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1,398 results for “Shallow water”
Summer water chemistry; sediment phosphorus fluxes and sorption capacity; sedimentation and sediment resuspension dynamics; water column thermal structure; and zooplankton, macroinvertebrate, and macrophyte communities in eight shallow lakes in northwest Iowa, USA (2018-2020)
The primary aim of this data product is to characterize change in water chemistry, sediment-water interactions, and biological communities in shallow, eutrophic lakes undergoing a fishery biomanipulation. We studied eight glacial lakes located in northwest Iowa, USA, from 2018 to 2020 during the summer season (May to September). A subset of these lakes (n = 4; Center, Five Island, North Twin, and Silver Lakes) were part of a fishery biomanipulation in which the Iowa Department of Natural Resources (IDNR) incentivized commercial harvest of common carp (Cyprinus carpio) and bigmouth buffalo (Ictiobus cyprinellus). Harvests occurred in Center and Five Island Lakes during 2018-2019 and in North Twin and Silver Lakes during 2019-2020. Between 73 and 373 kg fish biomass per ha were removed each year. The other study lakes (n = 4; Blue, South Twin, Storm, and Swan Lakes) remained unmanipulated during the study period. Over the course of the biomanipulation, we quantified a suite of physical, chemical, and biological parameters across the study lakes. High frequency aquatic sensors were used to measure water column thermal structure, dissolved oxygen concentrations, and algal pigments. Manual water chemistry sampling further quantified suspended solids, total phosphorus and nitrogen, soluble reactive phosphorus, nitrate, and water clarity. We measured flux rates of phosphorus between bottom sediments and the overlying water using ex situ sediment core incubations under both oxic and anoxic conditions. We further quantified sediment phosphorus sorption capacity using equilibrium phosphorus concentration assays. Tiered sediment traps were used to measure sedimentation rates as well as sediment resuspension in bottom waters. We also measured change in zooplankton, macroinvertebrate, and macrophyte community composition and abundance. These data will be used to better understand the mechanisms of internal phosphorus loading in shallow lakes and the ecosystem effects of fisherie
Satellite-based remote sensing of water clarity in the shallow coastal lagoons of Virginia 2013-2021
This dataset contains raw data, analysis products and code for a study of satellite-based estimation of water clarity. The files are: Match-up.csv: In situ Secchi depths collected by the Virginia Coast Reserve Long Term Ecological Research project (VCR LTER), matched with satellite (Landsat-8/Sentinel-2) Secchi depth estimates from 2013-2022 from NASA SeaDAS 8.2. Satellite overpasses occurred +/- 0-1 days within in situ sampling. Valid remote sensing reflectance values (Rrs) from NASA SeaDAS (not masked by quality flags) were recovered at 12 of 17 in situ sampling sites: 6 ocean inlet sites, 2 lagoon site, and 3 mainland tidal creek sites. Therefore, there are 12 in situ sites available for comparison with satellite estimates. compare_L8S2.csv: Satellite data and water clarity estimates from 150 randomly sampled sites across 5 clear day images in the Virginia Coast Reserve, 2021. Satellite data are from Landsat-8 and Sentinel-2 and processed/atmospherically-corrected using NASA SeaDAS 8.2. The Virginia Coast Reserve is a coastal lagoon system located in Virginia, USA, near the southern tip of the Delmarva Peninsula. Due to low nitrogen inputs and frequent exchange with the Atlantic Ocean via inlets between barrier islands, water quality is high relative to many other coastal bays in the United States and worldwide. Spatial_averaging_analysis.csv: Secchi depths at in situ water quality sites at 10 m resolution (Sentinel-2 only), 30 m resolution (Landsat-8 and Sentinel-2), and 90 m resolution (Landsat-8 and Sentinel-2) where there are in situ match-ups. atmocorrect.csv: In situ Secchi depths collected by the Virginia Coast Reserve Long Term Ecological Research project (VCR LTER), matched with satellite (Landsat-8/Sentinel-2) Secchi depth estimates from 2013-2022 from NASA SeaDAS 8.2 and ACOLITE Version 2022022.00. L8_ALL.csv: All Landsat-8 Secchi depth data available between 2013-2021 at in situ water quality sites. S2_ALL.csv: All Sentinel-2 Secchi depth data availab
Summer water chemistry, phytoplankton and zooplankton community composition, size structure, and biomass in a shallow, hypereutrophic reservoir in southwestern Iowa, USA (2019).
This data product contains data for Green Valley Lake, a hypereutrophic reservoir in southwest Iowa (USA) from the summer of 2019. We sampled and quantified zooplankton, phytoplankton, and nutrient concentrations (total N, total P, soluble reactive P, nitrate) in the lake weekly with the primary aim of assessing consumer nutrient cycling, specifically zooplankton nutrient cycling, in a hypereutrophic reservoir. Weekly plankton sampling included quantifying zooplankton and phytoplankton biomass, community composition, and size structure. Phytoplankton size was measured as the greatest axial linear distance which would be approached by a zooplankton grazer. Allometric equations from the literature were applied to the zooplankton size measurements to estimate zooplankton community excretion of N and P. We found that the estimated contribution of zooplankton excretion to the dissolved P pool was substantial in the spring. Further, we found evidence that zooplankton affected phytoplankton size distributions through selective grazing of smaller phytoplankton cells likely affecting nutrient uptake and storage by phytoplankton.
MPAS-Ocean Shallow Water Meshes
<p>The MPAS_Ocean_Shallow_Water_Meshes directory contains planar hexagonal mesh files in NetCDF format necessary for running a verification suite of shallow water test cases for the barotropic solver of ocean models using a mimetic finite volume spatial discretization based on the TRiSK scheme. It also contains mesh plots showing the cell centers, edge centers, vertices, and orientation of the normal vectors at the edges; plots of high resolution meshes superimposed on low resolution ones; plots of state variables interpolated from edges and vertices to cell centers along with the interpolation error; plots of state variables interpolated from a high resolution mesh to a low resolution one; and plots of various spatial operators of the TRiSK scheme applied to the state variables along with their error and convergence plots. The associated code can be cloned from the Github repository <a href="https://github.com/siddharthabishnu/Rotating_Shallow_Water_Verification_Suite.git">Rotating_Shallow_Water_Verification_Suite</a>. Please download the MPAS_Ocean_Shallow_Water_Meshes.zip file, unzip it, and place the resulting directory within the meshes directory of Rotating_Shallow_Water_Verification_Suite.</p>
Rotating Shallow Water Verification Suite Output
<p>The Rotating_Shallow_Water_Verification_Suite_Output directory contains the output obtained by running a verification suite of shallow water test cases for the barotropic solver of ocean models using two types of spatial discretizations: a mimetic finite volume method based on the TRiSK scheme and a discontinuous Galerkin spectral element method (DGSEM); and a variety of time-stepping methods. The associated code can be cloned from the Github repository <a href="https://github.com/siddharthabishnu/Rotating_Shallow_Water_Verification_Suite.git">Rotating_Shallow_Water_Verification_Suite</a>. The output, which is organized into the two directories MPAS_Ocean_Shallow_Water_Output and DGSEM_Rotating_Shallow_Water_Output corresponding to the two spatial discretizations, includes:</p><ul><li>text files containing the exact solution and the numerical error of the various test cases at specific instants of time along with their plots; and </li><li>text files containing the L2 error norm with respect to the exact solution for refinement in both space and time, and the L2 norm of the difference in the numerical solution for refinement only in space and only in time, along with the convergence plots.</li></ul>
Time-lapse electrical resistivity tomography and seismic reflection imaging of a shallow ground-water aquifer (0-50 m): Mississippi River levee seepage across the Duncan Point bar, Baton Rouge, Louisiana, U.S.A.
<p>The electrical resisitivity raw data files are slightly processed to remove bad data points but can be inverted using tomographic inversion code. </p> <p>The seismic data were assembled in Seismic Unix format, a shortened version of the SEG-Y format (Society of Exploration Geophysicists Exchange Format-Y https: //seg. org/Publications/SEG-Technical-Standards), that has the 3200-byte EBCDIC and 400-byte tape header removed. The data uploaded online (<a href="https://zenodo.org/records/14776025">https://zenodo.org/records/14776025</a>) is a CMP brute-stacked seismic section. </p> <p>During data collection, shotpoint location changed proceeding along a 136-degree azimuth (south-easterly direction), and spaced every 1 m.</p> <p>A total of 48, horizontal-component 28-Hz nominal geophones were placed every one meter and shotpoints were located half-way between geophones. Geophones remained fixed at their locations throughout the survey and so the CMP spacing is nominally 0.5-m but fold varies linearly from a value of 1 from either side of the survey to a central maximum of 24. The seismic source consisted of a partially buried 20-lb steel I-beam struck repeatedly on either side three times by an 8-lb sledge hammer. Data of the same striking polarity were added in-phase in the field. Data with opposing polarity at each shotpoint location were subtracted later to enhance SH-wave data and suppress converted SH-to-P waves.</p> <p>Seismic processing is minimal and consists of standard surface-wave muting, elimination of bad seismic traces, normal moveout, bandpass filtering (between 12 Hz and 50 Hz) and preliminary stacking with trace mixing every 3 CMPs. The data were stacked with a single velocity throughout that ranged from 80 m/s (Vs) at 0.2 s, to 100 m/s at 0.35 s and reached 180 m/s at 0.5 s of two-way traveltime.</p> <p> </p>
Supporting Data - Double Ridge Formation over Shallow Water Sills on Jupiter's Moon Europa
<p>This archive contains data produced in support of R. Culberg, D. M. Schroeder, G. Steinbrügge, Double Ridge Formation Over Shallow Water Sills on Jupiter’s Moon Europa, <em>Nature Communications</em>, 2022. This includes the WorldView imagery in Figure 1, the reprocessed radargrams underlying the radar analysis and inversion, and outputs of all inversion and sensitivity test runs. See the README file for a complete description of the files available in this archive.</p>
Simulations of shallow water wave turbulence
<p><strong>About</strong></p> <p>This dataset curates all the simulations used to reproduce the paper:</p> <blockquote> <p><em>Shallow water wave turbulence</em><br> DOI: <a href="https://doi.org/10.1017/jfm.2019.375">10.1017/jfm.2019.375</a></p> </blockquote> <p>The source code and scripts necessary to generate the manuscript are archived at:</p> <blockquote> <p><a href="https://github.com/ashwinvis/augieretal_jfm_2019_shallow_water">https://github.com/ashwinvis/augieretal_jfm_2019_shallow_water</a></p> </blockquote> <p>See the README in the repository above to generate the manuscript</p> <p><strong>Abstract</strong></p> <p>The dynamics of irrotational shallow water wave turbulence forced at large scales and dissipated at small scales is investigated. First, we derive the shallow water analogue of the ‘four-fifths law’ of Kolmogorov turbulence for a third-order structure function involving velocity and displacement increments. Using this relation and assuming that the flow is dominated by shocks, we develop a simple model predicting that the shock amplitude scales as <span class="math-tex">\((\epsilon d)^{1/3}\)</span>, where <span class="math-tex">\( \epsilon\)</span> is the mean dissipation rate and <span class="math-tex">\(d\)</span> the mean distance between the shocks, and that the <span class="math-tex">\(p\)</span><sup>th</sup>-order displacement and velocity structure functions scale as <span class="math-tex">\((\epsilon d)^{p/3} r/d\)</span>, where <span class="math-tex">\(r\)</span> is the separation. Then we carry out a series of forced simulations with resolutions up to 7680<sup>2</sup>, varying the Froude number,<span class="math-tex">\(F_{f} = (\epsilon L_f)^{1/3}/ c \)</span>, where <span class="math-tex">\(L_f\)</span> is the forcing length scale and <span class="math-tex">\(c\)</span> is the wave speed. In all simulations a stationary state is reached in which there is a constant spectral energy flux and equipartition between kinetic and potential energy in the constant flux range. The third-order structure function relation is satisfied with a high degree of accuracy. Mean energy is found to scale approximately as <span class="math-tex">\(E \sim \sqrt{\epsilon L_f c}\)</span>, and is also dependent on resolution, indicating that shallow water wave turbulence does not fit into the paradigm of a Richardson–Kolmogorov cascade. In all simulations shocks develop, displayed as long thin bands of negative divergence in flow visualizations. The mean distance between the shocks is found to scale as <span class="math-tex">\( d \sim F_f^{1/2} L_f\)</span>. Structure functions of second and higher order are found to scale in good agreement with the model. We conclude that in the weak limit, <span class="math-tex">\(F_f \rightarrow 0 \)</span>, shocks will become denser and weaker and finally disappear for a finite Reynolds number. On the other hand, for a given <span class="math-tex">\(F_f\)</span>, no matter how small, shocks will prevail if the Reynolds number is sufficiently large.</p>
Underwater hyperspectral data of shallow water seafloor at Vigo-Rias Biaxas sea zones
<h2>Abstract</h2> <p>Raw hyperspectral data of shallow water seafloor at three different Vigo-Rias Biaxas sea zones from Vigo fieldwork Sept. 2023. The hyperspectral data was recorded by Ecotone UHI (underwater hyperspectral imaging) installed on customized BlueROV 2. The UHI was run about 0.3-2m above the seafloor.</p> <p>This depositry contains data generated within the European S34 project. The data are in raw form and have not been further processed. Processed data are published in other depositories.</p> <h2>Metadata information</h2> <p> </p> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>Underwater hyperspectral data of shallow water seafloor at Vigo-Rias Biaxas sea zones</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>Raw hyperspectral data of shallow water seafloor at three different Vigo-Rias Biaxas sea zones from Vigo fieldwork Sept. 2023. The hyperspectral data was recorded by Ecotone UHI (underwater hyperspectral imaging) installed on customized BlueROV 2. The UHI was run about 0.3-2m above the seafloor.</p> <p>This depositry contains data generated within the European S34 project. The data are in raw form and have not been further processed. Processed data are published in other depositories.</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>Raw hyperspectral data, underwater hyperspectral data, UHI, seafloor, seabed, mineral, sea region, Vigo, Vigo-Rias Biaxas</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Ria de Vigo</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Bio-geographical regions</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>27.09.2023</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Format</p> </td> <td> <p>HDF5</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>2mm (with UHI about 2m away)</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p>3035</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>no</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>no</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p>Ecotone As</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>Ecotone As</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Ecotone As, info@ecotone.com</p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table> <p> </p>
Salinity - water level relationships in shallow lakes: Data
<p>Data consists of water levels and salinity of 159 lakes across southwest Australia, collected as part of the South West Wetlands Monitoring Program (Lane et al., 2017). The data was collected between 1977 and 2019 by staff from the Department of Biodiversity Conservation and Attractions, Western Australia, and its predecessors. </p> <p>Description of files:</p> <p>SiteSummary.xlsx</p> <ul> <li>An Excel file with basic lake descriptions, including names and geographic coordinates. </li> </ul> <p>WaterData.csv</p> <ul> <li>A comma delimited ascii file consisting of a lake identifier, a date of observation, a lake level relative to the deepest bed elevation, the measured salinity (g/L).</li> </ul> <p>Bathymetry.xlsx</p> <ul> <li>An Excel file with bathymetries of a subset of lakes</li> </ul>
Fig. 38 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 38. Fossil lateral arm plates (LAPs) of ophiacanthid brittle stars in external (a) and internal (b) views. 1-4. Ophiojagtus irimurai gen. et sp. nov. from the early Kimmeridgian (Late Jurassic) of the Pointe du Chay, France. 1. GZG.INV.78808 (holotype), proximal LAP. 2. GZG.INV.78809 (paratype), median LAP. 3. GZG.INV.78810 (paratype), median LAP. 4. GZG.INV.78811 (paratype), distal LAP. 5-7. Ophiojagtus acklesi gen. et sp. nov. from the late Aptian (Early Cretaceous) of Wizard Way, Texas. 5. GZG.INV.78814 (holotype), proximal LAP. 6. GZG.INV.78815 (paratype), median to distal LAP. 7. GZG.INV.78816 (paratype), proximal LAP. 8. Ophiojagtus sp. 1 from the early Cenomanian (Late Cretaceous) of Waco, Texas; proximal LAP. 9-10. Ophiojagtus alternatus (Kutscher & Jagt, 2000) comb. nov. from the early late Maastrichtian (Late Cretaceous) of Haccourt, Belgium. 9. NHMM 2012 060, proximal to median LAP. 10. NHMM 2012 061, proximal LAP. One common scale bar per species.
Fig. 31 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 31. Lateral arm plates (LAPs) of fossil and Recent ophiacanthid brittle stars in external (a) and internal (b) views. 1-4. Ishidacantha fuersichi gen. et sp. nov. from the Callovian (Middle Jurassic) of Jumara, India. 1. GZG.INV.78728 (holotype), proximal LAP. 2. GZG.INV.78729 (paratype), proximal LAP. 3. GZG.INV.78730 (paratype), median LAP. 4. GZG.INV.78731 (paratype), distal LAP. 5-6. Ishidacantha trispinosa (Hess, 1965) comb. nov. from the early Oxfordian (Late Jurassic) of Longecombe, France. 5. NHMB M11222, proximal LAP. 6. NHMB M11223, distal LAP. 7-9. Ophiomitrella conferta (Koehler, 1922), Recent. 7. Proximal LAP. 8. median LAP. 9. distal LAP. 10-12. Ophiomitrella? sp. 1 from the Callovian of Bauer-Wehrland, Germany. 10. GZG.INV.78735, proximal LAP. 11. GZG.INV.78736, median LAP. 12. GZG.INV.78737, distal LAP. One common scale bar per species.
Fig. 30 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 30. Fossil lateral arm plates (LAPs) of ophiacanthid brittle stars in external (a) and internal (b) views. 1-3. Dermacantha sp. nov. innom. from the Bajocian-Bathonian boundary of Touert, France. 1. GZG.INV.78714, proximal LAP. 2. GZG.INV.78715, median LAP. 3. GZG.INV.78716, distal LAP. 4-6. Dermacantha carli gen. et sp. nov. from the late Oxfordian (Late Jurassic) of the Plettenberg, Germany. 4. GZG.INV.78718 (holotype), proximal LAP. 5. GZG.INV.78719 (paratype), median LAP. 6. GZG. INV.78720 (paratype), distal LAP. 7-9. Ishidacantha hirokoae gen. et sp. nov. from the middle Toarcian (Early Jurassic) of Le Clapier, France. 7. GZG.INV.78723 (holotype), proximal LAP. 8. GZG.INV.78724 (paratype), median LAP. 9. GZG.INV.78725 (paratype), distal LAP. One common scale bar per species.
Fig. 22 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 22. Lateral arm plates (LAPs) of fossil and Recent ophiacanthid brittle stars in external (a) and internal (b) views. 1-2. Hanshessia sp. from the Callovian (Middle Jurassic) of Jumara, India. 1. GZG. INV.78641, proximal to median LAP. 2. GZG.INV.78642, proximal LAP. 3-4. Ophiocopa spatula Lyman, 1883, Recent. 3. Proximal LAP. 4. Distal LAP. 5. Alternacantha? sp. from the late Pliensbachian (Early Jurassic) of Amellago, Morocco; GZG.INV.78645, proximal LAP. 6. Alternacantha sp. nov. innom. 1 from the middle Toarcian (Early Jurassic) of Le Clapier, France; GZG.INV.78647, proximal to median LAP. 7-8. Alternacantha occulta Thuy & Meyer, 2013, from the early Bajocian (Middle Jurassic) of Longwy, France. 7. GZG.INV.78648, proximal LAP. 8. GZG.INV.78649, distal LAP. 9-10. Alternacantha sp. nov. innom. 2 from the Callovian (Middle Jurassic) of Jumara, India. 9. GZG.INV.78652, proximal to median LAP. 10. GZG.INV.78653, median LAP. One common scale bar per species.
Fig. 26 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 26. Fossil lateral arm plates (LAPs) of ophiacanthid brittle stars in external (a) and internal (b) views. 1-3. Dermocoma faberi sp. nov. from the Hettangian (Early Jurassic) of Vance, Belgium. 1. MnhnL HE408 (holotype), proximal LAP. 2. MnhnL HE409 (paratype), median LAP. 3. MnhnL HE410 (paratype), distal LAP. 4-6. Dermocoma potti sp. nov. from the late Pliensbachian (Early Jurassic) of Feuguerolles, France. 4. GZG.INV.78675 (holotype), proximal LAP. 5. GZG.INV.78676 (paratype), median LAP. 6. GZG. INV.78677 (paratype), distal LAP. 7-8. Dermocoma toarcensis (Hess, 1962) comb. nov. from the late Toarcian (Early Jurassic) of Seewen, Switzerland. 7. NHMB M11216, proximal LAP. 8. NHMB M11217, distal LAP. 9-11. Dermocoma longwyensis sp. nov. from the early Bajocian (Middle Jurassic) of Longwy, France. 9. GZG.INV.78679 (holotype), proximal LAP. 10. GZG.INV.78680 (paratype), median LAP. 11. GZG.INV.78681 (paratype), distal LAP. One common scale bar per species.
Fig. 19 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 19. Fossil skeletal plates of ophiacanthid brittle stars; lateral arm plates (LAPs) in external (a) and internal (b) views. 1-2. Ophiacantha sp. nov. innom 3 from the middle Albian (Early Cretaceous) of Folkestone, Great Britain. 1. GZG.INV.78602, proximal LAP. 2. GZG.INV.78603, distal LAP. 3-5. Ophiacantha reginae sp. nov. from the late Campanian (Late Cretaceous) of Lägerdorf-Alsen, Germany. 3. GZG.INV.78605 (holotype), proximal LAP. 4. GZG.INV.78606 (paratype), median LAP. 5. GZG.INV.78607 (paratype), distal LAP. 6-9. Ophiacantha steffenschneideri sp. nov. from the Rupelian (Oligocene) of Bad Freienwalde, Germany. 6. GZG.INV.78609 (holotype), proximal LAP. 7. GZG.INV.78610 (paratype), median LAP. 8. GZG.INV.78611 (paratype), distal LAP. 9. GZG. INV.78612 (paratype), arm spine. 10-12. Ophiogaleus sp. nov. innom 1 from the late Sinemurian to early Pliensbachian (Early Jurassic) of the Glasenbach Gorge, Austria. 10. NHMW 2012/0137/0017, proximal LAP. 11. NHMW 2012/0137/0018, proximal to median LAP. 12. NHMW 2012/0137/0019, proximal to median LAP. One common scale bar per species except for 9.
Fig. 15 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 15. Fossil lateral arm plates (LAPs) of ophiacanthid brittle stars in external (a) and internal (b) views. 1-3. Geromura teckliformis gen. et sp. nov. from the late Valanginian (Early Cretaceous) of the Ternberg Nappe, Austria. 1. NHMW 2012/0138/0005 (holotype), proximal LAP. 2. NHMW 2012/0138/0006 (paratype), median LAP. 3. NHMW 2012/0138/0007 (paratype), distal LAP. 4-6. Krohcoma mira gen. et sp. nov. from the late Sinemurian to early Pliensbachian (Early Jurassic) of the Glasenbach Gorge, Austria. 4. NHMW 2012/0137/0013 (holotype), proximal LAP. 5. NHMW 2012/0137/0014 (paratype), median LAP. 6. NHMW 2012/0137/0015 (paratype), distal LAP. 7-8. Krohcoma sp. nov. innom from the late Bathonian (Middle Jurassic) of Jumara, India. 7. GZG.INV.78574, proximal LAP. 8. GZG.INV.78575, median to distal LAP. 9-12. Krohcoma ampla gen. et sp. nov. from the early Kimmeridgian of the Pointe du Chay (9-10), France, and the late Kimmeridgian of Trancoso, Portugal (11-12). 9. GZG.INV.78577 (holotype), proximal LAP. 10. GZG.INV.78578 (paratype), median LAP. 11. GZG.INV.78579 (paratype), median LAP. 12. GZG.INV.78580 (paratype), distal LAP. One common scale bar per species is given.
Fig. 13 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 13. Lateral arm plates (LAPs) of fossil and Recent ophiacanthid brittle stars in external (a) and internal (b) views. 1-3. Ophiotoma incredibilis sp. nov. from the latest Aptian to earliest Albian (Early Cretaceous) of Blake Nose, NE Atlantic. 1. GZG.INV.78549 (holotype), proximal LAP. 2. GZG. INV.78550 (paratype), median LAP. 3. GZG.INV.78551 (paratype), distal LAP. 4. Ophiolimna antarctica (Lyman, 1879), Recent, proximal LAP. 5-6. Ophiolimna perfida (Koehler, 1904), Recent. 5. Proximal LAP. 6. distal LAP. 7-8. Ophiolimna tiamatia sp. nov. from the late Sinemurian to early Pliensbachian (Early Jurassic) of the Glasenbach Gorge, Austria. 7. NHMW 2012/0137/0010 (holotype), proximal LAP. 8. NHMW 2012/0137/0011 (paratype), median LAP. 9-12. Ophiolimna malagasica sp. nov. from the Bathonian (Middle Jurassic) of Jumara, India. 9. GZG.INV.78553 (holotype), proximal LAP. 10. GZG.INV.78554 (paratype), median LAP. 11. GZG.INV.78555 (paratype), median LAP. 12. GZG. INV.78556 (paratype), distal LAP. One common scale bar per species is given.
Fig. 34 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 34. Lateral arm plates (LAPs) of fossil and Recent ophiacanthid brittle stars in external (a) and internal (b) views. 1-4. Ophioleviathan watsoni gen. et sp. nov. from the late Sinemurian to early Pliensbachian (Early Jurassic) of the Glasenbach Gorge, Austria. 1. NHMW 2012/0137/0024 (holotype), proximal LAP. 2. NHMW 2012/0137/0025 (paratype), proximal LAP. 3. NHMW 2012/0137/0026 (paratype), median LAP. 4. NHMW 2012/0137/0027 (paratype), distal LAP. 5-7. Manfredura curvata (Kutscher & Jagt, 2000) comb. nov. from the early Maastrichtian (Late Cretaceous) of Rügen, Germany. 5. GZG.INV.78759, proximal LAP. 6. GZG.INV.78760, median LAP. 7. GZG.INV.78761, distal LAP. 8-9. Ophiomitra valida Lyman, 1869, Recent. 8. Proximal LAP. 9. Median LAP. One common scale bar per species.
Fig. 12 in Temporary expansion to shelf depths rather than an onshore-offshore trend: the shallow-water rise and demise of the modern deep-sea brittle star family Ophiacanthidae (Echinodermata: Ophiuroidea)
Fig. 12. Lateral arm plates (LAPs) of fossil and Recent ophiacanthid brittle stars in external (a) and internal (b) views. 1. Ophiotoma assimilis Koehler, 1904, Recent, proximal LAP. 2-3. Ophiotoma megatreta (H.L. Clark, 1911), Recent. 2. Proximal LAP. 3. Median LAP. 4. Ophiotoma sp. nov. innom. from the late Sinemurian to early Pliensbachian (Early Jurassic) of the Glasenbach Gorge, Austria; NHMW 2012/0137/0009, median LAP. 5-7. Ophiotoma vadosa sp. nov. from the early Pliensbachian (Early Jurassic) of Blockley, Great Britain. 5. GZG.INV.78541 (holotype), proximal LAP. 6. GZG.INV.78542 (paratype), median LAP. 7. GZG.INV.78543 (paratype), distal LAP. 8-10. Ophiotoma charlottae sp. nov. from the early Kimmeridgian of the Pointe du Chay, France. 8. GZG.INV.78545 (holotype), proximal LAP. 9. GZG.INV.78546 (paratype), proximal to median LAP. 10. GZG.INV.78547 (paratype), distal LAP. One common scale bar per species is given.
ScienceDex guides
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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.