, and agricultural processes. Current methods of quantifying herbivory are slow or inaccurate. We present LeafByte, a free iOS application for measuring leaf area and herbivory. LeafByte can save data automatically, read and record barcodes, handle both light and dark colored plant tissue, and be used non-destructively. </li> <li>We evaluate its accuracy and efficiency relative to existing herbivory assessment tools.</li> <li>LeafByte has the same accuracy as ImageJ, the field standard, but is 50% faster. Other tools, such as BioLeaf and grid quantification, are quick and accurate, but limited in the information they can provide. Visual estimation is quickest, but it only provides a coarse measure of leaf damage and tends to overestimate herbivory.</li> <li>LeafByte is a quick and accurate means of measuring leaf area and herbivory, making it a useful tool for research in fields such as ecology, entomology, agronomy, and plant science.</li> </ol> <p> </p>
Data from: Risky roots and careful herbivores: Sustained herbivory by a root-feeding herbivore attenuates indirect plant defences
<p><b>Abstract</b></p> <ol> <li>Aboveground plant tissues produce characteristic blends of volatile compounds in response to insect herbivory. These herbivore-induced plant volatiles (HIPVs) function in plant defence and mediate foraging decisions by herbivores and their natural enemies. The ecological roles of HIPVs as foraging cues for different trophic levels highlight an important conflict for herbivores that need to locate suitable host plants while avoiding competition and predation. </li> </ol> <p> </p> <ol> <li>Plant roots also emit HIPVs following herbivory, but our understanding of root-produced volatiles and their ecological functions in soil environments remains limited. Moreover, recent studies have documented the effects of temporal dynamics of plant volatile production on ecological interactions, but little is known about how root HIPVs change throughout herbivory or the resulting ecological implications from such changes. </li> </ol> <p> </p> <ol> <li>In this study, we examined the roles of HIPVs from roots of cucumber plants (<i>Cucumis sativus</i>) as foraging cues for a specialist herbivore, striped cucumber beetle (<i>Acalymma vittatum</i>) and its natural enemies, entomopathogenic nematodes (EPNs). We predicted HIPVs from <i>A. vittatum</i>-damaged roots would attract EPNs, while repelling conspecific larvae that avoid competition, induced plant defences, and increased risk of predation by EPNs. To capture the temporal dynamics of root HIPVs, we determined how HIPV-mediated interactions change over time with sustained herbivory. </li> </ol> <p> </p> <ol> <li>Initially (after 24 h), <i>A. vittatum </i>herbivory on <i>C. sativus</i>, or mechanical wounding, induced greater production of root volatiles. These root HIPVs recruited EPNs and repelled foraging <i>A. vittatum </i>larvae, although larval performance was not affected by prior damage. Sustained (7-day) herbivory by larvae reduced HIPVs to levels indistinguishable from undamaged control roots, while mechanically damaged roots continued to produce higher levels of volatiles. Attenuation of HIPVs impaired indirect defence responses of <i>C. sativus</i> by reducing recruitment of EPNs and deterrence of <i>A. vittatum </i>larvae. </li> </ol> <p> </p> <ol> <li><span>These results suggest that root HIPVs function as honest signals that indicate the presence of herbivores, induction of indirect plant defences, and increased risk of predation by natural enemies. However, some herbivores may overcome this line of plant defence by attenuating production of HIPVs and thus altering the outcomes of subsequent interactions among plants, herbivores, and natural enemies.</span></li> </ol>
The importance of vertebrates in regulating insect herbivory pressure along a gradient of logging intensity in Sabah, Borneo
<b>Description: </b><p>Visual surveys of invertebrates, and seedling survival and leaf herbivory photographs, taken inside and outside experimental vertebrate exclusion cages</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/186"><b>The importance of vertebrates in regulating insect herbivory pressure along a gradient of logging intensity in Sabah, Borneo</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3975973">here</a></p><p><b>Files: </b>This consists of 1 file: EwersExclusionInvertSurveys.xlsx</p><p><b>EwersExclusionInvertSurveys.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Invertebrate surveys</b> (described in worksheet InvertSurveys)</p><p>Description: Visual surveys of invertebrates to ordinal level. Includes counts of invertebrates killed by Cordyceps fungus.</p><p>Number of fields: 54</p><p>Number of data rows: 38</p><p>Fields: </p><ul><li><b>ec5_uuid</b>: Unique record ID generated by EpiCollect (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Treatment</b>: Experimental treatment: control or exclusion (Field type: categorical)</li><li><b>5_Date</b>: Date of observations (Field type: date)</li><li><b>6_Time</b>: Time of observations (Field type: time)</li><li><b>7_Plot_photo</b>: Link to photograph of the plot; photos are held on five.epicollect.net (Field type: comments)</li><li><b>lat_71_GPS_coordinates</b>: Latitude (Field type: numeric)</li><li><b>long_71_GPS_coordinates</b>: Longitude (Field type: numeric)</li><li><b>accuracy_71_GPS_coordinates</b>: Accuracy of GPS coordinates (Field type: numeric)</li><li><b>8_Notes</b>: Observations on state of the experimental exclusion cages (Field type: comments)</li><li><b>Acari</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Annelida</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Araneae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Archaeognatha</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Isoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Blattodea</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Chilopoda</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Chrysomelidae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Curculionidae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Staphylinidae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>ColeopteraAdults</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>ColeopteraLarvae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Collembola</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Dermaptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Diplopoda</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>DipteraAdult</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>DipteraLarvae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Embioptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Ephemeroptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Gastropoda</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Hemiptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Formicidae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Hymenoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Isopoda</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>LepidopteraAdult</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>LepidopteraLarvae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Mantodea</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Myriapoda</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>NeuropteraAdult</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>NeuropteraLarvae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Opiliones</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Orthoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Phasmatodea</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Plecoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Platyhelminthes</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Pseudoscorpiones</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Psocoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Siphonaptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Thysanoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Trichoptera</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Thelyphonida</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>IndetAdult</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>IndetLarvae</b>: Number of individuals inside 4m2 area (Field type: abundance)</li><li><b>Cordyceps</b>: Number of individuals inside 4m2 area (Field type: abundance)</li></ul></li><li><p><b>Seedling surveys</b> (described in worksheet SeedlingSurvey)</p><p>Description: Surveys of seedling status (alive/dead) after approximately one year in the field. Includes naturally germinated and experimentally planted Dipterocarp seedlings. Data also provides links to individual leaf photographs taken for leaf herbivory estimates, but these were never processed.</p><p>Number of fields: 24</p><p>Number of data rows: 275</p><p>Fields: </p><ul><li><b>ec5_uuid</b>: Unique record ID generated by EpiCollect. Should be used to link to plot numbers and sample dates recorded on InvertSurveys worksheet. (Field type: id)</li><li><b>title</b>: Unique record entry ID generated on Epicollect (Field type: id)</li><li><b>44_Planted_or_natura</b>: Was the seedling a naturally occurring one or experimentally planted? (Field type: categorical)</li><li><b>45_Seedling_ID</b>: ID code of the label attached to the seedling (Field type: id)</li><li><b>46_Alive_or_dead</b>: Is the seedling alive or dead? (Field type: categorical)</li><li><b>47_Height_cm</b>: Height of the seedling (Field type: numeric)</li><li><b>48_Diameter_at_groun</b>: Stem diameter of the seedling (Field type: numeric)</li><li><b>51_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>52_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>53_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>54_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>55_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>56_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>57_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>58_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>59_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>60_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>61_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>62_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>63_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>64_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>65_Leaf_number</b>: Leaf number, as written on the bottom of individual leaves (Field type: replicate)</li><li><b>66_Leaf_photo</b>: Link to photo of the leaf. Photos are archived on five.epicollect.net (Field type: comments)</li><li><b>84_Notes</b>: Any issues relating to the experiment (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2018-06-21 to 2018-06-24</p><p><b>Latitudinal extent: </b>4.6815 to 4.6990</p><p><b>Longitudinal extent: </b>117.5396 to 117.5855</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Annelida <br> -  -  Platyhelminthes <br> -  -  Arthropoda <br> -  -  -  Chilopoda <br> -  -  -  Diplopoda <br> -  -  -  Myriapoda <br> -  -  -  Arachnida <br> -  -  -  -  Acari <br> -  -  -  -  Araneae <br> -  -  -  -  Opiliones <br> -  -  -  -  Pseudoscorpiones <br> -  -  -  -  Uropygi <br> -  -  -  -  -  Thelyphonidae <br> -  -  -  Insecta <br> -  -  -  -  Archaeognatha <br> -  -  -  -  Isoptera <br> -  -  -  -  Blattodea <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  Dermaptera <br> -  -  -  -  Diptera <br> -  -  -  -  Diptera <br> -  -  -  -  Embioptera <br> -  -  -  -  Ephemeroptera <br> -  -  -  -  Hemiptera <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Formicidae <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Mantodea <br> -  -  -  -  Neuroptera <br> -  -  -  -  Neuroptera <br> -  -  -  -  Orthoptera <br> -  -  -  -  Phasmida <br> -  -  -  -  Plecoptera <br> -  -  -  -  Psocoptera <br> -  -  -  -  Siphonaptera <br> -  -  -  -  Thysanoptera <br> -  -  -  -  Trichoptera <br> -  -  -  Entognatha <br> -  -  -  -  Collembola <br> -  -  -  Malacostraca <br> -  -  -  -  Isopoda <br> -  -  Arthropoda <br> -  -  -  Chilopoda <br> -  -  -  Diplopoda <br> -  -  -  Myriapoda <br> -  -  -  Arachnida <br> -  -  -  -  Acari <br> -  -  -  -  Araneae <br> -  -  -  -  Opiliones <br> -  -  -  -  Pseudoscorpiones <br> -  -  -  -  Uropygi <br> -  -  -  -  -  Thelyphonidae <br> -  -  -  Insecta <br> -  -  -  -  Archaeognatha <br> -  -  -  -  Isoptera <br> -  -  -  -  Blattodea <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  Coleoptera <br> -  -  -  -  -  Chrysomelidae <br> -  -  -  -  -  Curculionidae <br> -  -  -  -  -  Staphylinidae <br> -  -  -  -  Dermaptera <br> -  -  -  -  Diptera <br> -  -  -  -  Diptera <br> -  -  -  -  Embioptera <br> -  -  -  -  Ephemeroptera <br> -  -  -  -  Hemiptera <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Formicidae <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Lepidoptera <br> -  -  -  -  Mantodea <br> -  -  -  -  Neuroptera <br> -  -  -  -  Neuroptera <br> -  -  -  -  Orthoptera <br> -  -  -  -  Phasmida <br> -  -  -  -  Plecoptera <br> -  -  -  -  Psocoptera <br> -  -  -  -  Siphonaptera <br> -  -  -  -  Thysanoptera <br> -  -  -  -  Trichoptera <br> -  -  -  Entognatha <br> -  -  -  -  Collembola <br> -  -  -  Malacostraca <br> -  -  -  -  Isopoda <br> -  -  Mollusca <br> -  -  -  Gastropoda <br> -  Fungi <br> -  -  Ascomycota <br> -  -  -  Sordariomycetes <br> -  -  -  -  Hypocreales <br> -  -  -  -  -  Cordycipitaceae <br> -  -  -  -  -  -  <i>Cordyceps</i> <br></div><p></p>
Consumer mobility predicts impacts of herbivory across a wave stress gradient
<p>Environmental stress impedes predation and herbivory by limiting the ability of animals to search for and consume prey. We tested the contingency of this relationship on consumer traits, and specifically hypothesized that herbivore mobility relative to the return time of limiting environmental stress would predict consumer effects. We examined how wave-induced water motion affects marine communities via herbivory by highly mobile (fish) versus slow moving (pencil urchin) consumers at two wave-sheltered and two wave-exposed rocky subtidal locations in the Galapagos Islands. The exposed locations experienced 99th percentile flow speeds that were 2-5 times greater than sheltered locations, with mean flow speeds >33 cm/s vs <16 cm/s, 2-7 times higher standing macroalgal cover and 2-3 times lower cover of crustose coralline algae than the sheltered locations. As predicted by the Environmental Stress Hypothesis (ESH), there was a negative relationship between mean flow speed and urchin abundance and herbivory rates on Ulva spp. algal feeding assays. In contrast, the biomass of surgeonfishes (Acanthuridae) and parrotfishes (Labridae- Scarinae) was positively correlated with mean flow speed. Ulva assays were consumed at equal rates by fish at exposed and sheltered locations, indicating continued herbivory even when flow speeds surpassed maximum reported swimming speeds at a rate of 1-2 times per minute. Modeled variation in fish species richness revealed minimal effects of diversity on herbivory rates at flow speeds <40 cm/s, when all species were capable of foraging, and above 120 cm/s, when no species could forage, while increasing diversity maximized herbivory rates at flow speeds of 40 – 120 cm/s. Two-month herbivore exclusion experiments during warm and cool seasons revealed that macroalgal biomass was positively correlated with flow speed. Fish limited macroalgal development by 65-91% at one exposed location but not the second, and by 70% at the two sheltered locations. In contrast, pencil urchins did not affect algal communities at either exposed location, but reduced macroalgae by 87% relative to controls at both sheltered locations. We propose an extension of the ESH that is contingent upon mobility to explain species-specific changes in feeding rates and consumer effects on benthic communities across environmental gradients.</p>
Water stress and insect herbivory interactively reduce crop yield while the insect pollination benefit is conserved
<p>Climate change is predicted to hamper crop production due to precipitation deficits and warmer temperatures inducing both water stress and increasing herbivory due to more abundant insect pests. Consequently, crop yields will be impacted simultaneously by abiotic and biotic stressors. Extensive yield losses due to such climate change stressors might, however, be mitigated by ecosystem services such as insect pollination. We examined the single and combined effects of water stress, insect herbivory and insect pollination on faba bean yield components and above- and belowground plant biomass under realistic field conditions. We used rainout shelters to simulate a scenario in line with climate change projections, with adequate water supply at sowing followed by a long period without precipitation. This induced a gradually increasing water stress, culminating around crop flowering and yield formation. We found that gradually increasing water stress combined with insect herbivory by aphids interactively shaped yield in faba beans. Individually, aphid herbivory reduced yield by 79 % and water stress reduced yield by 52 %. However, the combined effect of water stress and aphid herbivory reduced yield less (84 %) than the sum of the individual stressor effects. In contrast, insect pollination increased yield by 68 % independently of water availability and insect herbivory. Our results suggest that yield losses can be greatly reduced when both water stress and insect herbivory are reduced simultaneously. In contrast, reducing only one stressor has negligible benefits on yield as long as the crop is suffering from the other stressor. We call for further exploration of interactions among ecosystem services and biotic and abiotic stressors that simulate realistic conditions under climate change.</p>
Contrasting effects of land-use changes on herbivory and pollination networks
<ol> <li>Land-use changes, one of the greatest threats to global biodiversity, can cause under-appreciated effects on ecosystems by altering the structures of interspecific interaction networks. These effects have typically been explored by evaluating interaction networks composed of a single type of interaction. Therefore, it remains unclear whether the different types of interaction networks sharing the same species respond to the same land-use changes in a similar manner.</li> <li>To compare the responses of herbivory and pollination networks to land-use changes, we investigated both types of interaction networks in semi-natural grasslands categorized into three types of agricultural land-use (abandoned, extensively managed, and intensively managed) in a Japanese agricultural landscape. We quantified the structures of the interaction networks using several indices (connectance, evenness, diversity, generality, network specialization, and robustness) and compared them among different land-use types. We conducted piecewise SEM to differentiate the direct and indirect effects of land-use changes on the network structures.</li> <li>Although both land-use changes (abandonment and intensification) led to reduced plant and insect species richness, the structures of herbivory and pollination networks showed different responses to the land-use changes. There was a marked contrast in network generality; while herbivore species were less generalized (i.e. having fewer host plant species) in fields with land-use intensification, pollinator species were less generalized in abandoned fields.</li> <li>Furthermore, the mechanisms behind the changes in interaction networks were also different between pollination and herbivory networks. The change in herbivory network generality was induced by the decrease in plant species richness, whereas the change in pollination network generality was mainly induced by the effect independent of changes in species richness and composition, which possibly reflect the less number of flowers in shaded environment.</li> <li>The present study demonstrates that agricultural land-use changes affect herbivory and pollination networks in contrasting ways and suggests the importance of assessing multiple types of interaction networks for biodiversity conservation in plant–insect systems. Our results also highlight the under-appreciated importance of maintaining habitats with an intermediate intensity of land-use.</li> </ol>
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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.