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1,392 results for “accumulation”

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edi60/100

Litter and soil accumulation estimates derived from lateral microplot photos in the Cross-Scale Interactions Study (CSIS) at Jornada Basin LTER, 2013-2017

This dataset contains litter and soil vertical accumulation estimates derived from lateral photos of microplots in a long-term experiment (2013-2017) of cross-scale interactions (CSIs) at the Jornada Basin LTER site in southern New Mexico, U.S.A. Experimental treatments were initiated in 2013 at 15 experimental blocks, each with 4 treatment plots: plant-scale herbicide of mesquite shrubs, patch-scale connectivity modifiers (ConMods), herbicide + ConMods, control without manipulations. Repeat, lateral (side-looking) photographs of ten "microplots" in each ConMods and herbicide+ConMods plot were taken for estimation of litter, soil, and vegetation cover in the experimental treatment and control plots over time. Photographs were analyzed with SigmaScan software to determine vertical accumulation of litter and soil withing the microplots. This study is complete and ended in 2017. These vertical accumulation estimates are derived from photos in EDI dataset knb-lter-jrn.210413006.

openCC (other)Oct 2023View details →
edi56/100

Increased inflammation and oxidative stress caused by accumulated metal particle exposure among metro station staff, Tianjin, China, 2023

Metro is a significant part of world transport, delivering over 58 billion passengers annually. The dilution effect of particulate matter (PM) from natural ventilation was limited in underground metro stations. What's worse, train operation processes generated PM rich in heavy metals. Though PM pollution in metro stations was reported widely, there is limited evidence of the adverse health effect of metro station PM. This dataset collected urinary samples from 74 metro station staff from three different metro stations in Tianjin, China, for inflammation and oxidative stress biomarker tests to better understand the potential health effects induced by metal particulates in metro stations. Also, an indoor air quality survey was conducted simultaneously in the metro stations.

openCC (other)Nov 2025View details →
edi56/100

PAB01 Aboveground net primary productivity of tallgrass prairie based on accumulated plant biomass on core LTER watersheds (001d, 004b, 020b)

Data set contains estimates of end-of-season standing crop biomass (grams per square meter) of live graminoids, forbs, woody plants, and previous year's dead vegetation for 2 soil types (shallow and deep) on three core LTER watersheds representing three fire frequency treatments. Twenty quadrats (0.1 square meters) are harvested for each soil/treatment type. NOTE: Early (April) and mid-season (July) biomass was collected from 1983-1988, and these data are available by request.

openCC0Jun 2025View details →
OpenNeuro52/100

Evidence accumulation relates to perceptual consciousness and monitoring

Open the record for dataset details and reuse information.

openCC0Jan 2021View details →
OpenNeuro52/100

Evidence Accumulation in Value-Based decisions

Open the record for dataset details and reuse information.

openCC0Jan 2020View details →
edi52/100

Seagrass Epiphyte Accumulation for Florida Bay, South Florida (FCE) from December 2000 to September 2001

Total epiphyte and epiphyte chlorophyll-a loads were measured from artificial seagrass leaves (Mylar) deployed for periods up to the approximate Thalassia leaf turnover period.

openCC (other)Feb 2024View details →
edi52/100

Mean Seagrass Epiphyte Accumulation for Florida Bay, South Florida (FCE) from December 2000 to September 2001

Total epiphyte and epiphyte chlorophyll-a loads were measured from artificial seagrass leaves (Mylar) deployed for periods up to the approximate Thalassia leaf turnover period. Data were collected in Florida Bay, within Everglades National Park.

openCC (other)Feb 2024View details →
edi52/100

Seagrass Epiphyte Accumulation: Epiphyte Loads on Thalassia testudinum in Rabbit Key Basin, Florida Bay (FCE) from March 2000 to April 2001

Total epiphyte and epiphyte chlorophyll-a loads and leaf nutrients were measured on Thalassia seagrass short-shoots from Rabbit Key Basin, Florida Bay.

openCC (other)Feb 2024View details →
zenodo48/100

Data from: Carbon accumulation of cool season sports turfgrass species in distinctive soil layers

<p>Carbon sequestered by turfgrasses may contribute to reducing atmospheric CO<sub>2 </sub>levels, to improved soil health and to increased turfgrass quality. Therfore in a field study conducted in the Netherlands, the amount of soil C accumulated by nine cool season turfgrass monocultures and 12 mixtures of turfgrass species during the first three years of establishment was analysed and compared. Thatch, mat and other soil layers and the layers were sampled and thickness of these layers was quantified. From these samples, dry matter, C and N concentrations, and CN ratio were measured.</p> <p>The study was conducted on a 3 years old turfgrass field of the turfgrass seed company DLF. The site was located in the Netherlands (51&deg;32&acute;N, 4&deg;20&acute;E), on a sandy soil (Hortic Anthrasol as described in the FAO/Unesco soil map of the world (2006)). The monocultures consisted of different varieties of the (sub)species&nbsp;<em>Lolium perenne (lp), Poa pratensis (Pp), Festuca arundinacea (Fa), Festuca rubra commutata (Frc), Festuca rubr trichophylla (Frt), Festuca rubra rubra (Frr), Festuca ovina duriuscala (Fod), Festuca ovina vulgaris (Fov), Agrostis stolonifera (As). </em>Varieties were treated as replicates per (sub)species, which resulted in some variation in the number of replicates, as not all species were available in the same number of varieties.<em> </em>Varieties of the<em> (s</em>ub)species and mixtures were on the market as commercial turfgrass seeds.&nbsp; &nbsp; &nbsp;</p> <p>In 2016&nbsp; a soil profile sampler with a depth of 20 cm, a horizontal length of 10 cm and a width of 2 cm was used to take an undisturbed soil profile in each plot and the thickness of each layer, thatch, matt and remainder soil, was measured using the protocol as described in Evers et al. (2024). Plant biomass in the plots was quantified by taking cores of the top 20 cm of the soil with a core sampler (diameter 28 mm). Cores were divided into thatch, mat, the remainder soil till 10 cm depth, and 10-20 cm depth, respectively, based on the earlier measurement of layer thicknesses in the field. Sediment of each section was then carefully washed out with tap water, after which the remaining below-ground (dead and living) plant biomass was dried at 65&deg;C until stable weight and weighed. Total C and N analyses were carried out at the General Instrumentation Department of Radboud University with a Vario Micro Cube Element Analyzer (Elementar, Langenselbold, Germany), from which C and N concentrations (in % of dry matter or in mg cm<sup>-3</sup> C from total plant biomass in a layer) and CN ratios were calculated.</p> <p>Statistical analyses were carried out using the open source program R version 3.5.2 (2018-12-20). Differences in thickness of thatch and mat as well as differences in the C accumulation and C- and N concentration in thatch, mat and soil layers between (sub)species of turfgrasses in were based on the calculated means per species. Normality of residuals and the equality of variances was checked with diagnostic plots and Levene&rsquo;s test, respectively. Non-normal and heteroscedastic data were either log transformed in linear models from the car package, or general least square (gls) models using varIdent from the nlme package were used. All data were further analyzed with ANOVA-type3 from the car package, followed by the Tukey post hoc test of the emeans package. Correlations between thatch and mat thickness were analyzed with linear regression models in R of the ggplot package. Similar procedures were performed for correlation between thatch, mat or soil thickness and C accumulation as well as for the correlation between C concentration and N concentration on C accumulation in a particular layer.</p>

opencc-by-4.0Nov 2024View details →
zenodo48/100

An estimate of fitness reduction from mutation accumulation in a mammal allows assessment of the consequences of relaxed selection: Dataset

<p>Supplementary files (data and analysis) for "An estimate of fitness reduction from mutation accumulation in a mammal allows assessment of the consequences of relaxed selection"</p> <p>Supplementary File 1: C3H_pheno_fix_Jun7_2023_nolowmut.csv</p> <p>Data for all mice in MA experiment including: mouse ID, sire, dam, generation, mating ID, sex, weight at 3 weeks, weight at 6 weeks, tail length, litter size, litter ID, line ID</p> <p>&nbsp;</p> <p>Supplementary File 2: C3H_pheno_Kontrol_June2023.csv</p> <p>Data for all control mice including: mouse ID, sire, dam, generation, mating ID, sex, weight at 3 weeks, weight at 6 weeks, tail length, litter size, litter ID, line ID</p> <p>&nbsp;</p> <p>Supplementary File 3: C3H_birthdates.csv</p> <p>Data for all C3H mice including: mouse ID, birthdate</p> <p>&nbsp;</p> <p>Supplementary File 4: MA_pheno.R</p> <p>R code for visualising trait data, running linear regressions, and comparing control and MA experiment data</p> <p>&nbsp;</p> <p>Supplementary File 5: C3H_pheno_burnin20_Jun7_2023_nolowmut.csv</p> <p>Data for all mice in MA experiment including a 20 generation burn-in to simulate mutation-drift balance for Animal model analyses: mouse ID, sire, dam, generation, mating ID, sex, weight at 3 weeks, weight at 6 weeks, tail length, litter size, litter ID, line ID</p> <p>&nbsp;</p> <p>Supplementary File 6: asreml_C3H_ALL.R</p> <p>R code for estimating mutational heritabilities using mixed model analysis</p> <p>&nbsp;</p> <p>Supplementary File 7: C3H_ped_rekey_Jun2023.csv</p> <p>Pedigree data for all mice in MA experiment</p> <p>&nbsp;</p> <p>Supplementary File 8: C3H_ped_rekey_KEY.csv</p> <p>Key for pedigree data file</p> <p>&nbsp;</p> <p>Supplementary File 9: plot_pedigree_tree_MS_final.R</p> <p>R code for visualising pedigree of mice in MA experiment</p>

opencc-by-4.0Jul 2024View details →
zenodo48/100

Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation: Confocal and atomic force microscopy

<p><strong>Summary</strong></p> <p>Dataset of imaging data related to the publication&nbsp; Raudenska, M., Kratochvilova, M., Vicar, T., Gumulec, J., Balvan, J., Polanska, H.&nbsp;Pribyl, J. &amp; Masarik, M.:Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation. <em>Scientific Reports&nbsp;</em><strong>2019,&nbsp;</strong>9, 1660</p> <p>This dataset includes image data of <em>atomic force microcopy</em> (Young modulus) and <em>confocal microscopy</em>(staining of F-actin and &beta;-tubulin) of prostate cell lines PNT1A, 22Rv1, and PC-3.&nbsp;</p> <p><strong>Materials and Methods</strong></p> <p><em>Cells, cell culture conditions</em></p> <p>Cells confluent up to 50&ndash;60% were washed with a FBS-free medium and treated with a fresh medium with FBS and required antineoplastic drug concentration (IC50 concentration for the particular cell line). The cells were treated with 93 &micro;M (PC-3), 38 &micro;M (PNT1A), and 24 &micro;M (22Rv1) of cisplatin (Sigma-Aldrich, St. Louis, Missouri), respectively. IC50 concentrations used for treatment with docetaxel (Sigma-Aldrich, St. Louis, Missouri) were 200nM for PC-3, 70nM for PNT1A, and 150nM for 22Rv1.&nbsp;</p> <p><em>Long-term zinc (II) treatment of cell cultures</em></p> <p>Cells were cultivated in the constant presence of zinc(II) ions. Concentrations of zinc(II) sulphate in the medium were increased gradually by small changes of 25 or 50 &micro;M. The cells were cultivated at each concentration no less than one week before harvesting and their viability was checked before adding more zinc. This process was used to select zinc resistant cells naturally and to ensure better accumulation of zinc within the cells (accumulation of zinc is usually poor during the short-term treatment of prostate cancer cells). Total time of&nbsp; the cultivation of cell lines in the zinc(II)-containing media exceeded one year. Resulting concentrations of zinc(II) in the media (IC50 for the particular cell line) were 50 &micro;M for the PC-3 cell line, 150 &micro;M for the PNT1A cell line, and 400 &micro;M for the 22Rv1 cell line. The concentrations of zinc(II) in the media and FBS were taken into account.&nbsp;</p> <p><em>Actin and tubulin staining</em></p> <p>&beta;-tubulin was labeled with anti- &beta; tubulin antibody [EPR1330] (ab108342) at a working dilution of 1/300. The secondary antibody used was Alexa Fluor&reg; 555 donkey anti-rabbit (ab150074) at a dilution of 1/1000. Actin was labeled with Alexa Fluor&trade; 488 Phalloidin (A12379, Invitrogen); 1 unit per slide. For mounting Duolink&reg; In Situ Mounting Medium with DAPI (DUO82040) was used. The cells were fixed in 3.7% paraformaldehyde and permeabilized using 0.1% Triton X-100.&nbsp;</p> <p><em>Confocal microscopy</em></p> <p>The microscopy of samples was performed at the Institute of Biophysics, Czech Academy of Sciences, Brno, Czech Republic. Leica DM RXA microscope (equipped with DMSTC motorized stage, Piezzo z-movement, MicroMax CCD camera, CSU-10 confocal unit and 488, 562, and 714 nm laser diodes with AOTF) was used for acquiring detailed cell images (100&times; oil immersion Plan Fluotar lens, NA 1.3). Total 50 Z slices was captured with Z step size 0.3 &mu;m.</p> <p><em>Atomic force microscopy</em></p> <p>We used the bioAFM microscope JPK NanoWizard 3 (JPK, Berlin, Germany) placed on the inverted optical microscope Olympus IX‑81 (Olympus, Tokyo, Japan) equipped with the fluorescence and confocal module, thus allowing a combined experiment (AFM‑optical combined images). The maximal scanning range of the AFM microscope in X‑Y‑Z range was 100‑100‑15 &micro;m. The typical approach/retract settings were identical with a 15 &mu;m extend/retract length, Setpoint value of 1 nN, a pixel rate of 2048 Hz and a speed of 30 &micro;m/s. The system operated under closed-loop control. After reaching the selected contact force, the cantilever was retracted. The retraction length of 15 &mu;m was sufficient to overcome any adhesion between the tip and the sample and to make sure that the cantilever had been completely retracted from the sample surface. Force‑distance (FD) curve was recorded at each point of the cantilever approach/retract movement. AFM measurements were obtained at 37&deg;C (Petri dish heater, JPK) with force measurements recorded at a pulling speed of 30&nbsp;&micro;m/s (extension time 0.5 sec).</p> <p>The Young&#39;s modulus (E) was calculated by fitting the Hertzian‑Sneddon model on the FD curves measured as force maps (64x64 points) of the region containing either a single cell or multiple cells. JPK data evaluation software was used for the batch processing of measured data. The adjustment of the cantilever position above the sample was carried out under the microscope by controlling the position of the AFM‑head by motorized stage equipped with Petri dish heater (JPK) allowing precise positioning of the sample together with a constant elevated temperature of the sample for the whole period of the experiment. Soft uncoated AFM probes HYDRA-2R-100N (Applied NanoStructures, Mountain View, CA, USA), i.e. silicon nitride cantilevers with silicon tips are used for stiffness studies because they are maximally gentle to living cells (not causing mechanical stimulation). Moreover, as compared with coated cantilevers, these probes are very stable under elevated temperatures in liquids &ndash; thus allowing long-time measurements without nonspecific changes in the measured signal.</p> <p><em>Image analysis</em></p> <p>Fluorescence microscopy data were analyzed in ImageJ 1.52h and Python 3.7.1 as follows: cells were manually segmented using actin fluorescence channel, two regions were created for analysis: whole cell and cell periphery, lining a 4 &mu;m thick region around cell border and including most of periphery actin cytoskeleton. In these two regions following parameters were measured for both actin and tubulin fluorescence: Integrated intensity, median intensity, and following regions were measured to describe cell morphology: Cell area, Maximum caliper (max feret diameter), roundness, and aspect ratio. Moreover, stress fibers were manually segmented in every cell and following parameters were measured: number of fibers per cell, feret angle of fiber, integrated intensity, fiber length, mean intensity. Next, a standard deviation of feret angles of individual fibers was calculated relatively to mean of feret angle using a circstd function from scipy package for Python.</p> <p><strong>Identification of files</strong></p> <p><em>Microscopy data</em></p> <p>Files are separated into individual zip files. The dataset of <em>confocal microscopy </em>is separated based on treatments: untreated control, docetaxel-treated cells, cisplatin-treated cells, zinc-treated cells. Filenames&nbsp;actin_tubulin_Zstack_cisplatin.zip, actin_tubulin_Zstack_untreated_control.zip,&nbsp;actin_tubulin_Zstack_zinc.zip,&nbsp;actin_tubulin_Zstack_docetaxel.zip. Files included in these ZIP archives are named as follows: &quot;cellline_treatment_FOV&quot;. Files are 3-layer 16bit tiff files with layer sequence as follows: F-Actin (Phalloidin)/b-tubulin/Hoechst 33342. The dataset contains 242 FOVs of three cell line types/three treatments + one control, files are Z-stacks made of 50 slices.</p> <p>The dataset&nbsp;of <em>atomic force microscopy </em>(AFM) is included in one ZIP archive &quot;AFM_YoungModulus_SetpointHeight.zip&quot;, which includes data on Young modulus and Setpoint Height of cell lines 22Rv1, PNT1A and PC-3 and treatments zinc, docetaxel, cisplatin (+control), i.e. identical like for confocal microscopy. The file naming is as follows: &quot;AFM_cellline_treatment_FOV_Youngmodulus.tif&quot;&nbsp; for Young modulus and &quot;AFM_cellline_treatment_FOV_setpointheight.tif&quot; for setpoint height. The data are filtered 32-bit tiff images, where the pixel value correspond to cell stiffness (young modulus) in Pa or setpoint height in m.</p> <p><em>Confocal microscopy analysis files</em></p> <p>Following files are csv tables including image analysis of actin/tubulin staining captured by confocal microscope:</p> <p>Cytoskeleton_fluo_analysis_Cell_Cell_periphery_morphology.csv: table includes analyzed data for actin and tubulin staining in following cellular regions: cell, cell periphery. Standard ImageJ parameters regarding intensity and morphology included.</p> <p>Cytoskeleton_fluo_analysis_Fibers.csv: table includes results of manual segmentation and consequent analysis of actin stres fibers in the cells. Apart from standard ImageJ parameters, also number of stress fibers per cell and standard deviation of fiber angle relative to the cell mean angle (for details see methods) are included.</p>

opencc-by-4.0Nov 2018View details →
zenodo48/100

Gridded depth and accumulation products from dated airborne radar stratigraphy over West Antarctica during the mid-Holocene, v.1.0.0

<p>This dataset comprises of codes (written in MATLAB) and gridded files (exported as GeoTIFF) presented in Bodart et al. (2023; The Crysophere; <a href="https://doi.org/10.5194/tc-2022-199">https://doi.org/10.5194/tc-2022-199</a>). A summary of the key findings from this study is provided as follows:</p> <p>&quot;Using a spatially extensive IRH over Pine Island Glacier, Thwaites Glacier, and Institute and M&ouml;ller Ice Streams (covering a total of 610 000 km2 or 30% of the WAIS), and a local layer approximation model, we infer mid-Holocene accumulation rates over the slow-flowing parts of these catchments for the past ~4700 years. By comparing our results with modern climate reanalysis models (1979 &ndash; 2019) and observational syntheses (1651 &ndash; 2010), we estimate that accumulation rates over the Amundsen-Weddell-Ross divide were on average 18% higher during the mid-Holocene than modern rates. However, no significant spatial changes in the accumulation pattern were observed.&quot;</p> <p>This&nbsp;dataset contains a series of files (5x .m files, 10x .tif files). The numbering of the figures in the description below refers to the order of the figures in the associated paper.</p> <ul> <li><strong>&nbsp;5x&nbsp;MATLAB files:</strong> <ul> <li><strong>Calculate_accumulation_rates.m</strong>: calculates accumulation rates for the mid-Holocene-to-present, as well as uncertainties associated with the age and model structural uncertainty;</li> <li><strong>Calculate_D_parameter.m</strong>: calculates the D parameter (and associated L_path, L_H and L_b) to assess the feasability of the LLA over our grid;</li> <li><strong>Calculate_longitudinal_strain_rates.m</strong>: calculates the longitudinal strain rates over our grid from modern ice-flow velocities;</li> <li><strong>Calculate_vertical_strain_rates.m</strong>: calculates vertical strain rates for the mid-Holocene-to-present part of the ice column from accumulation estimates;</li> <li><strong>Resample_IRH_data.m</strong>: Re-samples the along-track IRH data into evenly distributed 500-m points for speeding up the gridding and calculations of accumulation rates;<br> &nbsp;</li> </ul> </li> <li><strong>10x GeoTIFF files:</strong> <ul> <li><strong>Holocene_IRH_depth_Fig2a.tif:&nbsp;</strong>Figure 2a;</li> <li><strong>Holocene_accumulation_rates_Fig3a.tif:</strong>&nbsp;Figure&nbsp;3a;</li> <li><strong>Difference_Holocene_accumulation_RACMO2_Fig3c.tif:</strong>&nbsp;Figure 3c;</li> <li><strong>Relative_difference_Holocene_accumulation_RACMO2_Fig4.tif:</strong>&nbsp;Figure 4;</li> <li><strong>D_parameter_FigS1d.tif:</strong>&nbsp;Figure S1d;</li> <li><strong>Holocene_vertical_strain_rates_FigS2a.tif:&nbsp;</strong>Figure S2a;</li> <li><strong>Longitudinal_strain_rates_FigS2b.tif:</strong>&nbsp;Figure S2b;</li> <li><strong>Holocene_accumulation_lower_uncertainty_FigS4a.tif:</strong>&nbsp;Figure&nbsp;S4a;</li> <li><strong>Holocene_accumulation_upper_uncertainty_FigS4b.tif:</strong>&nbsp;Figure&nbsp;S4b;</li> <li><strong>Holocene_accumulation_relative_uncertainty_FigS4c.tif:&nbsp;</strong>Figure S4c;</li> </ul> </li> </ul> <p>Please also cite the associated paper when using this dataset.</p> <p>Any questions, please direct them to the corresponding author,&nbsp;Julien Bodart (julien.bodart@ed.ac.uk).</p>

opencc-by-4.0Mar 2023View details →
edi48/100

Uranium mobility and accumulation along the Rio Paguate, Jackpile Mine in Laguna Pueblo, NM

The mobility and accumulation of uranium (U) along the Rio Paguate, adjacent to the Jackpile Mine, in Laguna Pueblo, New Mexico was investigated using aqueous chemistry, electron microprobe, X-ray diffraction and spectroscopy analyses. Given that it is not common to identify elevated concentrations of U in surface water sources, the Rio Paguate is a unique site that concerns the Laguna Pueblo community. This study aims to better understand the solid chemistry of abandoned mine waste sediments from the Jackpile Mine and identify key hydrogeological and geochemical processes that affect the fate of U along the Rio Paguate. Solid analyses using X-ray fluorescence determined that sediments located in the Jackpile Mine contain ranges of 320 to 9200 mg kg-1 U. The presence of coffinite, a U(IV)-bearing mineral, was identified by X-ray diffraction analyses in abandoned mine waste solids exposed to several decades of weathering and oxidation. The dissolution of these U-bearing minerals from abandoned mine wastes could contribute to U mobility during rain events. The U concentration in surface waters sampled closest to mine wastes are highest during the southwestern monsoon season. Samples collected from September 2014 to August 2016 showed higher U concentrations in surface water adjacent to the Jackpile Mine (35.3 to 772 mg L-1) compared with those at a wetland 4.5 kilometers downstream of the mine (5.77 to 110 mg L-1). Sediments co-located in the stream bed and bank along the reach between the mine and wetland had low U concentrations (range 1–5 mg kg-1) compared to concentrations in wetland sediments with higher organic matter (14–15%) and U concentrations (2–21 mg kg-1). Approximately 10% of the total U in wetland sediments was amenable to complexation with 1 mM sodium bicarbonate in batch experiments; a decrease of U concentration in solution was observed over time in these experiments likely due to re-association with sediments in the reactor. The findings from this study pro

openCC (other)Dec 2019View details →
edi48/100

Annual bedload accumulation from sediment basin surveys in small gauged watersheds in the Andrews Experimental Forest, 1957 to present

Sediment debris basins are established within the Andrews Experimental Forest as part of paired watershed experiments examining differences in streamflow and nutrient chemistry due to timber harvest. Basins are constructed below the stream gaging station in each of five basins, and these basins and the deposits of sediment within them are re-surveyed or emptied annually to measure bedload sediment production. Basins are measured on Watersheds 1, 2 (control) and 3 beginning with wateryear 1957 and on Watersheds 9 (control) and 10 beginning wateryear 1974. Data collection is ongoing at an annual time step. Data provided include the watershed name, wateryear, survey method, watershed area, annual bedload volume and accumulation rate. These data display both the chronic production of sediment, as well as pulsed, episodic bedload from landslides within the contributing basins.

openCC (other)Oct 2019View details →
edi48/100

Post-logging community structure and biomass accumulation in Watershed 10, Andrews Experimental Forest , 1974 to present

Old-growth and mature Douglas-fir forest were clearcut logged in 1975. Large slash was removed from the site rather than burned. Douglas-fir seedlings were planted in 1976 and 1977, but due to poor survival 4.9 ha were replanted in 1978. Despite planting, most tree stems originated naturally, either as sprouts from cut stumps (hardwoods) or as natural regeneration (conifers and hardwoods). Study plots were established and sampled for cover and frequency of understory vegetation and counts of seedlings and saplings prior to harvest (1973) and resampled annually for cover and biomass of understory vegetation and tree growth from 1976-1981, then in 1983, 1985, and then in 4-6 year intervals. WS10 was intensively studied in the 1970’s and 80’s. The entire watershed was surveyed into a 25 x 25-m grid and then 36 15 by 10 meter plots were established for long-term sampling.

openCC (other)Aug 2019View details →
edi48/100

Stream discharge and bedload accumulation in gauged watersheds at the South Umpqua Experimental Forest, Coyote Creek, 1963 to 1981 and 2001 to present

Stream discharge is collected on four small watersheds in the Coyote Creek drainage within the South Umpqua Experimental forest in the southwest Oregon Cascades. Stream discharge data was started in October 1963 and discontinued in June 1981 (discontinued April 1985 on Watershed 4). Stream discharge measurement was resumed in December 2000 on all four watersheds. Watersheds 1, 2, and 3 were harvested with differing silvicultural methods in summer 1971, and watershed 4 is the control. High resolution temporal data is provided as well as daily, monthly and annual summary data. Streamflow data by sampling intervals are also provided from 1970 to 1981 when stream water chemistry data were being collected. Annual bedload accumulation totals from each of the four watersheds is also provided beginning 2001.

openCC (other)Oct 2019View details →
edi48/100

Periphyton Accumulation Rates from Shark River Slough, Taylor Slough and Florida Bay, Everglades National Park (FCE LTER), South Florida, USA, January 2001 - ongoing

Periphyton accumulation rates were measured quarterly at FCE LTER sites in SRS and TS/Ph marshes (SRS 1-3, TS/Ph 1-3) and the seagrass meadows of Florida Bay (TS/Ph 9-11). Glass slides were used as artificial substrates for periphyton growth. Twenty slides were incubated for 2 months in triplicate periphytometers (flow-through plastic boxes) at the surface (marsh sites) and bottom (seagrass sites) at each site. In addition, at seagrass sites, twelve artificial seagrass blades were incubated for two months in triplicate at each site. Blades were made from strips of transparency film anchored to the bottom and floating upward toward the surface by use of a styrofoam bead on the top of the blade. Data are presented in terms of grams dry and ash-free dry mass accumulated per area per time, as well as the chlorophyll a content of the dry mass and its rate of accumulation. Total phosphorus content of accumulated periphyton is also provided. This is part of continuous data collection to test the hypothesis that phosphorus availability and hydroperiod influence periphyton production in the Everglades.

openCC (other)Feb 2026View details →
edi48/100

Periphyton Biomass Accumulation from the Shark River and Taylor Sloughs, Everglades National Park (FCE LTER), South Florida, USA, January 2003 - ongoing

Periphyton biomass was measured quarterly at three replicate locations (1, 2, and 3) at FCE LTER marsh sites (SRS 1-3; TS/Ph 1-3). A 1-m2 plot was placed in the marsh and percent cover of periphyton was visually estimated, including cover on the water surface (floating), plant stems (epiphytic), and on the bottom (benthic). Periphyton was then harvested from the quadrats into a 2000 ml perforated graduated cylinder and the volume measured. A 120-ml subsample was removed and taken back to the laboratory for analysis. Data provided include percent cover by substrate, dry, ash, and ash-free dry mass per area, chlorophyll a per gram ash-free dry mass and per area, and the total phosphorus, nitrogen and carbon concentration on a dry weight basis. This is part of a continuous data collection to test the hypothesis that phosphorus and hydrology interact to influence periphyton abundance in Everglades marshes.

openCC (other)Jan 2026View details →
edi48/100

Biomass accumulation in trees and downed wood at Bartlett Experimental Forest, Hubbard Brook Experimental Forest, the Bowl Natural Research Area, and the White Mountain National Forest, NH, USA

Standing trees and downed wood were inventoried in all of the chronosequence stands in the White Mountains, New Hampshire to characterize biomass. Live and standing dead trees were inventoried in the chronosequence stands in 1994, 2004, 2012, and 2021. Coarse (≥ 7.6 cm diameter) and fine woody debris (3.0 – 7.6 cm) were inventoried at the same stands in 2004 and 2020. Twigs (FWD < 3.0 cm) were inventoried in 2004 and 2020. The Bowl and Mt. Pond old-growth sites were inventoried (standing trees and downed wood) in 2021.

openCC (other)Aug 2023View details →
edi48/100

PAB04 Aboveground primary productivity of tallgrass prairie based on accumulated plant biomass on miscellaneous LTER watersheds

Data set contains estimates of end-of-season standing crop biomass (grams per square meter) of live graminoids, forbs, woody plants, current year's dead, and previous year's dead vegetation for 2 soil types (shallow and deep) on watersheds of various burning-grazing treatments. Twenty quadrats (0.1 square meters) are harvested for each soil/treatment type. NOTE: Early (April) and mid-season (July) biomass was collected from 1983-1988, and these data are vailable by request.

openCC0Dec 2024View 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