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1,572 results for “Sedimentation”
75-kyr paired mean summer temperature (MST) and moisture balance (BIT-index) data for eastern equatorial Africa based on GDGT distributions in the DeepCHALLA sediment sequence
<p>The DeepCHALLA (DCH) GDGT-based climate proxy data series consist of paired measurements on 373 discrete 2-cm-thick sediment samples, represented by their DCH event-free depth in meter (mefd). Section depth center refers to the distance (in cm) of the sample’s center from the top of the individual core section as represented by its DCH core code. Sediment age is based on the age model as presented in Fig. 2 in Baxter et al. (2023). Mean Summer Temperature (MST) was calculated from the distribution of sedimentary brGDGTs according to Pearson et al. (2011) and rescaled using an ensemble reconstruction for eastern Africa covering the last 25 ka (Extended Data Fig. 4 in Baxter et al., 2023). The branched versus isoprenoid tetraether (BIT) index of sedimentary brGDGTs from Lake Chala, reflecting lake water-balance variation, was calculated according to Hopmans et al. (2004).</p>
Absolute time markers and age-depth model for the last 75 kyr of Lake Chala sediments
<p>The 171 time markers include 162 <sup>14</sup>C ages on bulk organic matter or grass charcoal in sediment intervals of the composite Challacea (CH03, CH05) sequence (Blaauw et al., 2011), transferred to the DeepCHALLA (DCH) composite sequence using mm- or cm-scale cross-correlation of visual lithostratigraphy (Baxter et al., 2023). The other nine time markers are six <sup>210</sup>Pb-dated intervals from gravity core CH99-1G transferred to the CH05 and DCH sequences using 1-cm resolution magnetic-susceptibility profiles (Blaauw et al., 2011), the November 2016 (DCH) and March 2005 (CH05) sediment-water interfaces, and the YTT cryptotephra (Baxter et al., 2023). Lab codes stand for the Poznan Radiocarbon Laboratory (Poz-), the Chrono Centre at Queen’s University in Belfast (UBA-), the Isotope Physics Laboratory at the University of Groningen (GrA-), the Saint-Croix Watershed Research Station of the Science Museum of Minnesota (SMM), and the Cambridge Tephra Laboratory (CT-). ‘Offset’ refers to the old-carbon age offset of bulk organic <sup>14</sup>C dates, modelled using 16 paired dates on bulk organic matter and grass charcoal and three sections allowing <sup>14</sup>C wiggle-match dating using closely spaced bulk organic samples (Blaauw et al., 2011). The compound error on corrected <sup>14</sup>C ages was calculated as SQRT ((Age Error)^2 + (Offset STD)^2). All dated intervals are represented by their DCH event-free depth in meter (mefd). </p>
Radiocarbon, Tephra, and Paleomagnetic Data from 5 Northern North Atlantic Sediment Cores to support Reilly et al. 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic."
<p>Data in support of Reilly et al., 2023, "The Amplitude and Timescales of 0-15 ka Paleomagnetic Secular Variation in the Northern North Atlantic." Published in the Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>Excel file includes worksheets for the following data:</p> <p>Tabular versions of the Supplementary Data Tables from the associated publication:</p> <ul> <li>Supplementary Table S1 from Publication: 14C data from sediment cores used in study</li> <li>Supplementary Table S2 from Publication: 14C data used in the GREENICE15 Stack</li> <li>Supplementary Table S3 from Publication: Tephra data used in study</li> </ul> <p>Paleomagnetic Datasets for the Characteristic Remanent Magnetizations used in this study:</p> <ul> <li>Paleomagnetic Data for Core MD99-2264</li> <li>Paleomagnetic Data for Core MD99-2265</li> <li>Paleomagnetic Data for Core MD99-2266</li> <li>Paleomagnetic Data for Core MD99-2269</li> <li>Paleomagnetic Data for Core MD99-2322</li> </ul> <p>Independent radiocarbon based Age Models for 5 cores used in this study:</p> <ul> <li>Independent Age Model for Core MD99-2264</li> <li>Independent Age Model for Core MD99-2265</li> <li>Independent Age Model for Core MD99-2266</li> <li>Independent Age Model for Core MD99-2269</li> <li>Independent Age Model for Core MD99-2322</li> </ul> <p>PSV Dynamic Time Warping (DTW) solutions of 3 cores to target curve, as described in publication</p> <ul> <li>DTW solution for MD99-2265 to target curve</li> <li>DTW solution for MD99-2266 to target curve</li> <li>DTW solution for MD99-2322 to target curve</li> </ul> <p>GREENICE15 PSV Stack</p> <ul> <li>Age model for GREENICE15 Stack using combined radiocarbon dates and correlated equivalent depth scale</li> <li>Inclination, Declination, and alpha 95 for the GREENICE15 PSV Stack</li> </ul>
A modern pollen dataset from lake surface sediments on the central-western Tibetan Plateau
<p>This is a modern pollen dataset on the central and western Tibetan Plateaubased on lake surface sediments of 90 lakes. The dataset includes pollen counts and pollen percentages for each lake sediment sample together with their locations (latitude, longitude and altitude) and climatic data. </p>
Validation of the satellite-estimated sedimentation rates in reservoirs using 10-m Sentinel-2 satellites and water level data
<p><strong>Overview</strong>: The database contains data used for the validation of satellite-based sedimentation rates in eight reservoirs across the central and western United States using 10-m Sentinel-2 imagery and in-situ level data. Additional validation of the results from combining Sentinel-2 imagery with simulated 27-day Sentinel-3 altimetry levels is also included.</p> <p> </p> <p><strong>This dataset includes</strong>:</p> <ol> <li>Satellite-derived area-level duplets</li> <li>Bathymetry curves from satellite-based estimates</li> <li>Bathymetry curves from survey data</li> <li>Validation</li> </ol>
Wave, Flow, and Sediment Dynamics under Strong Winds on a tidal beach
<p>The data are saved as matlab data file.</p> <p>1) ssc_fit.mat is used for producing figure 2.</p> <p>2) Reynolds_shear_stress.mat is used for producing figures 3 and 10.</p> <p>3) hydrodynamics.mat is used for producing figure 4.</p> <p>4) shear_stress_&_ssc.mat is uesd for producing figures 5 and 8.</p> <p>5) SSF.mat is used for producing figures 6 and 11.</p> <p>6) breaking_wave_criteria.mat is used for producing figure 7.</p> <p>7) mob_number.mat is used for producing figure 9.</p>
Data for 'Rethinking variability in bedrock rivers: sensitivity of hillslope sediment supply to precipitation events modulates bedrock incision during floods'
<p>This is the repository for model code, sample data, and plotting scripts for the OTTER model for Python.</p> <p>The file OTTERPy.py contains the actual model code</p> <p>The file OTTERPlottingFuncs.py contains a few scripts for plotting model results.</p> <p>The four sample data files in the repository are results from two long (1.5million model year) runs at different rock uplift rates which took several days to run on the IU Bloomington Quartz supercomputing cluster. This data should be viewed and plotted using the OTTERPlottingFuncs.py script. See that code for information on how to select which model to plot.</p> <p> </p> <pre><code>Glossary of variables - this is pretty close to exhaustive, there are a probably a couple of throwaway variables not listed here. a: Sternberg's law multiplier Ah: drainage area from Hack's Law (m^2) beta: fraction of sediment transported as bedload from 0 to 1 D: grain size at each node (m) dA: change in drainage area from node to node (m^2) depth_thresh: sediment depth at which bedrock erosion can occur Do: initial grain size Do: grain size at headwaters (m) dQs: change in sediment supply from node to node dt: time step (years) dx: space step (m) dz_b: bedrock erosion at each node dz_s: change in sed depth dz_b_t: bedrock erosion saved through time dz_b_store: bedrock erosion stored dz_s_store: sed depth change stored eQ: exponent for scaling Qw from Ah eroded_sedsup: sediment created by bedrock erosion eW: exponent for scaling W from Qw F: fractional bedrock exposure g: gravitational acceleration (M/s^2) H: water depth Hc: Hack's Law constant He: Hack's law Exponent initial_sedsup: Sediment supply in first 10k yr (equal to uplift) kf: bedrock erodibility kQ: constant for scaling Qw from Ah kv: parameter controlling discharge variability - Crave & Davy, 2001. Lower kv is more variable kw: lateral bedrock erosion constant kWid: constant for scaling W from Qw last_z: elevation at channel mouth lmbda: sediment porosity n: manning's roughness coefficient onlyonce: changes from 0 to 1 to make sure the uplift pulse only happens one time onoff: turns sediment on and off entirely onoffsedvar: turns stochastic sediment on and off Qs: sediment supply along the length of the river Qs_down: downstream sediment flux at each node Qt: sediment transport capacity Qw: water discharge Qwo: initial water discharge QwScale: array of scalar multipliers for Qw, from the chosen distribution R: effective density of submerged sediment rho_w: density of water (kg/m^3) rho_s: density of sediment (kg/m^3) savesteps: at what time should we save outputs? sed_depth: depth of seidment at each node (m) SedStore: storing snapshots of sediment thickness through time slope: river gradient (negative usually) SlopeStore: storing snapshots of channel slope through time tarray: array of model time tau_b: basal shear stress tau_c: critical shields criterion for initiation of sediment motion time: model duration (years) topo: channel elevation (bedrock + sediment) upinc: size up uplift pulse, as a multiplier of initial uplift rate upinctime: when should the pulse happen? (years) uplift: uplift field across the entire domain uprate: initial uplift rate, if using constant uplift across domain W: channel width WidthStore: storing snapshots of channel width through time Wo: initial channel width yr2sec: number of seconds in a year z: bedrock channel elevation ZStore: storing snapshots of bedrock elevation through time</code></pre>
Data for: Water depth and transparency drive the quantity and quality of organic matter in sediments of Alpine lakes on the Tibetan Plateau
<p>The primary objectives of the study were to: (i) determine OM quantity and quality in the sediments of alpine lakes on the Tibetan Plateau, (ii) identify the primary environmental regulators of OM quantity and quality, and (iii) reveal OM transformations in the water column and sediments.</p> <p>Firstly, we collected sediments and lake water from 20 lakes with diverse morphology and sizes across the entire Tibetan Plateau.</p> <p>Secondly, We analyzed the bulk sedimentary OM and two leachable pools of the sedimentary OM, i.e., water-soluble OM and alkaline-extracted OM combining elemental and stable isotopic analysis, optical measurements (i.e., absorbance and fluorescence spectroscopy), and ultrahigh-resolution molecular techniques (i.e., electrospray ionization-assisted Fourier transform-ion cyclotron resonance mass spectrometry, ESI FT-ICR MS). We also measured the lake water physicochemical characteristics (i.e., depth, transparency, salinity, turbidity, DO, pH, TN, TP and Chl a), as well as the composition of dissolved OM in water column via optical measurements.</p> <p>Thirdly, we performed statistical analysis to determine the primary environmental control and predictors of the spatial variability in sedimentary OM on the Tibetan Plateau. The statistical analysis included non-parametric Kruskal-Wallis with Dunn post hoc test, redundancy analysis, and linear regression models.</p> <p>Main results of the study are that (i) sedimentary water-soluble OM and alkaline-extracted OM were both dominated by low-molecular-weight, low-aromaticity compounds with low contributions of terrestrial humic substances, suggesting that sedimentary leachable OM was primarily regulated by in-lake sources and processes; (ii) water depth, water transparency, and total phosphorus concentration in water column explained ~50% variance of sedimentary bulk and leachable OM, substantiating the importance of autochthonous sources and primary productivity in regulating the quantity and quality of sedimentary OM; (iii) in comparison to lake surface water DOM, water-soluble OM and alkaline-extracted OM from sediments had higher proportions of terrestrial humic-like substances, suggesting preferential preservation of allochthonous materials in the sediments.</p>
Sediment texture and nutrient data from: Bacterial assembly in agricultural streams
<p>Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally-associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy-stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, while nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.</p>
data for K-feldspar enrichment in the Pacific pelagic sediments before Miocene
<p>This is the data associated with the manuscript K-feldspar enrichment in the Pacific pelagic sediments before Miocene published in Progress in Earth and Planetary Sciences.</p> <p> </p> <p>The data includes:</p> <p>Sample ID and depth.</p> <p>Magnetic susceptibility.</p> <p>Weight fraction after chemical digestions (CBD and Na-pyrosulfate fusion).</p> <p>Grain size.</p> <p>XRD spectra.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Magnetic properties of siliciclastic cave sediments from the Ciur Izbuc Cave
<p>Magnetic properties of siliciclastic cave sediments from the Ciur Izbuc Cave (Apuseni Mts., Romania: 46.85171° N, 22.40014° E, 540 m). Further details can be found in Moldovan et al. (2016), Fossil invertebrates records in cave sediments and paleoenvironmental assessments: a study of four cave sites from Romanian Carpathians, Biogeosciences, 13, 483-487, https://doi.org/10.5194/bg-13-483-2016.</p>
Magnetic properties of siliciclastic cave sediments from the Leșu Cave
<p>Magnetic properties of siliciclastic cave sediments from the Leșu Cave (Peștera cu Apă din valea Leșu) (Apuseni Mts., Romania: 46.824332° N, 22.556533° E, 721 m). Further details can be found in Moldovan et al. (2016), Fossil invertebrates records in cave sediments and paleoenvironmental assessments: a study of four cave sites from Romanian Carpathians, Biogeosciences, 13, 483-487, https://doi.org/10.5194/bg-13-483-2016.</p>
Radionuclide, particle size and elemental geochemistry analysis results of the Poechos sediment core, northern Peru
<p>This database presents the particle size, elemental geochemistry and radionuclide analyses carried out on the 19CO3 core (IGSN number: 10.58052/IEFOU0009) collected in June 2019 in the Poechos reservoir (Peru). These results are part of the publication <em>" El Niño-Southern Oscillation (ENSO)-driven hypersedimentation in the Poechos Reservoir, northern Peru "</em> available via the following link: http://dx.doi.org/10.5194/egusphere-2022-1233</p> <p>Corresponding authors: anthony.foucher@lsce.ipsl.fr</p> <p>Particle size analysis was performed using a laser grain sizer Malvern Mastersizer 3000 allowing to measure the grain size distribution between 10 nm and 3.5 mm. Particle size was measured on the sandy layers identified along the core (n=19) Grain size parameters such as d10, d50, d90 and raw are present on the file: <em>Particle_size_POECHOS-reservoir_Foucher-et-al</em></p> <p>Sediment core sections were analyzed with an Avaatech X-Ray Fluorescence core scanner (XRF) available at the Laboratoire des Sciences du Climat et de l’Environnement (Gif-sur-Yvette, France) with a 0.5 cm resolution. These data are available on the file: <em>XRF_core_scanner_POECHOS-reservoir_Foucher-et-al</em></p> <p>Gamma spectrometry measurements were obtained using HPGe detectors (Canberra/Ortec) available at the Laboratoire des Sciences du Climat et de l’Environnement. Short-lived radionuclides (e.g., caesium-137 (137Cs) and excess of lead-210 (210Pbex)) were measured in 12 samples of dry sediment (≈10g) collected along the sedimentary sequence (approximatively every 40 cm). The data are available on the file: <em>Radionuclides_POECHOS-reservoir_Foucher-et-al</em></p>
Distribution of heavy metals in coastal sediments under the influence of multiple factors: A case study from the south coast of an industrialized harbor city (Tangshan, China)
<p><span>This research investigated the spatial distribution of heavy metals, including mercury (Hg), cadmium (Cd), copper (Cu), arsenic (As), nickel (Ni), lead (Pb), chromium (Cr), and zinc (Zn), in surface sediments from the coastal area near to an industrial harbor (the Tangshan Harbor, China) with 161 sediment samples. The results showed that the distribution patterns of Cr, Cu, Zn, Ni, and Pb were similar to each other, high in the northwest, southeast, and southwest regions of the study area and low in the northeast region, which corresponded well with components of sedimental sizes. The uncontaminated specimen proportions for Hg, Cd, Cu, As, Ni, Pb, Cr, and Zn were 6.8%, 4.3%, 31.1%, 28.6%, 42.9%, 64.6%, 44.7%, and 50.3%, respectively. Based on principal component analysis (PCA) and positive matrix factorization (PMF), four distinct sources of pollution were quantitatively attributed, including agricultural activities (22.08%), fossil fuel consumption (24.14%), steel production (29.78%), and natural sources (24.00%). Hg (80.29%), Cd (82.31%) and As (65.33%) in the region's coastal sediments were predominantly contributed by fossil fuel, steel production and agricultural</span> <span>sources, respectively. Cr (40.00%), Cu (43.63%), Ni (47.54%), and Zn (38.98%) were primarily of natural lithogenic origin, while Pb mainly came from the mixed sources of agricultural activities (36.63%), fossil fuel (36.86%), and steel production (34.35%). Multiple factors played important roles in the selective transportation of sedimentary heavy metals, especially sediment properties, and hydrodynamic sorting processes in the study area.</span></p>
Data from: Erosion regime controls sediment environmental DNA-based community reconstruction
<p><span>Analysis of environmental DNA detected in lake sediments shows promise to become a great paleoecological technique that can provide detailed information about organism communities living in past environments. However, when interpreting sedimentary environmental DNA records, it is of crucial importance to separate ecosystem responses to large-scale environmental change from 'noise' caused by changes in sediment provenance or potential post-depositional DNA mobility. In this study, we show that plant and mammalian communities reconstructed from sediments are strongly affected by sediment provenance, but unaffected by vertical mobility of DNA after sediment deposition. We observe that DNA from aquatic plants was abundant in background sediment, while embedded detrital event layers (sediment deposited under erosion events) primarily contained terrestrial plants; hence, vertical mobility of aquatic plant DNA across sediment layers was negligible within our studied lakes. About 33% of the identified terrestrial plant genera were only found in detrital sediment suggesting that sediment origin had a strong impact on the reconstructed plant community. Similarly, DNA of some mammalian taxa (<em>Capra hircus</em>, <em>Ursus arctos</em>, <em>Lepus</em>, <em>Felis</em>) were only or preferentially found in detrital event layers. Temporal changes across the Holocene were the main drivers of change for reconstructed plant communities, but sediment type was the second most important factor of variance. Our results highlight that erosion and sediment provenance need to be considered when reconstructing past mammalian and plant communities using environmental DNA from lake sediments.</span></p>
Contaminated sediment in the Detroit River selects for evolved CYP1A and p53 responses in wild brown bullhead (Ameiurus nebulosus) populations
<div> <div> <p><span>In a previous study, adaptive responses to a single polycyclic aromatic hydrocarbon (PAH), benzo[a]pyrene (BaP), were identified in brown bullhead (</span><span><em>Ameiurus nebulosu</em>s</span><span>) captured from contaminated sites across the Great Lakes. The tumor suppressor p53 and phase I toxin metabolizing CYP1A genes showed a protective and refractory response, respectively, up to the F1 generation (Williams and Hubberstey, 2014). As an extension to the first study, bullhead were exposed to sediment collected from sites along the Detroit River to see if these adaptive responses are attainable when fish from a contaminated site are exposed to a mixture of contaminants, instead of a single compound. p53 and CYP1A proteins were measured in both studies with the addition of phase II glutathione-s-transferase (GST) activity in the second. Three treatment groups were measured: acute (treated immediately), cleared (depurated for three months and subsequent treatment), and farm raised F1 offspring. All three treatment groups were exposed to clean and contaminated sediment for 24 and 96 hours. </span><span>Acute fish from contaminated sites exposed to contaminated sediment revealed an initial elevated p53 response that was not reached in cleared fish exposed to contaminated sediment. Instead, cleared and F1 bullhead from clean and contaminated sites had overlapping p53 expression patterns in response to contaminated sediment by 96 hours. Acute fish from contaminated sites exposed to contaminated sediment revealed refractory CYP1A expression, which disappeared in cleared fish and whose F1 refractory response overlapped with clean site F1 offspring. Decreasing GST activity was evident in both clean and contaminated fish over time, with clean site fish responding to contaminated sediment more deliberately. By 96 hours, the response patterns of F1 offspring from clean and contaminated sites to clean and contaminated sediment exposures were similar. </span><span> </span></p> </div> <div> <p><span>Because p53, CYP1A and GST activity responses to contaminated sediment dosing overlapped in clean and contaminated farm-raised F1 offspring, these results suggest that contaminated fish have acclimated to the contaminants present in their environments by reaching a tolerance threshold and no evidence of adaptation was detected in these biomarkers. </span></p> </div> </div>
The presence and abundance of Escherichia coli in beach sediment following a coastal renourishment project
<p>Erosion poses a major threat to oceanic beaches worldwide. To combat this threat, management agencies often utilize renourishment, which supplements eroded beaches with offsite sand. This process alters the physical characteristics of the beach and can subsequently influence the presence and abundance of microbes. In this study, we examined how a renourishment project impacted sand grain size and the presence and abundance of <em>Escherichia</em> <em>coli</em> (<em>E</em>. <em>coli</em>), a common bacteria species. Using an observational field approach, we compared abundances of <em>E. coli</em> and sand grain sizes between non-renourished and renourished sections of Folly Beach, South Carolina, USA in 2014 and 2015. We found that <em>E. coli</em> was prevalent in every zone of the beach in both years of sampling. Additionally, we found that in comparison to non-renourished areas, renourished areas had significantly higher abundances of <em>E. coli</em> and coarser sand grains in the intertidal zone. However, these differences were temporary and only present following the initial renourishment event. Collectively, our findings raise concerns about how physical changes in sand grain size, and the introduction of offsite sand to a beach, could alter bacterial presence and growth. However, more work is needed to fully understand the timescales these effects operate upon.</p>
Data for "Invertebrate Activities in Wetland Sediments Influence Oxygen and Nutrient Dynamics at the Sediment-Water Interface"
<p>Code and data for a project looking at how bioturbation by two benthic invertebrate taxa influence oxygen and nutrient dynamics a coastal freshwater wetland along Lake Erie, located in Ohio, USA.</p> <p>Article is titled "Invertebrate Activities in Wetland Sediments Influence Oxygen and Nutrient Dynamics at the Sediment-Water Interface" and is published in Wetlands.</p>
Evolution of sediment temperature, pressure, phases distribution, carbon pools and seabed methane flux at the Arctic continental Shelves since the Last Glacial Maximum
<p>This dataset are produced by a manuscript (<strong>Biodegradation of Ancient Organic Carbon Fuels Seabed Methane Emission at the Arctic Continental Shelves</strong>) to be submitted to the Journal of Geophysical Research - Global Biogeochemical Cycles. I</p> <p>The file "MethaneEmission_Permafrost" contains the predicted temperature, pressure, pore water salinity, ice stable zone, methane hydrate stable zone, ice saturation, methane hydrate saturation, free methane gas saturation, labile organic carbon content, stable organic carbon content, and methanogenesis rate from seafloor to 1200 m depth from 18,000 years before present to 2,000 years after present for 8 different simulation scenarios. </p> <p>The file "Seabed_Methane_Flux" contains the predicted seabed methane emission rate from 18,000 years before present to 2,000 years after present for 8 different simulation scenarios. </p> <p>Detailed information about the model could be found in the paper <strong>Biodegradation of Ancient Organic Carbon Fuels Seabed Methane Emission at the Arctic Continental Shelves. </strong></p> <p> </p>
Soil-biodegradable plastic films do not decompose in a lake sediment over 9 months of incubation
<p>Dataset with the article 'Soil-biodegradable plastic films do not decompose in a lake sediment over 9 months of incubation', containing CO2 and CH4 data of sediment core incubations in a laboratory setting.</p> <p>Time is in days.</p> <p>Group identifiers: PC = control, PE = PE plastics (traditional), PR = Biodegradable plastics type 1, PS = biodegradable plastics type 2.</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.