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1,572 results for “sediments”
Effect of sediment suspensions on seawater conductivity measurements
<p>Data are in small files recorded in April 2015 and March 2016 during experiments made in Shom's metrology laboratory. A 2 liter cylindrical container, immersed in a calibration bath, was filed with seawaters of practical salinities 35 or 38, and stabilized in temperature at 10 °C to better than 1 mK. 10 °C was choosen to avoid seawater evaporation during measurements. Measurements were made with a calibrated CTD recorder SBE 37 placed in the cylindrical container and a reference temperature probe SBE 35 placed in the calibration bath. Sand or sediments were added progressively in the container and mixed with a stirring propeller. After each increase in sand concentration, a file was recorded. Measurements were made at concentrations: 0, 50, 100, 200, 300, 500, 700, 900, 1100, 2000, 3000 and 5000 mg/l.<br> The sand comes from Plouneour-Trez beach in Brittany, France, 48° 39′ North, 4° 19′ West. The sediments come from muds taken in the Abers Benoit (Treglonou) and Le Faou bays (France) located respectively at 48° 33′ North, 4° 32′ West and 48° 17′ 36″ North, 4° 10′ 39″ West.</p>
Assessing suspended sediment fluxes with acoustic doppler current profilers: case study from large rivers in Russia
<p>The dataset contains measurements of water discharge by Teledyne RDInstruments RioGrande WorkHorse ADCP unit with a working frequency of 600kHz mounted on a moving boat in 6 areas over large rivers of Russia. The dataset comprises the four largest Arctic Siberian rivers and included continuous ADCP measurements done in 2018-2020 at constant crossection at each river located upper from the impact of recipient seas (tides, surges) near the cities of Salekhard (Ob River), Igarka (Yenisey River), Zhigansk (Lena river) and Chersky (Kolyma River). Another area includes ADCP measurements over 20 transects (named S1…S26, fig. 2) in the lower 200 km of the river Selenga on 27-31July 2018. Additionally, the dataset contains ADCP measurements at 38 points along the Moskva River (named M1, M2…) and 17 tributaries (named T01, T02…) done during 2019-2020.</p> <p>This is a supporting material to a manuscript submitted to «Big Earth Data» journal</p>
Data_Sediment accumulation rates and carbonate fluxes of deep-sea sediments in the southern Gulf of Mexico
<p>We present the mass and carbonate annual fluxes, collected by two sediment traps at 1000 m depth, located in the western and southern deep-water region of the Gulf of Mexico, and the total mass and carbonate accumulation rates from 48 sediment cores retrieved from continental slopes and the abyssal plain of the southern Gulf of Mexico (sGM). We also presented the conventional and calibrated radiocarbon age analyzed in planktic foraminifera (> 250 μm size fraction) in sediment cores from the southern Gulf of Mexico, collected in the XIXIMI-7 cruise (May 2019).</p>
Permafrost-thaw lake development in Central Yakutia: sedimentary ancient DNA and element analyses from a Holocene sediment record
<p>In Central Yakutia (Siberia) livelihoods of local communities depend on alaas (thermokarst depression) landscapes and the lakes within. Development and dynamics of these alaas lakes are closely connected to climate change, permafrost thawing, catchment conditions, and land use. To reconstruct lake development throughout the Holocene we analyze sedimentary ancient DNA (sedaDNA) and biogeochemistry from a sediment core from Lake Satagay, spanning the last c. 10,800 calibrated years before present (cal yrs BP). SedaDNA of diatoms and macrophytes and microfossil diatom analysis reveal lake formation earlier than 10,700 cal yrs BP. The sedaDNA approach detected 42 amplicon sequence variants (ASVs) of diatom taxa, one ASV of Eustigmatophyceae (Nannochloropsis), and 12 ASVs of macrophytes. We relate diatom and macrophyte community changes to climate-driven shifts in water level and mineral and organic input, which result in variable water conductivity, in-lake productivity, and sediment deposition. We detect a higher lake level and water conductivity in the Early Holocene (c. 10,700–7000 cal yrs BP) compared to other periods, supported by the dominance of Stephanodiscus sp. and Stuckenia pectinata. Further climate warming towards the Mid-Holocene (7000–4700 cal yrs BP) led to a shallowing of Lake Satagay, an increase of the submerged macrophyte Ceratophyllum, and a decline of planktonic diatoms. In the Late Holocene (c. 4700 cal yrs BP–present) stable shallow water conditions are confirmed by small fragilarioid and staurosiroid diatoms dominating the lake. Lake Satagay has not yet reached the final stage of alaas development, but satellite imagery shows an intensification of anthropogenic land use, which in combination with future warming will likely result in a rapid desiccation of the lake.</p>
Observed and Predicted Bulk Sediment Uranium Isotope Composition (δ234U) for ODP 1094 Over the Last 500 kyr
<p>This is supplementary data associated with a manuscript entitled "Anomalous 234U/238U Isotopic Composition in Southern Ocean Sediments" by N. Redmond, C. T. Hayes, S. K. Glasscock, E. Rohde, R. F. Anderson, and D. McGee</p> <p><br> Variables<br> Sample ID - Section of ODP 1094 core. Hole-Core-Section-Depth(cms)<br> MCD_TOP - Meters Composite Depth at the top of the section<br> Age (Hasenfratz et al., 19) - in kyrs, based on tuning of benthic δ18O to LR04 stack<br> U-238 - Concentration of 238U in bulk sediment, units in ppm or micrograms/gram.<br> aU - Authigenic uranium concentration, calculated from removing th-based detrital U fraction from bulk 238U, units in ppm or micrograms/gram<br> δ234U Observed - Uranium isotope composition observed in bulk sediment, written as the per mil deviation from secular equilibrium, units in ppm or micrograms/gram<br> δ234U Observed Error - Uncertainty Uranium isotope composition observed in bulk sediment, written as the per mil deviation from secular equilibrium, units in ppm or micrograms/gram<br> δ234U Modeled - Uranium isotope composition predicted in bulk sediment by a mixing model of authigenic and detrital U, decayed with age to match observed data, written as the per mil deviation from secular equilibrium, units in ppm or micrograms/gram<br> δ234U Modeled Error - Uncertainty of Uranium isotope composition predicted in bulk sediment by a mixing model of authigenic and detrital U, decayed with age to match observed data, written as the per mil deviation from secular equilibrium, units in ppm or micrograms/gram</p> <p> </p>
The research of River Morphology transition and Sediment variation: Shule River, Northwest of China
<p>The data acquisition in this study is mainly divided into two parts: indoor statistics and field measurements to obtain. In the indoor work, satellite image data and radar digital elevation data were primarily used to measure and count the river width (Fig.1c), sinuosity, gradient, and elevation every 500m along the top of the Shule River downward (Tab.1). The river width was calculated as the distance between the outer banks, measured at a 90° angle to the river axis, including the channel bar and point bar (Mcglue et al., 2016). The classification of river morphology is mainly based on the size of sinuosity (Rust, 1978). The sinuosity greater than 1.5 is defined as a meandering river, and less than 1.5 is defined as a braided river (Fig.1c). The river gradient is counted for every two adjacent measurement points. According to the above measurement criteria, there are 237 river morphology data within the alluvial fan of the Shule River (Tab.1).</p> <p>In the field measurement process, due to the limited accuracy of satellite images in portraying river morphology. We also use UAV aerial photography to refine further the river's morphological characteristics based on satellite images, which mainly included the channel bar and point bar description. Under the guidance of sedimentological theory, we measured and sampled the gravel in the modern riverbed of Shule River (Fig.2). By measuring the grain size and orientation parameters of gravel(Fig.2a), we research the refinement characteristics of sediments from the apex to the toe (Folk, 1954). Among them, gravel grain size and orientation were measured by the quantitative characterization method of gravel orientation proposed by Huang YuanGuang et al. (Fig.2a, b), and grain size was determined by the long flat axis of gravels (Huang et al., 2018), gravel orientation was measured by the rose diagram of the relative apparent dip (Fig.2b) (Huang et al., 2018; Tao et al., 2018). A total of five gravel statistical points were included within the alluvial fan of the Shule River, and a total of 1862 gravel grain size parameters were measured (Tab.2). We also use the hand-hold X-ray fluorescence spectrometer to measure the element characteristics of each sampling point (Fig.2c, d; Tab.3), which uses intelligent one-button testing and intelligent judgment functions for elements between atomic numbers 12-92 (Mg-U) (Fig.2e; Tab.3).</p>
Insight into the Mechanical Coupling Behavior of Loose Sediment and Embedded Fiber-optic Cable using Discrete Element Method
<p>The dataset contains the simulation codes and generated data in the manuscript titled "Insight into the mechanical coupling behavior of loose sediment and embedded fiber-optic cable using discrete element method". The codes (M files) were written in MatDEM, version 3.0 (free access at <strong>www.matdem.com</strong>), and the data is stored in MAT files.</p> <ul> <li>Test2D_2L1.m - codes for initial compacted elements</li> <li>Test2D_2L1.mat - generated data for initial compacted elements</li> <li>Test2D_2L2.m - codes for compacted elements with embedded fiber-optic cable</li> <li>Test2D_2L2.mat - generated data for compacted elements with embedded fiber-optic cable</li> <li>Test2D_2L3.m – codes for confining pressure setting</li> <li>Test2D_2L-0MPa3.mat ~ Test2D_2L-1.0MPa3.mat - generated data for confining pressure setting</li> <li>Test2D_2L4.m – codes for fiber-optic cable pullout tests under various confining pressures</li> <li>Test2D_2L-05-26-20mm-0MPa-un-No1-4.mat ~ Test2D_2L-07-21-20mm-1MPa-un-No1-4.mat - generated data for fiber-optic cable pullout tests under various confining pressures</li> </ul>
Electronic appendix to: Spectral Induced Polarization (SIP) of Denitrification-Driven Microbial Activity in Column Experiments Packed with Calcareous Aquifer Sediments
<p>This is the electronic appendix of the publication <br> C. Strobel, S. Abramov, J. A. Huisman, O.A. Cirpka, A. Mellage (2022): Spectral Induced Polarization (SIP) of Denitrification-Driven Microbial Activity in Column Experiments Packed with Calcareous Aquifer Sediments (submitted)</p>
Data for Novel Approach to Quantify Sediment Transfer and Storage in Rivers with Feldspar Single-Grain pIRIR
<p>Raw data of feldspar post infra-red infra-red (pIRIR) stimulated luminescence signal from modern sand from New Zealand rivers (Rakaia, six samples; Waimakariri, height samples) used in the paper Guyez et al. (2022) submitted to JGR: Earth Surface. The samples were collected in February 2020 by S. Bonnet and A. Guyez. They were measured in the Netherlands Center for Luminescence dating (Wageningen University and Research). </p>
Text-fig. 7. Geology of the Muaredzi-Muanza sector of the Cheringoma Plateau showing the location of fossil occurrences. White stars – fossiliferous localities mapped by Pickford (2012, 2013), Black stars – fossil sites mapped by Habermann et al. (2019) and d'Oliveira Coelho et al. (2021) (GPL 12 and GPL 12b correspond to the White Patch sites). TTI – Cheringoma Formation, TTs1 – Mazamba Formation, TTs1a – Palaeopan facies, TTs2 – Inhaminga Formation, Qc – Quaternary sediments. The base map is modified from Google Earth. in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 7. Geology of the Muaredzi-Muanza sector of the Cheringoma Plateau showing the location of fossil occurrences. White stars – fossiliferous localities mapped by Pickford (2012, 2013), Black stars – fossil sites mapped by Habermann et al. (2019) and d'Oliveira Coelho et al. (2021) (GPL 12 and GPL 12b correspond to the White Patch sites). TTI – Cheringoma Formation, TTs1 – Mazamba Formation, TTs1a – Palaeopan facies, TTs2 – Inhaminga Formation, Qc – Quaternary sediments. The base map is modified from Google Earth.
Text-fig. 3. Examples of plant macrofossil assemblages from post-evaporitic sections. a: bedding plane from Ciabòt Cagna covered by impressions of plant parts, with dominance of leaves of cf. Oleinites liguricus M.SACHSE, MCEA-P05038. b: waterloggedcompressed seeds of Toddalia latisiliquata (R.LUDW.) H.-J.GREGOR sieved out of a bulk sediment sample from Pollenzo, MGPTPU141033. c: millimeter-sized, waterlogged-compressed seeds of Sambucus pulchella C.REID et E.REID with abundant cracks, probably formed during both diagenesis and extraction of the fossils (bulk sediment sample from Ciabòt Cagna), MGPT- in Late Messinian Flora From The Post-Evaporitic Deposits Of The Piedmont Basin (Northwest Italy)
Text-fig. 3. Examples of plant macrofossil assemblages from post-evaporitic sections. a: bedding plane from Ciabòt Cagna covered by impressions of plant parts, with dominance of leaves of cf. Oleinites liguricus M.SACHSE, MCEA-P05038. b: waterloggedcompressed seeds of Toddalia latisiliquata (R.LUDW.) H.-J.GREGOR sieved out of a bulk sediment sample from Pollenzo, MGPTPU141033. c: millimeter-sized, waterlogged-compressed seeds of Sambucus pulchella C.REID et E.REID with abundant cracks, probably formed during both diagenesis and extraction of the fossils (bulk sediment sample from Ciabòt Cagna), MGPT-
Text-fig. 7. Stereomicroscope microphotographs of plant remains sieved out of a sediment bulk sample (C3X) from bed GLA10 of Govone. a: Tetraclinis salicornioides (UNGER) KVAČEK, shoot fragment, MGPT-PU141083). b: Toddalia latisiliquata (R.LUDW.) H.-J. GREGOR, seed, MGPT-PU141084. c: Toddalia rhenana H.-J.GREGOR, seed, MGPT-PU141085. d: Eurya stigmosa (R.LUDW.) MAI, small seed with piths filled by organic remains and sediment, MGPT-PU141086. e: Eurya stigmosa (R.LUDW.) MAI, fragmentary seed, MGPT-PU141087. f: Visnea germanica MENZEL, fruit from two opposite sides, MGPT-PU141088. g: Symplocos casparyi R.LUDW., endocarp in lateral view from two opposite sides, MGPT-PU141089. Scale bar 1 mm. in Remains Of A Subtropical Humid Forest In A Messinian Evaporitebearing Succession At Govone, Northwestern Italy - Preliminary Results
Text-fig. 7. Stereomicroscope microphotographs of plant remains sieved out of a sediment bulk sample (C3X) from bed GLA10 of Govone. a: Tetraclinis salicornioides (UNGER) KVAČEK, shoot fragment, MGPT-PU141083). b: Toddalia latisiliquata (R.LUDW.) H.-J. GREGOR, seed, MGPT-PU141084. c: Toddalia rhenana H.-J.GREGOR, seed, MGPT-PU141085. d: Eurya stigmosa (R.LUDW.) MAI, small seed with piths filled by organic remains and sediment, MGPT-PU141086. e: Eurya stigmosa (R.LUDW.) MAI, fragmentary seed, MGPT-PU141087. f: Visnea germanica MENZEL, fruit from two opposite sides, MGPT-PU141088. g: Symplocos casparyi R.LUDW., endocarp in lateral view from two opposite sides, MGPT-PU141089. Scale bar 1 mm.
Text-fig. 3. "Rzehakia beds" at Líšeň-Neklež locality. 1 – topsoil, 2 – greenish-gray clay, locally yellow-brown, 3 – ochre-brown coarse sand, 4 – conglomerate with clasts of granodiorite, 5 – grey-brown medium-grained sand, 6 – light yellowish fine sand, 7 – re-sedimented red-brown eluvium of granodiorite, 8 – re-sedimented red-brown granodiorite debris, 9 – granodiorite, 10 – fossil macroflora. in A New Early Miocene (Ottnangian) Flora Of The "Rzehakia Beds" From Brno-Líšeň
Text-fig. 3. "Rzehakia beds" at Líšeň-Neklež locality. 1 – topsoil, 2 – greenish-gray clay, locally yellow-brown, 3 – ochre-brown coarse sand, 4 – conglomerate with clasts of granodiorite, 5 – grey-brown medium-grained sand, 6 – light yellowish fine sand, 7 – re-sedimented red-brown eluvium of granodiorite, 8 – re-sedimented red-brown granodiorite debris, 9 – granodiorite, 10 – fossil macroflora.
Greigite formation modulated by turbidites and bioturbation in deep-sea sediments offshore Sumatra
<p>This repository contains the rock magnetic and paleomagnetic data, TOC and TN data, and XRD spectra data associated with the research paper titled "Greigite formation modulated by turbidites and bioturbation in deep-sea sediments offshore Sumatra" by Yang et al. published in Journal of Geophysical Research: Solid Earth, Volume127, Issue11, e2022JB024734, https://doi.org/10.1029/2022JB024734</p>
Рис. 4. Распределение станций отбора проб по глубине и типу грунта (круЖком обведены станции, на которых макробентос не обнаруЖен; БО – биогенные остатки, ГМ – галька мелкаЯ, Гр – гравий, И – ил, П – песок). Fig. 4. Distribution of sampling stations by depth and type of bottom sediments (circles are around the stations where no macrobenthos was detected; БО – biogenic residues, ГМ – pebbles, Гр – gravel, И – silt, П – sand). in Species composition and distribution of bivalve mollusks in plankton and benthos in Nevelsky Strait in summer
Рис. 4. Распределение станций отбора проб по глубине и типу грунта (круЖком обведены станции, на которых макробентос не обнаруЖен; БО – биогенные остатки, ГМ – галька мелкаЯ, Гр – гравий, И – ил, П – песок). Fig. 4. Distribution of sampling stations by depth and type of bottom sediments (circles are around the stations where no macrobenthos was detected; БО – biogenic residues, ГМ – pebbles, Гр – gravel, И – silt, П – sand).
CoUDlabs_WP8_T812_Deltares_001. Measuring sediment deposits in gully pots from temperature signals
<p>This dataset contains the results of the experimental campaign and how data were collected on the the <a href="https://co-udlabs.eu/">Co-UDlabs</a> <strong>Work Package 8 (Joint Research Activity 3)</strong>: <i>Improving resilience and sustainability in urban drainage solutions</i>; <strong>Task 8.1</strong>: <i>Development of consensus on measurement of hydraulic and water quality performance of urban drainage technologie</i>s; <strong>Subtask 8.1.2</strong>: <i>Development of scalable measurement protocols to assess the pollutant retention and release potential of urban drainage structures</i>. </p><p>The experimental campaign was funded under the European Union's Horizon 2020 research and innovation programme under grant agreement No 101008626.</p><p>The experiments were designed to further develop an innovative methodology for measuring sediment bed deposits in UDS based on temperature data analysis (<a href="https://doi.org/10.5281/zenodo.7258998">Anta et al., 2022</a>; <a href="https://doi.org/10.1039/D2EW00820C">Regueiro-Picallo et al., 2023</a>). Particularly, the aim of these campaigns was to test the application of this methodology in gully pots for measuring sediment build-up. For this purpose, we focused on understanding the heat transfer processes in gully pots in relation to the volume of bed deposits. Thus, the aim of this research is to estimate or at least obtain proof for the presence/absence of sediments by analyzing the differences between the temperature time series measured in the water phase and at the bottom of bed deposits. Results from the experimental campaigns will help to develop new technologies to estimate accumulation in urban drainage infrastructures.</p><p>The data are described so that others can use and reproduce.</p>
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C). in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C).
Dense vegetation hinders sediment transport towards saltmarsh interiors - Supporting data and source code (Part III: Extra runs)
<p>This is Part III of the supporting data and source code for the paper entitled "Dense vegetation hinders sediment transport towards saltmarsh interiors", submitted to <em>Limnology and Oceanography Letters.</em> It contains all input and output files for the extra simulations used in the paper (Figures S3, S8-S10).</p> <p>Each zip file corresponds to a model run. </p> <p>TIGER_XX.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 0-100.<br>TIGER_XX_100.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 100-200.<br>TIGER_XX_HYYY.zip: Scenario XX, hydro-morphodynamics only, year YYY.</p> <p>Main scenarios:<br>- 01: Spartina (Figures 1-5, S3-S10)<br>- 02: Salicornia (Figures 1-5, S3-S10)<br>- 83: No vegetation (Figures 1-5, S3, S8-S10)</p> <p>Additional scenarios:<br>- 146: Spartina, low bulk drag coefficient (Figure S3)<br>- 147: Spartina, very low bulk drag coefficient (Figure S3)<br>- 148: Salicornia, low bulk drag coefficient (Figure S3)<br>- 149: Salicornia, very low bulk drag coefficient (Figure S3)<br>- 122: Spartina, low settling velocity (Figure S8)<br>- 123: Spartina, high settling velocity (Figure S8)<br>- 124: Salicornia, low settling velocity (Figure S8)<br>- 125: Salicornia, high settling velocity (Figure S8)<br>- 126: No vegetation, low settling velocity (Figure S8)<br>- 127: No vegetation, high settling velocity (Figure S8)<br>- 128: Spartina, low critical bed erosion shear stress (Figure S8)<br>- 129: Spartina, high critical bed erosion shear stress (Figure S8)<br>- 130: Salicornia, low critical bed erosion shear stress (Figure S8)<br>- 131: Salicornia, high critical bed erosion shear stress (Figure S8)<br>- 132: No vegetation, low critical bed erosion shear stress (Figure S8)<br>- 133: No vegetation, high critical bed erosion shear stress (Figure S8)<br>- 134: Spartina, low Partheniades constant (Figure S8)<br>- 143: Spartina, high Partheniades constant (Figure S8)<br>- 136: Salicornia, low Partheniades constant (Figure S8)<br>- 144: Salicornia, high Partheniades constant (Figure S8)<br>- 138: No vegetation, low Partheniades constant (Figure S8)<br>- 145: No vegetation, high Partheniades constant (Figure S8)<br>- 150: Spartina, low sediment dry bulk density (Figure S8)<br>- 151: Spartina, high sediment dry bulk density (Figure S8)<br>- 152: Salicornia, low sediment dry bulk density (Figure S8)<br>- 153: Salicornia, high sediment dry bulk density (Figure S8)<br>- 154: No vegetation, low sediment dry bulk density (Figure S8)<br>- 155: No vegetation, high sediment dry bulk density (Figure S8)<br>- 76: Spartina, replicate #1 (Figures S9-S10)<br>- 77: Spartina, replicate #2 (Figures S9-S10)<br>- 78: Spartina, replicate #3 (Figures S9-S10)<br>- 88: Spartina, replicate #4 (Figures S9-S10)<br>- 80: Salicornia, replicate #1 (Figures S9-S10)<br>- 81: Salicornia, replicate #2 (Figures S9-S10)<br>- 82: Salicornia, replicate #3 (Figures S9-S10)<br>- 89: Salicornia, replicate #4 (Figures S9-S10)<br>- 85: No vegetation, replicate #1 (Figures S9-S10)<br>- 86: No vegetation, replicate #2 (Figures S9-S10)<br>- 87: No vegetation, replicate #3 (Figures S9-S10)<br>- 90: No vegetation, replicate #4 (Figures S9-S10)</p> <p> </p>
Dense vegetation hinders sediment transport towards saltmarsh interiors - Supporting data and source code (Part V: Figures)
<p>This is Part V of the supporting data and source code for the paper entitled "Dense vegetation hinders sediment transport towards saltmarsh interiors", submitted to <em>Limnology and Oceanography Letters.</em> It contains all input and output files to generate the figures of the paper.</p> <p>To be able to run the scripts as is, the path (at the beginning of each script) to the following folders must be updated:</p> <p>Runs (includes all model run folders from Part II and Part III)<br>Post (includes all post-processing folders from Part IV)</p>
Fig. 5 in The oldest birotule-bearing freshwater sponges from the Upper Cretaceous-lower Paleocene Deccan volcanic-associated sediments of India
Fig. 5. Spicular complement of skeleton and gemmules of palaeospongillid sponge Longibirotula antiqua gen. et sp. nov. from Upper Cretaceous–lower Paleocene of Naskal GSI Quarry (India) (slides PGNU/NSKQ/ST-1, 2). A, B. Acanthoxeas short with dense spines. C, D. Oxeas fusiform, long and with acute tips. E, F. Birotules with long shaft. Diagenetic processes affect all spicules to various degree. Scale bars 20 µm.
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.