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365 results for “Spatial modeling”

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zenodo12/100

Spatial explicit modeling of the probability of land abandonment in the Spanish Pyrenees

<p>Raster outputs of land abandonment probability and uncertainty&nbsp;over semi-natural grassland communities in the Pyrenees mountain range in Spain.</p>

restrictedNov 2020View details →
zenodo12/100

Database for the manuscript "Improving the predictive skill of a distributed hydrological model by calibration on spatial patterns with multiple satellite datasets"

<p>******************************************************************************************************************************************************<strong>NOTICE: </strong>all datasets and tools provided in this database can and should only be used to reproduce the original experiment for which the database was created. The use of any datasets and tools in this database is subject to third party restrictions. Before copying or using this database for other purposes than reproducing the original experiment for which it was created, please ask for adequate authorisations to the author (Moctar Demb&eacute;l&eacute;, mocdembele@gmail.com), who might additionaly need the authorization of&nbsp; the providers of the&nbsp;data and the tools available in this database. ******************************************************************************************************************************************************</p> <p>This database provides model outputs for the manuscript &#39;Improving the predictive skill of a distributed hydrological model by calibration on spatial patterns with multiple satellite datasets&#39; by Demb&eacute;l&eacute; et al.</p> <p>The content of each folder is as&nbsp;follows:</p> <p>-OF5 contains the model outputs for the model calibration case Q</p> <p>-OF42&nbsp;contains the model outputs for the model calibration case MV-Q</p> <p>-OF46 contains the model outputs for the model calibration case MV-St</p> <p>-OF47 contains the model outputs for the model calibration case MV-Su</p> <p>-OF48 contains the model outputs for the model calibration case MV-Ea</p> <p>-OF49 contains the model outputs for the model calibration case MV</p> <p>-Input contains the data needed to setup and run the model</p> <p>-multiOFanalysis contains the results and the files&nbsp;of the analysis of the model outputs using the MATLAB software.</p> <p>For further information, please contact Moctar Demb&eacute;l&eacute;, mocdembele@gmail.com</p> <p>&nbsp;</p>

restrictedNov 2019View details →
zenodo12/100

Example simulation showing spatial and temporal variations in surface carbon biomass of plankton functional groups during a Spring bloom as shown by a 3D hydrodynamic-biogeochemical model (FVCOM-ERSEM), with and without integration of the mixoplankton paradigm.

<p>The outputs are from simulations from using the FVCOM hydrodynamic model coupled to two different versions of ERSEM &ndash; (i) ERSEM and (ii) ERSEM-PB (the latter includes the implementation of the mixoplankton paradigm through integration of the &#39;Perfect Beast&#39; PB&nbsp;model;&nbsp;Flynn and Mitra 2009 <em>Journal of Plankton Research</em>).</p> <p>The FVCOM domain was configured to represent Lyme Bay: a protected bay on the South Coast of England. This region is an important area for shellfish aquaculture.&nbsp; The&nbsp;domain was configured at 350 m &ndash; 5 km high-resolution, resolving sub-km scale dynamics in the area. A nested modelling&nbsp;approach of increasing model resolution was set up using two model domains. For the coupled hydrodynamic-biogeochemical model, a parent domain of 1.5 km &ndash; 10 km resolution was used to drive Lyme Bay model domain. The atmospheric forcing was provided by a 3-step downscaling of GFS global datasets to reach the 3 km of the final model domain using the Weather Research Forecast (WRF) model. Hydrodynamic boundary conditions are extracted from the European Copernicus Marine System North West European Shelf Forecast system. River flows were extracted from a National scale hydrology model run by the&nbsp;Center for Hydrology and Ecology in the UK. Simulations were initialised at Jan 1<sup>st</sup>&nbsp;2005, and spun up for 3 months prior to the output of the data visualised in these videos.&nbsp; &nbsp;</p> <p>The 6 videos portray spatial and temporal variation of daily averaged surface carbon biomass (&mu;gC L<sup>-1</sup>) during the month of April 2005 for the different plankton functional types (FTs) as follows:</p> <ul> <li>Video 1: all phytoplankton FTs in standard ERSEM grouped together. These thus include diatoms, nano-, pico- and micro- plankton; i.e., these simulations do not discriminate between phytoplankton and constitutive mixoplankton (CM).</li> <li>Video 2: phytoplankton FT in ERSEM-PB now considering only diatoms and picoplankton (i.e., cyanobacteria) only; CM are now included in Video 3 outputs.</li> <li>Video 3: all mixoplankton FTs grouped together in ERSEM-PB. These outputs thus include biomasses of micro-CM, nano-CM and NCM.</li> <li>Video 4: all zooplankton FTs grouped together in standard ERSEM. Thus, these include nanoflagellates, meso- and micro- zooplankton and thus includes the primary producing non-constitutive mixoplankton</li> <li>Video 5: zooplankton FT representing only the heterotrophic nano- and micro- zooplankton in ERSEM-PB.</li> <li>Video 6: spatio-temporal variability between the constitutive and non-constitutive mixoplankton functional groupings within FVCOM-ERSEM-PB.&nbsp;</li> </ul> <p>For further information about the mixoplankton paradigm, please see the following open access publications and references there in:</p> <p>Mitra A, Caron DA, Faure E, Flynn KJ, Leles SG, Hansen PJ, McManus GB, Not F, Gomes HR, Santoferrara L, Stoecker DK, Tillmann U (2023) <strong>The Mixoplankton Database &ndash; diversity of photo-phago-trophic plankton in form, function and distribution across the global ocean</strong>. <em>Journal of Eukaryotic Microbiology</em>, e12972. <a href="https://doi.org/10.1111/jeu.12972">https://doi.org/10.1111/jeu.12972</a></p> <p>Glibert PM, Mitra A (2022) <strong>From webs, loops, shunts, and pumps to microbial multitasking: evolving concepts of marine microbial ecology, the mixoplankton paradigm, and implications for a future ocean</strong>. <em>Limnology and Oceanography</em> 67: 585-597 <a href="https://doi.org.10.1002/lno.12018">https://doi.org.10.1002/lno.12018</a> &nbsp;</p> <p>Mitra A, Irigoien X (2022) <strong>Mixoplankton &ndash; Marine Organisms that break the rules</strong>.&nbsp; EU Researcher. <a href="https://issuu.com/euresearcher/docs/mixitin_eur28_h_res">https://issuu.com/euresearcher/docs/mixitin_eur28_h_res</a> &nbsp;&nbsp;&nbsp;</p> <p>Flynn KJ, Mitra A, Anestis K, Ansch&uuml;tz AA, Calbet A, et al. (2019) <strong>Mixotrophic protists and a new paradigm for marine ecology: where does plankton research go now?</strong> <em>Journal of Plankton Research</em> 41: 375-391 <a href="https://doi.org/10.1093/plankt/fbz026">https://doi.org/10.1093/plankt/fbz026</a></p>

restrictedMar 2023View details →
zenodo12/100

National-Scale Spatial Flood Modeling with an Optimized Deep Learning Approach (case study: Sweden)

<p>National-Scale Spatial Flood Modeling with an Optimized Deep Learning Approach (case study: Sweden)</p>

restrictedcc-by-4.0Mar 2023View details →
zenodo8/100

test "Inviting atomic mechanics to macro-continua: A study of monocrystalline Si using spatial multilevel coarsening model"

<p>Law source data and LAMMPS codes of</p> <p>&quot;Inviting atomic mechanics to macro-continua: A study of monocrystalline Si using spatial multilevel coarsening model&quot;</p>

restrictedMay 2022View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record