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110 results for “river sediment”
Water column nitrate and ammonium concentrations, sediment oxygen, di-nitrogen (gas), nitrate, nitrite, ammonium, phosphate, and silicate flux from sealed, whole core incubations, Rowley River, Rowley, MA.
Tidal flats are critical components of coastal estuarine ecosystems characterized by high rates of benthic primary productivity and biogeochemical cycling. In order to investigate the impact of anthropogenic nutrient loading on tidal flat biogeochemistry we carried out a two-week fertilization experiment. Throughout the course of the study we conducted two light-dark, whole-core incubations and took measurements of three indicators of microphytobenthos activity in addition to quantifying the resident eastern mud snail (Ilyanassa obsoleta) population.
Sediment porewater nutrients, sulfide, pH, and alkalinity in the Parker and Rowley River, Massachusetts
Measurements of sediment porewater nutrient, sulfide, pH, and alkalinity, 1993 -2004, at a variety of sites and salinities throughout the Plum Island Sound estuary.
Sediment redox potential in the Parker and Rowley River, Massachusetts
Measurements of sediment redox potential at 4 stations along a transect of the Parker River and near the mouth of the Rowley River, Newbury and Rowley, Massachusetts during 1993 and 1994.
PIE LTER, Year 2013-2018, remote sensing derived sediment concentration maps, movies, transect averaged sediment concentation, water level, dh/dt, wind direction and speed, river discharges at Plum Island Sound, Massachusetts.
PIE LTER, Year 2013-2018, remote sensing (Landsat8 OLI sensors and Sentinel-2A/2B) derived sediment concentration maps, transect averaged sediment concentation, water level, dh/dt, wind direction and speed, river discharges for Plum Island Sound estuary, Massachusetts.
A genome catalogue of mercury-methylating bacteria and archaea from sediments of a boreal river facing human disturbances
<p>Methyl mercury is a toxic compound produced by anaerobic microbes that biomagnifies in aquatic food webs, impacting animal and human health. Genome-based explorations of Hg methylators remain limited, particularly in the context of river ecosystems. To fill this knowledge gap, we created a genome catalogue of putative Hg-methylating microorganisms (based on the presence of <em>hgcAB</em>) from the sediments of a river impacted by two run-of-river hydroelectric dams, logging, and a wildfire. By using genome-resolved metagenomics, we uncovered a unique and diverse assemblage of Hg methylators dominated by members of the metabolically versatile Bacteroidota and particularly enriched in butyrate fermentative microbes. By comparing diversity and abundance of Hg methylators between sites that were subjected to different disturbances, we found that ongoing disturbances, such as input of organic matter related to logging activities. were particularly favorable to the establishment of a Hg-methylating niche. Lastly, for a deeper understanding of the environmental factors shaping Hg methylator diversity, we juxtaposed the Hg-methylating genome catalogue with the wider microbial community. The results suggest that Hg methylators respond to environmental conditions similarly to overall microbial community, and therefore it is crucial to interpret the diversity and abundance of Hg methylators within their specific ecological context.</p>
Dataset for 'Can restoring water and sediment fluxes across a mega-dam cascade alleviate a sinking river delta?'
<p>Please cite this dataset and corresponding manuscript at <a href="https://doi.org/10.1126/sciadv.adn9731">10.1126/sciadv.adn9731</a> if data were used in any way.</p> <p>Correspondence to Prof Lu Xi Xi at geoluxx@nus.edu.sg</p>
Data and code for the publication "Microplastics in water and sediments at the confluence of the Elbe and Mulde rivers in Germany"
<p><strong>Background</strong></p> <p>The data set contains data on visual and chemical analysis of sediment and water samples taken at the confluence of the Elbe and the Mulde rivers in Germany. It was analysed in the paper by H. Laermanns, G. Reifferscheid, J. Kruse, C. Földi, G. Dierkes, D. Schaefer, C. Scherer, C. Bogner and F. Stock, 2021, “Microplastics in water and sediments at the confluence of the Elbe and Mulde rivers in Germany” (<a href="https://doi.org/10.3389/fenvs.2021.794895">https://doi.org/10.3389/fenvs.2021.794895</a>) published in Frontiers in Environmental Science, Research Topic: “Plastics in Aquatic Systems: from Transport and Fate to Impacts and Management Perspectives”.</p> <p> </p> <p><strong>Description of the dataset</strong></p> <p>The data is available in the folder <strong>data_and_results.zip</strong>, and there in the folder <strong>data</strong>. The folder <strong>pyrolysis</strong> contains the file</p> <ul> <li><strong>pyr-gc-ms_raw.csv</strong>. This is the pyrolysis analysis (see description in the paper for technical details). The calibration data are part of the supplemental material of the paper and can be downloaded there.</li> </ul> <p>The folder <strong>visual_analysis</strong> contains the files</p> <ul> <li><strong>elbe_filter_photos_complete_v2.csv</strong>: IDs of samples, number of the photographs of filters, shapes of particles located on the filter</li> <li><strong>elbe_samples_v2.csv</strong>: IDs of samples, medium (water or sediment sample), location and side (left or right riverside) of sampling, sampling tool, sampled volume and mesh size.</li> </ul> <p>The folder <strong>results</strong> contains the figures produced by the R code (see <strong>Description of the code</strong>).</p> <p> </p> <p><strong>Description of the code</strong></p> <p>The file <strong>MP_visual_and_chemical_analysis.Rmd</strong> is the R notebook we wrote for the analysis. For information on the software version, see <strong>Information on software version </strong>below<strong>.</strong></p> <p> </p> <p><strong>Disclaimer</strong></p> <p>The data and code are provided as is without any warranty.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We thank the staff of the BfG laboratory for their support during the pyr-GC-MS analysis. Julia Horn helped with geochemical and sedimentological measurements in the laboratory of the Institute of Geography at the University of Cologne.</p> <p> </p> <p><strong>Funding</strong></p> <p>This study is embedded in the Project “Micro- and macroplastic in federal water ways of Germany” (Project 4.1.12, Project No. M39620304028) that intends to analyse the occurrence, transport mechanism, ecological risks and management options. This project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project Number 391977956, SFB 1357.</p> <p> </p> <p><strong>References</strong></p> <p>Hannes Laermanns, Georg Reifferscheid, Jonas Kruse, Corinna Földi, Georg Dierkes, Dirk Schaefer, Christian Scherer, Christina Bogner and Friederike Stock, 2021, Microplastics in water and sediments at the confluence of Elbe and Mulde rivers in Germany, <a href="https://doi.org/10.3389/fenvs.2021.794895">https://doi.org/10.3389/fenvs.2021.794895</a></p> <p>R Core Team, 2021, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, https://www.R-project.org/</p> <p> </p> <p><strong>Information on software version</strong></p> <p>sessionInfo()</p> <p>R version 4.1.0 (2021-05-18)<br> Platform: x86_64-pc-linux-gnu (64-bit)<br> Running under: Ubuntu 20.10</p> <p>Matrix products: default<br> BLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3<br> LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3</p> <p>locale:<br> [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C <br> [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=de_DE.UTF-8 <br> [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 <br> [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C <br> [9] LC_ADDRESS=C LC_TELEPHONE=C <br> [11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C </p> <p>attached base packages:<br> [1] stats graphics grDevices utils datasets<br> [6] methods base </p> <p>other attached packages:<br> [1] lubridate_1.8.0 patchwork_1.1.1 ggforce_0.3.3 <br> [4] gridExtra_2.3 RColorBrewer_1.1-2 forcats_0.5.1 <br> [7] stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 <br> [10] readr_2.0.2 tidyr_1.1.4 tibble_3.1.6 <br> [13] ggplot2_3.3.5 tidyverse_1.3.1 </p> <p>loaded via a namespace (and not attached):<br> [1] httr_1.4.2 sass_0.4.0 bit64_4.0.5 <br> [4] vroom_1.5.5 jsonlite_1.7.2 modelr_0.1.8 <br> [7] bslib_0.3.1 assertthat_0.2.1 highr_0.9 <br> [10] cellranger_1.1.0 yaml_2.2.1 sessioninfo_1.1.1<br> [13] pillar_1.6.4 backports_1.2.1 glue_1.5.0 <br> [16] digest_0.6.28 polyclip_1.10-0 rvest_1.0.0 <br> [19] colorspace_2.0-2 htmltools_0.5.2 pkgconfig_2.0.3 <br> [22] broom_0.7.6 haven_2.4.1 scales_1.1.1 <br> [25] tweenr_1.0.2 tzdb_0.2.0 generics_0.1.1 <br> [28] farver_2.1.0 ellipsis_0.3.2 withr_2.4.2 <br> [31] cli_3.1.0 magrittr_2.0.1 crayon_1.4.2 <br> [34] readxl_1.3.1 evaluate_0.14 fs_1.5.0 <br> [37] fansi_0.5.0 MASS_7.3-54 xml2_1.3.2 <br> [40] tools_4.1.0 hms_1.1.1 lifecycle_1.0.1 <br> [43] munsell_0.5.0 reprex_2.0.0 compiler_4.1.0 <br> [46] jquerylib_0.1.4 rlang_0.99.0.9000 grid_4.1.0 <br> [49] rstudioapi_0.13 labeling_0.4.2 rmarkdown_2.11 <br> [52] gtable_0.3.0 DBI_1.1.1 R6_2.5.1 <br> [55] knitr_1.36 fastmap_1.1.0 bit_4.0.4 <br> [58] utf8_1.2.2 rprojroot_2.0.2 desc_1.3.0 <br> [61] stringi_1.7.5 parallel_4.1.0 Rcpp_1.0.7 <br> [64] vctrs_0.3.8 dbplyr_2.1.1 tidyselect_1.1.1<br> [67] xfun_0.28</p>
Dereplicated Metagenome assembled genomes (MAGs) from Columbia River hyporheic sediments
<p>Fasta file containing 55 metagenome assembled genomes (MAGs) from publication to be submitted titled "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
Freshwater viral metagenome assembled genomes (vMAGs) used for vContact2 analysis in publication Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments
<p>This dataset contains all freshwater viruses that were mined from publicly available data in an effort to provide biogeographical context to viral communities identified from the Columbia River. These two files include data from:</p> <p>1) East River, CO (PRJNA579838)</p> <p>2) A previous study from the Columbia River, WA (PRJNA375338)</p> <p>3) Prairie Potholes, ND (PRJNA365086)</p> <p>4) Amazon River (PRJNA237344)</p> <p> </p> <p>Manuscript title Genome-resolved metaproteomics decodes the microbial and viral contributions to coupled carbon and nitrogen cycling in river sediments</p>
Grain size distribution of Amazon river sediment samples collected over the period 2005-2008; and ADCP water velocity profiles collected on the major tributaries of the Amazon in Bolivia and Peru, 2007-2008
<p>This dataset contains two items:</p> <p>- The grain size distribution of river sediment samples collected along the Amazon River and its tributaries during four sampling campaigns performed in June 2005 (lower Amazon, Brazil), March 2006 (lower Amazon, Brazil), May 2007 (Upper Madeira, Bolivia), and April 2008 (Upper Solimões-Amazonas, Peru). [spreadsheet "Grain_size_distribution_dataset_Amazon_2005-2008_Bouchez_data.xlsx"].</p> <p>- River water velocity profiles derived from Acoustic Doppler Current Profiler (ADCP) measurements performed on the major tributaries of the Amazon in May 2007 (Upper Madeira, Bolivia) and April 2008 (Upper Solimões-Amazonas, Peru) [folder "ADCP_dataset_Amazon_2007-2008_Bouchez_data"].</p> <p>The dataset description and the relevant references are provided in the text files "Grain_size_distribution_dataset_Amazon_2005-2008_Bouchez_description.docx" and "ADCP_dataset_Amazon_2007-2008_Bouchez_description.docx" .</p> <p>These data were acquired thanks to the support of the French National Service for Observation "HYBAM" ("Hydrogeochemistry of the Amazon Basin"), part of the CNRS National Infrastructure "OZCAR" ("Critical Zone Observatories: Applications and Research").</p>
GTDB-Tk Phylogenetic Information for 102 MAGs from Columbia River hyporheic sediments
<p>These are the phylogenetic analyses output for the GTDB-Tk that was run on the 102 MAGs from the Columbia River Hyporheic Zone. They form part of supplementary material from publication titled "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
River bed sediment and debris flow deposit lithology and Schmidt Hammer Rock Strength dataset, Suiattle River, Washington State, USA
<p>This dataset includes measurements of river bed sediment lithology and Schmidt Hammer Rock Strength (SHRS), as well as debris flow deposit lithology, grain size, and SHRS, at sites along the Suiattle River, North Cascades, Washington State, USA. See Pfeiffer et al. (2022, JGR-ES) for further description of the collection methodology and site description.</p>
Data of sediment load in Yangtze River basin
<p>Time series of annual sediment load(Mt/yr) at the 13 key gauging stations in the Yangtze River basin during 1970–2017</p>
Relative roles of sediment transport and localized erosion on phosphorus load in the lower Susquehanna River and its mouth in the Chesapeake Bay, USA
<p>Data set includes average wind and wave conditions for the mouth of the Susquehanna River that were used to calculate normal and storm conditions; turbidity measurements at each site; mass of particulate matter from water column and erosion experiments; inorganic phosphate from sequential extraction of particulate matter in water column, sediment, and erosion experiments; and δ<sup>15</sup>N, δ<sup>13</sup>C, and C:N ratios of particulate matter from the water column and from erosion experiments.</p>
Bottom water mediated microplastics distribution in water and sediment in the Yangtze River Estuary and East China Sea
<p>This database included the original data of water parameters, microplastics abundance, microplastics size, shape, color and shape. </p>
The past and future changes of river sediment in the U.S. Mid-Atlantic
<p><a href="../api/records/12597593/draft/files/E3SM-tanzeli-lnd-elm-erosion-v3.zip/content" target="_blank" rel="noopener noreferrer">E3SM-tanzeli-lnd-elm-erosion-v3.zip</a>: Model code</p> <p><a href="../api/records/12597593/draft/files/domain_lnd_Mid-Atlantic_MPAS_c220107.nc/content" target="_blank" rel="noopener noreferrer">domain_lnd_Mid-Atlantic_MPAS_c220107.nc</a>: Mid-Atlantic mesh grid</p> <p><a href="../api/records/12597593/draft/files/ancillary.pk/content" target="_blank" rel="noopener noreferrer">ancillary.pk</a>: ancillary variables including "area" (grid cell area: m^2), "areaTotal" (upstream drainage area: m^2), "DSIG" (downstream index), "GINDEX" (grid cell index), "outletG" (river basin index), and "rlen" (river channel length: m).</p> <p><a href="../api/records/12597593/draft/files/Baseline.pk/content" target="_blank" rel="noopener noreferrer">Baseline.pk</a>: Baseline simulation: "Q": discharge (m^3/s), "Qs": sediment discharge (kg/s)</p> <p><a href="../api/records/12597593/draft/files/CLIM_noLU_noDAM.pk/content" target="_blank" rel="noopener noreferrer">CLIM_noLU_noDAM.pk</a>: CLIM_noLU_noDAM simulation</p> <p><a href="../api/records/12597593/draft/files/noCLIM_LU_noDAM.pk/content" target="_blank" rel="noopener noreferrer">noCLIM_LU_noDAM.pk</a>: noCLIM_LU_noDAM simulation</p> <p><a href="../api/records/12597593/draft/files/noCLIM_noLU_DAM.pk/content" target="_blank" rel="noopener noreferrer">noCLIM_noLU_DAM.pk</a>: noCLIM_noLU_DAM simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_UKESM1-0-LL.pk/content" target="_blank" rel="noopener noreferrer">SSP585_UKESM1-0-LL.pk</a>: SSP585_UKESM1-0-LL simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_MPI-ESM1-2-HR.pk/content" target="_blank" rel="noopener noreferrer">SSP585_MPI-ESM1-2-HR.pk</a>: SSP585_MPI-ESM1-2-HR simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_GFDL-ESM4.pk/content" target="_blank" rel="noopener noreferrer">SSP585_GFDL-ESM4.pk</a>: SSP585_GFDL-ESM4 simulation</p> <p><a href="../api/records/12597593/draft/files/SSP585_IPSL-CM6A-LR.pk/content" target="_blank" rel="noopener noreferrer">SSP585_IPSL-CM6A-LR.pk</a>: SSP585_IPSL-CM6A-LR simulation</p> <p><a href="../api/records/12597593/draft/files/draw_ssc_channel_vari4pub.py/content" target="_blank" rel="noopener noreferrer">draw_ssc_channel_vari4pub.py</a>: Python script to plot longitudinal SSC variations</p> <p><a href="../api/records/12597593/draft/files/cmp_qs_icom_future4pub.py/content" target="_blank" rel="noopener noreferrer">cmp_qs_icom_future4pub.py</a>: Python script to plot future sediment discharge change</p>
NMR data for Columbia River Sediments
<p>Columbia River Sediments NMR data files, including 1D and 2D XX.fid files, as well as mnova files. Link to manuscript will be made available upon publication. </p>
Viral metagenome assembled genomes (vMAGs) from Columbia River hyporheic sediments
<p>Fasta file containing 111 viral metagenome assembled genomes (vMAGs) from publication to be submitted titled "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
Metagenome assembled genome (MAG) annotations for Columbia River sediment bacteria and archaea
<p>Excel spreadsheet containing all annotations for metagenome assembled genomes (MAGs) that form part of a publication to be submitted titled: "<strong>Microbial genome-resolved metaproteomic analyses frame intertwined carbon and nitrogen cycles in river hyporheic sediments". </strong></p>
Tectonic and magmatic evolution of NE Cathaysia Block controls sediment geochemical heterogeneity of rivers in SE China
<p>The supplementary data of the manuscript: <strong>Tectonic and magmatic evolution of NE Cathaysia Block controls sediment geochemical heterogeneity of rivers in SE China</strong></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.