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113 results for “tree canopy”
Data from: Using Landsat time-series to investigate nearly 50 years of tree canopy cover change across an urban-rural landscape in southern Ontario
<p><strong>Paper Abstract:</strong></p> <p>Canadian urban and adjacent landscapes have been dynamic over the last 50 years due to land management, land cover alternations, climate change, and disturbances. Remote sensing, particularly the Landsat archive, provides the only means to spatially quantify these long-term dynamics locally. Here, we explore the utility of Landsat, including the often-forgotten MSS sensor, for investigating percent tree canopy cover (TCC) change between 1972 and 2020 in a Canadian urban-rural context. We build a TCC time-series by training random forest models using visually interpreted TCC from high-resolution imagery. Predictors include topographic and yearly LandsatLinkr-harmonized and LandTrendr-fitted tasseled cap indices. Yearly binary TCC maps are built to mask consistently treeless areas and limit noise. To increase confidence in observed TCC change without historical reference imagery, we investigate multiple temporal validation options. Our TCC time-series (R2: 0.89, RMSE: 10.7%), quantifies TCC dynamics while limiting erroneous change and predictor space extrapolation. We explore TCC changes across landscapes, revealing periods of gain and loss associated with agricultural reforestation (1978-1996), housing development (on-going), drought (late 1990s), emerald ash borer (2010s), an ice storm (2013), and other drivers. Results demonstrate how long-term Landsat time-series can be used to better understand historical tree canopy change at local-regional scales. </p> <p> </p> <p><strong>Dataset details:</strong></p> <p>See paper. </p> <ul> <li>cc_72to20.tif: Yearly tree CC predictions (1972-2020)</li> <li>always_nonforest10_nowater.tif: continuous-non-canopy mask</li> <li>water.tif: water mask</li> <li>Yearly.zip: Annual predictors (including CC10) and asc outputs</li> </ul> <p> </p> <p>See code on GitHub: <a href="https://github.com/ZZMitch/PredictTreeCC_Landsat_1972to2020">ZZMitch/PredictTreeCC_Landsat_1972to2020: Code from the portion of my PhD about using Landsat time-series to predict tree canopy cover from 1972 - 2020. Code will be released as papers are published. (github.com)</a></p>
Data for: Using spatial patterns of seeds and saplings to assess the prevalence of heterospecific replacements among cloud forest canopy tree species
<p><b>Questions:</b> To gain insights into the role of species-by-species replacements in cloud forest community structuring, we asked: (1) What are the effects of the spatial distribution of standing individuals on the seed rain, soil seed bank, and sapling density and survival in this cloud forest? and (2) What is the prevalence of conspecific vs<i>.</i> heterospecific replacements in the regeneration of this forest?</p> <p><b>Location:</b> Santo Tomás Teipan, Oaxaca State, southern Mexico.</p> <p><b>Methods:</b> In a 1-ha cloud forest plot we assessed seed rain, seed bank, and sapling density and survival of four canopy tree species (<i>Chiranthodendron pentadactylon</i>, <i>Cornus disciflora</i>,<i> Quercus laurina</i>, <i>Oreopanax</i> <i>xalapensis</i>). All standing individuals of these and other tree species (dbh ≥ 2.5 cm) were mapped. We used neighbourhood models to examine the spatial patterns of the three life cycle stages relative to the spatial distribution of adults. The neighbourhood effect was assessed through the Neighbourhood Index, which integrates information on size (dbh) and distance to adults. Data analysis was based on maximum likelihood and model selection procedures.</p> <p><b>Results:</b> We found large between-species differences regarding the spatial patterns of seeds and saplings. Three species showed evidence for the Janzen-Connell effect operating at the seed (<i>C. pentadactylon</i> and <i>Q. laurina</i>) or sapling (<i>O.</i> <i>xalapensis</i>) stage. We also found support for a critical role of specific microsite factors (i.e., niche differentiation) in the regeneration of two species (<i>C. pentadactylon</i> and <i>C. disciflora</i>).</p> <p><b>Conclusions:</b> Seed and sapling distribution patterns suggest the prevalence of heterospecific replacements, and that both Janzen-Connell and niche differentiation effects contribute to this pattern. Our results largely support the notion that the prevalence of heterospecific replacements among canopy species promotes species coexistence in cloud forest.</p>
Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
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Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
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Data for: Using spatial patterns of seeds and saplings to assess the prevalence of heterospecific replacements among cloud forest canopy tree species
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Canopy gaps facilitate upslope shifts in montane conifers but not in temperate deciduous trees in the Northeastern United States
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Non-native weed reaches community dominance under the canopy of native tree
Whether facilitation from native plants is strong enough to trigger community dominance by non-natives remains unclear. We explored the possibility that facilitation from Prosopis caldenia, the dominant native tree in the semiarid open forest of central Argentina, drives local community dominance by Chenopodium album, an annual herb native to Europe. We assessed this hypothesis by conducting extensive field sampling in which we recorded the relative abundance of species growing under the canopy of P. caldenia (caldén microsites) and in adjacent locations free of this tree (open microsites). If our hypothesis is correct, then the relative abundance of C. album will be greater than that of the rest of the species only when growing under P. caldenia. Also, we measured C. album performance, estimated its soil seed bank, and characterized growing conditions in caldén and open microsites. We found that the relative abundance of C. album was over seven times greater than that of any other species in communities occurring in caldén microsites; by contrast, C. album co-dominated communities with several other species in the open. Chenopodium album density, cover, biomass, and fecundity were all several times greater in caldén than open microsites. Similarly, C. album seed bank displayed an eight-fold increase in caldén as compared to open microsites. Growing conditions were markedly different between microsites, which could explain positive responses from C. album. Our results suggest that facilitation from natives is indeed strong enough to trigger local community dominance by non-natives, advancing the understanding of community-level consequences of this interaction.
Tree census, demography, and exposed canopy area data at the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrological Laboratory, Otto, NC from 1993 to 2016
The five Terrestrial Gradient sites were established in the early 1990s as part of the 1990 Coweeta LTER Renewal. The original terrestrial gradient sites were 20 x 40-m. In the late 1990s the plots were expanded to 80 x 80-m and later (around 1998) they were slope-corrected by Clark's lab using survey equipment. Much of the Coweeta LTER “core” datasets have been collected from the gradient plots. This study is one of the long-term studies that are ongoing with defined sampling intervals. The tree demography and census study consists of trees census every two years and seeds collected ~5 x each year.
A drone carrying DAPSI above the canopy of birch trees in Gosau, Upper Austria.
<p>A drone carrying DAPSI above the canopy of birch trees in Gosau, Upper Austria.</p>
Lianas explore the forest canopy more effectively than trees under drier conditions
<p>Lianas rely on trees for support and access to high light positions in the forest canopy, but the implications for how lianas explore the canopy compared to trees remain understudied. We present an in situ forest canopy study to test the hypotheses that: (1) lianas favour leaf display over stem investment compared to trees and (2) lianas have greater potential to colonize non-shaded, high-light areas effectively than trees.</p> <p>We compared branches of 16 liana species with those of 16 sympatric tree species in two lowland tropical forest canopies in Panama using 40-50 m tall canopy cranes. One forest was relatively dry and seasonal in rainfall and in associated light availability. The other forest was relatively wet and evergreen.</p> <p>We observed that lianas were more efficient in leaf display over stem investment than trees, particularly in the forest with lower precipitation and stronger seasonality. Specifically, lianas had a lower LMA (leaf mass per unit leaf area), stronger apical dominance, higher stem slenderness and fewer leaf layers than trees. In the forest with higher precipitation and weaker seasonality, lianas also had stronger apical control and fewer leaf layers than trees, but both lianas and trees were relatively similar in LMA and stem slenderness.</p> <p>Our study shows that lianas more effectively explore the canopy than trees under drier conditions, but much less so under wetter conditions. We argue that lianas display a functional strategy that allow them to better intercept light than the tree species in forests with low precipitation and strong seasonality, while they are constrained to display such strategy at high precipitation – light-limited – sites.</p>
Lausanne tree canopy
<p>Tree canopy map of Lausanne at the 1m resolution obtained with <a href="https://github.com/martibosch/detectree">DetecTree</a> [1] from <a href="https://shop.swisstopo.admin.ch/en/products/images/ortho_images">SWISSIMAGE 2016</a>.</p> <p><strong>Citation</strong></p> <p>If you use this dataset, the source, i.e., SWISSIMAGE 2016 <em>must</em> be acknowledged. Additionally, a citation to DetecTree would certainly be appreciated. Note that DetecTree is based on the methods of Yang et al. [2], therefore it seems fair to reference their work too. An example citation in an academic paper might read as follows:</p> <blockquote> <p>The tree canopy dataset for the agglomeration of Lausanne has been obtained from the SWISSIMAGE 2016 aerial imagery dataset with the Python library DetecTree (Bosch, 2020), which is based on the approach of Yang et al. (2009).</p> </blockquote> <p><strong>Technical specifications</strong></p> <ul> <li><strong>Source</strong>: <a href="https://shop.swisstopo.admin.ch/en/products/images/ortho_images">SWISSIMAGE 2016</a></li> <li><strong>CRS</strong>: CH1903+/LV95 – Swiss CH1903+/LV95 (<a href="https://epsg.io/2056">EPSG:2056</a>)</li> <li><strong>Resolution</strong>: 1m</li> <li><strong>Extent</strong>: From file <a href="https://github.com/martibosch/lausanne-tree-canopy/blob/master/data/raw/agglom-extent.shp">agglom-extent.shp</a>. Obtained with the <a href="https://github.com/martibosch/urban-footprinter">Urban footprinter</a>. See the <a href="https://github.com/martibosch/lausanne-agglom-extent">lausanne-agglom-extent</a> repository for more details.</li> <li><strong>Method</strong>: supervised learning (AdaBoost) with 4 classifiers on manually-generated ground truth masks for 7 training tiles (out of a total 499 tiles) of 512x512 pixels. See Yang et al. [2] for more details.</li> <li><strong>Accuracy</strong>: 91.75%, estimated from <a href="https://github.com/martibosch/lausanne-tree-canopy/blob/master/data/interim/validation-tiles/tile_16384-2560.tif">a manually-generated ground truth mask for 1 tile of 512x512 pixels</a>.</li> </ul> <p><strong>Acknowledgements</strong></p> <ul> <li>With the support of the École Polytechnique Fédérale de Lausanne (EPFL)</li> </ul> <p><strong>References</strong></p> <ol> <li> <p>Bosch, M. (2020). Detectree: Tree detection from aerial imagery in Python. Journal of Open Source Software (under review).</p> </li> <li> <p>Yang, L., Wu, X., Praun, E., & Ma, X. (2009). Tree detection from aerial imagery. In Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (pp. 131-137). ACM.</p> </li> </ol>
Differences in architecture and performance between two sub-canopy congeneric tropical tree species
<p>We report architectural divergence between two congeneric tropical tree species coexisting in the same stratum which suggests different strategies: reducing self-shading and support costs, or maximizing light foraging. We found species-specific differential performance across light environments, suggesting that architectural differentiation could facilitate the coexistence of species with similar vertical habitat.</p>
Predicting medicinal phytochemicals of Moringa oleifera using hyperspectral reflectance of tree canopies
<p>Research article: <a href="https://doi.org/10.1080/01431161.2021.1887541">https://doi.org/10.1080/01431161.2021.1887541</a></p><p>New technique for processing hyperspectral data: 1)https://www.researchgate.net/publication/349663204_Computer_vision_and_hyperspectral_imagery_in_orchards_and_in_fields_Data_processing_and_analysis_methods</p><p>2)https://www.researchgate.net/profile/Vjacheslav-Fisenko/publication/349663204/figure/fig13/AS:1139984849485825@1648804976658/3-D-visualization-of-reflectance-spectra-of-four-medicinal-plant-genotypesPredicting_W640.jpg</p>
Tree canopy accession strategy changes along the latitudinal gradient of temperate Northeast Asia
<p>Aim: Understanding how natural forest disturbances control tree regeneration is key to predict the consequences of globally accelerating forest diebacks on carbon stocks and forest biodiversity. Tropical cyclones (TCs) are important drivers of forest dynamics in Eastern Asia and it is predicted that their importance will increase. However, little is known about TC impact on forest regeneration.</p> <p>Location: Latitudinal gradient from south Korea (33°N) to the Russian Far East (45°N).</p> <p>Time period: Last 300 years.</p> <p>Major taxa studied: <i>Quercus mongolica</i>, <i>Abies nephrolepis</i> and <i>Pinus koraiensis</i>.</p> <p>Methods: We explore the effects of TC activity on canopy accession strategies derived from long-term tree radial growth patterns along a 1500-km latitudinal gradient of decreasing TC activity. We analyzed canopy accession strategies for more than 800 trees of three widely distributed tree species by dividing them into gap trees (GTs) that established immediately after gap formation, and released trees (RTs) that accessed the upper canopy after a period of competitive suppression.</p> <p>Results: We found a substantial decrease in GTs and increase in RTs proportionally along the gradient of decreasing TC activity. <i>P. koraiensis</i> and <i>A. nephrolepis</i> exhibited high variability in the proportions of the individual canopy accession strategies along the latitudinal gradient, while it was more stable for <i>Q. mongolica</i>. We identified the gradient of TC activity as the main driver influencing canopy dynamics and thus changes in life history traits for <i>P. koraiensis</i> and <i>Q. mongolica</i>, while maximal growth rate was the main driver for <i>A. nephrolepis</i>.</p> <p>Main conclusions: Flexibility in growth strategies enabled the studied species to cover extensive areas and indicates that they will be able to cope with shifts in disturbance regimes induced by the poleward migration of TCs and increasing TC intensity. Our results highlight the canopy accession strategy as an ecological indicator of past disturbance activity.</p>
Vapour pressure deficit is the main driver of tree canopy conductance across biomes
<p>Datasets related to <a href="https://github.com/vflo/drivers_importance">https://github.com/vflo/drivers_importance</a></p> <p>All the data contained in the folder have been generated by Victor Flo and are necessary for the preparation of the results of the study Vapour pressure deficit is the main driver of tree canopy conductance across biomes. The authors of which are Victor Flo, Jordi Martínez-Vilalta, Víctor Granda, Maurizio Mencuccini and Rafael Poyatos.</p>
Code for data analysis - intra-community variability of leaf-out in temperate tree canopies
<p>The code and data were used for producing the results of "Phenology across scales: an intercontinental analysis of leaf-out dates in temperate deciduous tree communities", by Delpierre et al.</p>
Unique Property Reference Number (UPRN) indicator: Tree canopy coverage (UPRN_3_1)
<p>This is an indicator with the tree canopy coverage for various distances (15m, 25m, 150m, 300m and 500m) from Unique Property Refence Numbers (UPRNs) in the Office for National Statistics (ONS) UPRN directory v2024.07 (Epoch 111). This metric is based on <em>Bluesky’s National Tree Map™,</em> which is the only tree dataset to include trees in Great Britain and the Republic of Ireland that are 3 metres and taller.</p> <h3>Available files</h3> <ul> <li><strong>UPRN_3_1_tree_canopy_coverage_cm_with_coords.csv</strong>: covers the Cheshire and Merseyside region (England) and includes latitude and longitude for each UPRN.</li> <li><strong>UPRN_3_1_tree_canopy_coverage_cm.csv</strong>: covers the Cheshire and Merseyside region (England).</li> <li><strong>UPRN_3_1_tree_canopy_coverage_lothian_with_coords.csv</strong>: covers the Lothian region (Scotland) and includes latitude and longitude for each UPRN.</li> <li><strong>UPRN_3_1_tree_canopy_coverage_lothian.csv</strong>: covers the Cheshire and Merseyside region (England).</li> </ul> <p> </p> <h3>Fields</h3> <table> <tbody> <tr> <td> <p><strong>Column name</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>UPRN</p> </td> <td> <p>Unique Property Reference Number as per the Office for National Statistics UPRN Directory (ONSUD) v2024.07 (Epoch 111).</p> </td> </tr> <tr> <td> <p>n_trees_15m</p> </td> <td> <p>Number of trees (above 3m) within 15m from the UPRN.</p> </td> </tr> <tr> <td> <p>tree_canopy_cover_15m</p> </td> <td> <p>Percentage of area covered by tree canopy within 15m from the UPRN. From a maximum area of approximately 707m<sup>2</sup>.</p> </td> </tr> <tr> <td> <p>n_trees_25m</p> </td> <td> <p>Number of trees (above 3m) within 25m from the UPRN.</p> </td> </tr> <tr> <td> <p>tree_canopy_cover_25m</p> </td> <td> <p>Percentage of area covered by tree canopy within 25m from the UPRN. From a maximum area of approximately 1963m<sup>2</sup>.</p> </td> </tr> <tr> <td> <p>n_trees_150m</p> </td> <td> <p>Number of trees (above 3m) within 150m from the UPRN.</p> </td> </tr> <tr> <td> <p>tree_canopy_cover_150m</p> </td> <td> <p>Percentage of area covered by tree canopy within 150m from the UPRN. From a maximum area of approximately 70686m<sup>2</sup>.</p> </td> </tr> <tr> <td> <p>n_trees_300m</p> </td> <td> <p>Number of trees (above 3m) within 300m from the UPRN.</p> </td> </tr> <tr> <td> <p>tree_canopy_cover_300m</p> </td> <td> <p>Percentage of area covered by tree canopy within 300m from the UPRN. From a maximum area of approximately 282743m<sup>2</sup>.</p> </td> </tr> <tr> <td> <p>n_trees_500m</p> </td> <td> <p>Number of trees (above 3m) within 500m from the UPRN.</p> </td> </tr> <tr> <td> <p>tree_canopy_cover_500m</p> </td> <td> <p>Percentage of area covered by tree canopy within 500m from the UPRN. From a maximum area of approximately 785398m<sup>2</sup>.</p> </td> </tr> <tr> <td> <p>latitude (only version with coordinates)</p> </td> <td> <p>Latitude of the UPRN, given in decimal degrees, where N is positive and S is negative.</p> </td> </tr> <tr> <td> <p>longitude (only version with coordinates)</p> </td> <td> <p>Longitude of the UPRN, given in decimal degrees, where E is positive and W is negative.</p> </td> </tr> </tbody> </table> <p> </p> <h3><strong>Regions</strong></h3> <p><strong>Cheshire and Merseyside (Endgland)</strong></p> <p>Includes the following local authorities:</p> <ul> <li>Cheshire East</li> <li>Cheshire West and Chester</li> <li>Halton</li> <li>Knowsley</li> <li>Liverpool</li> <li>Sefton</li> <li>St. Helens</li> <li>Warrington</li> <li>Wirral</li> </ul> <p> </p> <p><strong>Lothian (Scotland)</strong></p> <p>Includes the following local authorities:</p> <ul> <li>East Lothian</li> <li>City of Edinburgh</li> <li>Midlothian</li> <li>Westlothian</li> </ul> <p> </p>
Data for: Characterizing individual tree-level snags using airborne lidar-derived forest canopy gaps within closed-canopy conifer forests
<p><span>1. Airborne lidar is often used to calculate forest metrics about trees but it may also provide a wealth of information about the space between trees. Forest canopy gaps are defined by the absence of vegetative structure and serve important roles for wildlife, such as facilitating animal movement. Forest canopy gaps also occur around snags, keystone structures that provide important substrates to wildlife species for breeding, roosting, and foraging.</span></p> <p><span>2. We wanted to test a method for quantifying canopy gaps around individual snags and live trees, with the working hypothesis that snags would have more gaps surrounding them overall than live trees. We evaluated canopy gaps around individual snags (n=270) and live trees (n=2186) and evaluated correlations between canopy structure and snag occurrence in dense conifer stands of the Idaho Panhandle National Forest, USA. We paired airborne lidar with ground reference data collected at fixed-radius plots (n=53) to evaluate local gap structure. The R package ForestGapR was used to quantify canopy gaps throughout the canopy to determine where the differences were greatest. A canopy space profile was created for each tree by mapping gaps (a) vertically every 2 m in height (2–50 m above ground), and (b) horizontally across small (16 m<sup>2</sup>), medium (36 m<sup>2</sup>), and large (64 m<sup>2</sup>) footprint sizes.</span></p> <p><span>3. Our results suggest this method is robust for quantifying canopy gaps around individual trees. The canopy space profiles were distinctly different for snags and live trees, with more canopy gaps within the area surrounding snags relative to live trees. The greatest differences occurred at mid-canopy heights (~20 m above ground) and at the smallest footprint size (16 m<sup>2</sup>).</span></p> <p><span>4. These results show potential to improve understanding of gap dynamics in closed-canopy conifer forests, and we suggest snag modeling could be improved by incorporating lidar-derived canopy gap analyses alongside existing methodologies.</span></p>
Canopy cover and ecological restoration increase natural regeneration of rainforest trees in the Western Ghats, India
<p>Restoration of canopy cover through tree planting can assist in overcoming barriers to natural regeneration and catalyze recovery of degraded tropical forests. India has made international pledges to restore millions of hectares of degraded forests by 2030, but lacks empirical research on regeneration under different types of planted and natural overstories to guide this mission. We conducted a field study (65 plots of 25 m<sup>2</sup>) to examine the influence of overstory type and canopy cover on naturally regenerating tree seedlings across degraded rainforests (DR), mixed-native species ecological restoration sites (ER), monoculture eucalypt plantations (MP), and mature "benchmark" rainforests (BR) in the Western Ghats mountains of peninsular India. ER had higher native tree seedling densities and recovered community composition towards BR levels compared to DR, while communities in MP shifted in the opposite direction. Densities of native late-successional species increased with canopy cover (particularly in ER), but greater canopy cover was also associated with increases in alien species, a few of which are shade-tolerant. Further, in a nursery experiment comprising four rainforest species, seed germination and early survival increased with shade, but did not vary across soils originating from DR, ER, and MP. Our findings show that while improving canopy cover is important, doing so by planting diverse native species, and controlling invasive alien species, can benefit rainforest recovery in degraded rainforest fragments. Conversely, planting non-native monocultures in degraded forests, which is a prevalent practice in India, could prove counterproductive for forest recovery in the long term.</p>
Large leaf hydraulic safety margins limit the risk of drought-induced leaf hydraulic dysfunction in Neotropical rainforest canopy tree species
<p>The sequence of key water potential thresholds from the onset of water stress to mortality, and the timing of stomatal closure with regard to leaf xylem embolism formation are essential to characterizing plant adaptive strategies to drought. This constitutes a critical knowledge gap for tropical rainforest species, which may be less vulnerable to drought than previously thought.</p> <p>We recorded key leaf and stem water potential thresholds, leaf hydraulic safety margins (HSMleaf), leaf stomatal safety margins (SSMleaf) and estimated native embolism levels during a normal-intensity dry season across 18 Neotropical rainforest tree species. We also solved a sequence of key water potential thresholds. Additionally, we provide a cross-biome analysis of SSMleaf encompassing 97 species from four major biomes based on a literature survey.</p> <p>In the studied rainforest species, leaf turgor loss point, used as a surrogate for stomatal closure, typically occurred before the onset of leaf xylem embolism. Most species exhibited positive HSMleaf and SSMleaf, with contrasting values across species and nearly absent embolism levels during the dry season irrespective of the experienced midday leaf water potentials. Our results point out that leaf xylem embolism is not routine for Neotropical rainforest tree species.</p> <p>Based on our proposal of the water potential sequence for tropical rainforest trees, we argue that leaf xylem embolism is a rare event for these species. This was supported by the literature survey, indicating that across biomes, most woody species have rather large SSM<sub>leaf</sub> and that leaves of tropical rainforest trees are not necessarily more vulnerable than in other biomes. However, we found evidence that some tropical rainforest species may be more vulnerable than others to ongoing climate change. Our data provide an opportunity to parametrize tree-based or land-surface models for tropical rainforests.</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.