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96 results for “dispersion modelling”
Model code and outputs of "Modeling the Dispersal of the San Francisco Bay Plume over the Northern and Central California Shelf"
<p>- "model_code.rar" contains the model source code.</p> <p>- "model_grid.nc" contains the grid file.</p> <p>- "model_outputs.nc" contains the model outputs.</p>
3D Vs model and phase velocity dispersion data of the Pearl River Delta onshore-offshore area
<p>3D Vs model and phase velocity dispersion data for PRD.</p>
Supplementary material 1 from: Nunes P, Robinet C, Branco M, Franco JC (2023) Modelling the invasion dynamics of the African citrus psyllid: The role of human-mediated dispersal and urban and peri-urban citrus trees. In: Jactel H, Orazio C, Robinet C, Douma JC, Santini A, Battisti A, Branco M, Seehausen L, Kenis M (Eds) Conceptual and technical innovations to better manage invasions of alien pests and pathogens in forests. NeoBiota 84: 369-396. https://doi.org/10.3897/neobiota.84.91540
Supplementary tables
Data from: Machine learning biogeographic processes from biotic patterns: a new trait-dependent dispersal and diversification model with model choice by simulation-trained discriminant analysis
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Data from: Modelling competition and dispersal in a statistical phylogeographic framework
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Data from: Spatiotemporally explicit demographic modelling supports a joint effect of historical barriers to dispersal and contemporary landscape composition on structuring genomic variation in a red-listed grasshopper
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Parasitism and host dispersal plasticity in an aquatic model system
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Data from: Creating virtual species to test species distribution models: The importance of landscape structure, dispersal and population processes
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Cross-correlation functions, dispersion data, and 3D velocity models of the Chao lake
<p>We obtained a 3-D isotropic and azimuthal anisotropic model beneath the Chao Lake. These datasets contain the cross-correlation functions, dispersion data we picked, and the models we obtained.</p>
Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral
Models of dispersal potential are required to predict connectivity between populations of sessile organisms. However, to date, such models do not allow for time‐varying rates of acquisition and loss of competence to settle and metamorphose, and permit only a limited range of possible survivorship curves. We collect high‐resolution observations of coral larval survival and metamorphosis, and apply a piecewise modeling approach that incorporates a broad range of temporally‐varying rates of mortality and loss of competence. Our analysis identified marked changes in competence loss and mortality rates, whose timing implicates developmental failure and depletion of energy reserves. Asymmetric demographic rates suggest more intermediate‐range dispersal, less local retention, and less long‐distance dispersal than predicted by previously‐employed non‐piecewise models. Because vital rates are likely temporally asymmetric, at least for non‐feeding broadcast‐spawned larvae, piecewise analysis of demographic rates will likely yield more reliable predictions of dispersal potential.
Figure 4 from: Aspöck H, Aspöck U, Gruppe A, Sittenthaler M, Haring E (2017) Anthropogenic dispersal of a snakefly (Insecta, Neuropterida) – a singular phenomenon or a model case in Raphidioptera? Deutsche Entomologische Zeitschrift 64(2): 123-131. https://doi.org/10.3897/dez.64.19859
Figure 4 - Raphidia mediterranea, pupa, from Pelmberg (Upper Austria). Photo H. Bruckner.
Figure 1 from: Aspöck H, Aspöck U, Gruppe A, Sittenthaler M, Haring E (2017) Anthropogenic dispersal of a snakefly (Insecta, Neuropterida) – a singular phenomenon or a model case in Raphidioptera? Deutsche Entomologische Zeitschrift 64(2): 123-131. https://doi.org/10.3897/dez.64.19859
Figure 1 - Raphidia mediterranea, male, from Pelmberg (Upper Austria). Photo H. Bruckner.
Figure 2 from: Aspöck H, Aspöck U, Gruppe A, Sittenthaler M, Haring E (2017) Anthropogenic dispersal of a snakefly (Insecta, Neuropterida) – a singular phenomenon or a model case in Raphidioptera? Deutsche Entomologische Zeitschrift 64(2): 123-131. https://doi.org/10.3897/dez.64.19859
Figure 2 - Raphidia mediterranea, female, from Pelmberg (Upper Austria). Photo H. Bruckner.
Data from: High-frequency sampling and piecewise models reshape dispersal kernels of a common reef coral
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ACTIVATE FLEXible PARTicle (FLEXPART) Dispersion Model Back-trajectories
ACTIVATE-FLEXPART is the FLEXible PARTicle dispersion model back-trajectories ending at the HU-25 Falcon locations. ACTIVATE was a 5-year NASA Earth-Venture Sub-Orbital (EVS-3) field campaign. Marine boundary layer clouds play a critical role in Earth’s energy balance and water cycle. These clouds cover more than 45% of the ocean surface and exert a net cooling effect. The Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project was a five-year project that provides important globally-relevant data about changes in marine boundary layer cloud systems, atmospheric aerosols and multiple feedbacks that warm or cool the climate. ACTIVATE studied the atmosphere over the western North Atlantic and sampled its broad range of aerosol, cloud and meteorological conditions using two aircraft, the UC-12 King Air and HU-25 Falcon. The UC-12 King Air was primarily used for remote sensing measurements while the HU-25 Falcon will contain a comprehensive instrument payload for detailed in-situ measurements of aerosol, cloud properties, and atmospheric state. A few trace gas measurements were also onboard the HU-25 Falcon for the measurements of pollution traces, which will contribute to airmass classification analysis. A total of 150 coordinated flights over the western North Atlantic occurred through 6 deployments from 2020-2022. The ACTIVATE science observing strategy intensively targets the shallow cumulus cloud regime and aims to collect sufficient statistics over a broad range of aerosol and weather conditions which enables robust characterization of aerosol-cloud-meteorology interactions. This strategy was implemented by two nominal flight patterns: Statistical Survey and Process Study. The statistical survey pattern involves close coordination between the remote sensing and in-situ aircraft to conduct near coincident sampling at and below cloud base as well as above and within cloud top. The process study pattern involves extensive vertical profiling to characterize the target cloud and surrounding aerosol and meteorological conditions.
Validation of the atmospheric dispersion model NAME against long-range tracer release experiments
<p>NAME model output files for the CAPTEX and ANATEX experiments.</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.