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Dataset results
96 results for “dispersion modelling”
Processed receiver function data, dispersion measurement, and shear velocity model (Dharwar)
<p>Processed receiver function data at 1 sample per second, dispersion measurement, and shear velocity model (Dharwar).</p>
Phase-velocity dispersions and Vs model of Tongzhou,Beijing
<p>Phase-velocity dispersions and Vs model of Tongzhou,Beijing, from the paper 'Improved 3D Shallow-Deep Vs Structure in Tongzhou, Beijing (China), Revealed by Dense Array Ambient Noise Tomography'</p>
Dispersion curves and Vs models
<p>Dispersion curves and Vs models from the academic paper titled 'High-Resolution Velocity Structure Surrounding the Bomi Section of Jiali Fault in Eastern Himalayan Syntaxis, Constrained from Multiscale Ambient Noise Tomography'</p>
Modelling long-distance seed dispersal of Spathodea campanulata in the Society Islands
<p>These datasets are related to the paper "Modelling long-distance seed dispersal of the invasive tree <em>Spathodea campanulata</em> in the Society Islands" published in Ecological Applications. We used a 3-D kinematic trajectory model (Computing Atmospheric Trajectory tool (CAT)) initiated from regional wind field data to assess the potential for long-distance seed dispersal (LDD) of a wind-dispersed invasive tree, <em>Spathodea campanulata</em> (African tulip tree) across the Society Islands (French Polynesia, South Pacific Ocean) following its initial planting and spread on the island of Tahiti. The main objective of our study was to determine whether <em>S. campanulata</em> can be expected to spread naturally among islands. Atmospheric dynamics, seed terminal velocity, precipitation, and temperature of air masses were considered to assess the potential for LDD between oceanic islands, with the island of Tahiti serving as the island source for multiple, geographically distant invasions. These datasets contain the number of simulated seed trajectories with Computing Atmospheric Trajectory tool (CAT) in the study area as well as all data corresponding to each figure found in the paper.</p>
Data set for "Spatially explicit ecological modeling improves empirical characterization of dispersal"
<p>Data set used and created in the simulations, analysis and figures of the associated paper.</p>
SAMC Model Inputs from: Predicting dispersal and conflict risk for wolf recolonization in Colorado
<p>The colonization of suitable yet unoccupied habitat due to natural dispersal or human introduction can benefit recovery of threatened species. Predicting habitat suitability and conflict potential of colonization areas can facilitate conservation planning.</p> <p>Planning for reintroduction of gray wolves (Canis lupus) to the U.S. state of Colorado is underway. Assessing which occupancy sites minimize the likelihood of human-wolf conflict during dispersal events and seasonal movements is critical to the success of this initiative.</p> <p>We used a spatial absorbing Markov chain (SAMC) framework, which extends random walk theory and probabilistically accounts for both movement behavior and mortality risk, to compare the viability of potential occupancy sites (public lands >500 km2 to minimally meet wolf pack range area). The SAMC framework produced spatially explicit predictions of wolf dispersal, philopatry, and conflict risk ahead of recolonization prior to reintroduction efforts. Our SAMC model included: 1) movement resistance based on terrain, roads, and housing density; 2) mortality risk and potential conflict (absorption) based on livestock presence, social tolerance, land ownership, and state boundaries; and 3) site fidelity based on habitat quality. Using this model, we compared 21 public land units by deriving predictions of: A) relative survival time outside each site, B) intensity of use and retention time within each site, and C) the probability of use on adjacent public lands. We also predicted and mapped potential conflict hotspots associated with each site.</p> <p>Among the units assessed, a complex of USFS Wilderness areas near Aspen, chiefly the Hunter-Fryingpan and Collegiate Peaks Wilderness areas, had the best overall rankings when comparing predictions of each metric. The area balances high-quality, well-connected habitat with relatively low livestock density and high social tolerance. </p> <p>Synthesis and applications: Our findings highlight the utility of the SAMC framework for assessing colonization areas and the capacity to identify locations for effective proactive management, especially of conflict-prone species. The flexibility of the SAMC framework enables predicting likely areas of philopatry and human-wildlife conflict using spatially-explicit metrics which can improve the success of conservation translocations and management of species with changing geographic extents.</p>
Water modelling used in "On the efficient particle dispersion and transfer in the fabrication of Al-SiCp MMCs"
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Modelling mycorrhizal fungi dispersal by the mycophagous swamp wallaby (Wallabia bicolor)
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Data from: Exploring the interaction of avian frugivory and plant spatial heterogeneity and its effect on seed dispersal kernels using a simulation model
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Model output data for "Negative density-dependent dispersal emerges from the joint evolution of density- and body condition-dependent dispersal strategies"
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SAMC Model Inputs from: Predicting dispersal and conflict risk for wolf recolonization in Colorado
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Data and R Code for publication: Should dispersers be fast learners? Modelling the role of cognition in dispersal
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Data from: Model-based analysis supports interglacial refugia over long-dispersal events in the diversification of two South American cactus species
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Data from: Seeds in motion: genetic assignment and hydrodynamic models demonstrate concordant patterns of seagrass dispersal
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Salmon louse infestation levels on sea trout can be predicted from a hydrodynamic lice dispersal model
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Data from: Statistical comparison of trait-dependent biogeographical models indicates that Podocarpaceae dispersal is influenced by both seed cone traits and geographical distance
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Data from: Discrete choice modelling of natal dispersal: "choosing" where to breed from a finite set of available areas
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Data from: Modelling unbiased dispersal kernels over continuous space by accounting for spatial heterogeneity in marking and observation efforts
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Data from: A model for simulating the active dispersal of juvenile sea turtles with a case study on western Pacific leatherback turtles
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Data from: Understanding age-specific dispersal in fishes through hydrodynamic modelling, genetic simulations and microsatellite DNA analysis
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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.