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Plant and root biomass, nitrogen, carbon, and phosphorus concentrations in a mesic acidic tussock tundra experimental site established in 1981(MAT81) and harvested in 2015, Arctic LTER, Toolik Lake, Alaska.
Plant and root biomass, nitrogen, carbon, and phosphorus were measured in 2015 in the Arctic LTER tussock tundra experimental site (MAT81). This site was established in 1981 and has been harvested in previous years (see Shaver and Chapin Ecological Monographs, 61(1), 1991, pp.1-31, https://doi.org/10.2307/1942997). Data tables include the biomass for each harvested quadrat and block summaries for percent carbon, nitrogen, and phosphorus for control and fertilized plots from the original 4-block design. New control plots, established in 2015, are in a separate data table and include biomass, percent carbon, nitrogen, and phosphorus for each quadrat.
Fine particulate matter (PM2.5) concentrations in downtown Phoenix, Arizona (USA) on August 20, 2024
This dataset contains a collection of estimated particulate matter (PM2.5) concentrations for downtown Phoenix, Arizona (USA), on a typical summer day (August 20, 2024) at three critical times of day (7 a.m., 1 p.m., and 5 p.m.). The 100-m resolution estimates were generated using a pre-trained support vector regression model. This dataset can inform public health interventions related to air quality.
Concentrations, turnover rates and fluxes of polyamines in coastal waters of the South Atlantic Bight during April and October 2011
Polyamines are short-chain aliphatic compounds containing multiple amine groups. They are important components of the cytosol of eukaryotes and are present at mmol/L concentrations inside phytoplankton cells, while complex polyamines play a role in biosilica deposition. Concentrations of polyamines measured in seawater are typically in the sub nmol/L range, implying rapid and efficient uptake by osmotrophs, likely bacterioplankton. We measured turnover rates of three polyamines (putrescine, spermidine and spermine) using 3H-labeled compounds and determined their concentrations by HPLC to estimate polyamine contributions to dissolved organic matter and bacterioplankton carbon and nitrogen demand. These measurements were made on transects from the inner shelf to the Gulf Stream across the South Atlantic Bight (SAB) during April and October of 2011 and in salt marsh estuaries on the Georgia coast during August of 2011 and April of 2012. This data set includes measurements of water column variables (temperature, salinity, biogenic Silica), nutrients (nitrite, nitrate+nitrite, ammonium and dissolved inorganic nitrogen), and concentrations and turnover rates of polyamine compounds.
Summary statistics and annual trends in chloride concentration in urban Minnesota lakes and streams
These data tables describe statistical summaries of chloride concentration, temporal trends in annual chloride, and projected risk of future chloride pollution in lakes and streams of the 17 most urban counties in Minnesota. Data were summarized separately for lakes and for streams, and include statistics (mean, median, standard deviation, upper and lower confidence intervals, and maximum) over the entire data record, over the warm season (May - October), and over the most recent 5 years (i.e., since 2018). Trends were computed on annual means and medians. For lakes, data were aggregated by lake basin (MN DNR Lake ID, or DOW) as well as by depth of sample (surface and deep). For streams, data were aggregated by individual site level as well as by stream reach (per MN Pollution Control Agency assessment units). Risk of chloride pollution was also determined for sites with longer records (10+ years) based on current concentration, number of exceedances of chronic standards, and projected chloride concentration based on current trends. Raw data were extracted from two sources: (1) the National Water Quality Portal (USGS & EPA) and (2) the Metropolitan Council Environmental Information Management System. The data were originally collected by a large number of entities, including watershed management authorities in the state of Minnesota, tribal groups, the Minnesota Pollution Control Agency, municipalities, university researchers, private consultants, and the Metropolitan Council. Some data records begin as early as the 1950's or 1960's, with many sites still including active data collection. A total of approximately 45,000 observations of chloride were included for lakes and wetlands, and approximately 70,000 observations for streams. Nearly 1600 stream sites and 700 lake/wetland sites were represented in the raw data, with 356 stream sites and 600 lakes represented in the summaries (after filtering out sites with less than 1 year of data collection). Primary data retr
A Global database of methane concentrations and atmospheric fluxes for streams and rivers
This dataset, referred to as MethDB, is a collation of publicly available values of methane (CH4) concentrations and atmospheric fluxes for world streams and rivers, along with supporting information on location, geographic, physical, and chemical conditions of the study sites. The data set is composed of four linked tables, corresponding to the data sources (Papers_MethDB), the study sites (Sites_MethDB), concentrations (Concentrations_MethDB), and influx/efflux rates (Fluxes_MethDB). Information was extracted from journal articles, government reports, book chapters, and similar sources that were acquired before 15 September 2015. Concentrations and fluxes were converted to a standard unit (micromoles per liter for concentration and millimoles per square meter per day for flux) and both the author-reported and converted data are included in the database. MethDB was assembled as part of a larger synthesis effort on stream and river CH4 dynamics, and assembled data were used to identify large-scale patterns and potential drivers of fluvial CH4 and to generate an updated global-scale estimate of CH4 emissions from world rivers.
Chloride Concentrations, Conductivity, and Water Temperature Data from Upper Yahara River Watershed Tributaries in Dane County, WI: December 2019 – April 2021
Conductivity and chloride were measured for 2 years in nine tributaries of Lake Mendota and Lake Monona in Dane County, WI. HOBO Conductivity loggers continuously measured absolute conductivity and water temperature every 30 minutes. Breaks in data collection were due to a calibration period or if the loggers were out of the water. Grab samples for chloride concentration occurred weekly or biweekly. Conductivity and water temperature were measured with a field meter at each sampling excursion. This data was needed for a master’s research thesis with the goal of characterizing the spatial distribution and loading of chloride in the Upper Yahara River Watershed.
Soil nitrous oxide and carbon dioxide concentration data for Niwot Ridge and Loch Vale watershed, 1994.
Concentrations of carbon dioxide and nitrous oxide from snow-covered alpine soil surfaces were measured at Niwot Ridge. Six sites characterized by relatively shallow snowpacks were sampled in 1993. A total of 27 sites were sampled in 1994. Nine of the 1994 sites were located in the naturally shallow snowfield sampled in 1993, 9 sites were located in a formerly shallow snowpack site where snow depth was augmented by the construction of a 2.8-m high, 60-m long snowfence, and the 9 remaining sites were located in a naturally deep snowpack. Concentrations of N2O and CO2 at the soil surface were measured monthly from January until March, biweekly through April, and weekly until snowmelt was complete. Elevated levels of CO2 under the snowpack, suggesting microbial activity, were first observed under the shallow snowpacks in early March of 1993. N2O production under snow was first observed in April 1993, when soil temperatures had warmed above -3 degrees C. In 1994 shallow snowpack sites exhibited diminished and sporadic production of both CO2 and N2O, apparently due to the inconsistent snow cover compared to 1993. The snowfence sites exhibited elevated CO2 and N2O levels beginning in February 1994. Both CO2 and N2O fluxes from the snowfence site were similar to those measured under the naturally deep snowpack. These data suggest that the timing and depth of snow cover during the alpine winter control microbial activity by insulating soils from extreme air temperatures. To obtain a regional perspective on subnivean trace gas fluxes, both CO2 and N2O samples were determined at sites below treeline on Niwot Ridge and at Loch Vale in Rocky Mountain National Park.
Porewater nutrient concentrations from control plots and fertilized plots at Spartina alterniflora, S.patens and Typha sp. marshes, Plum Island Ecosystem LTER, MA (1999-2025).
Porewater samples from five marsh locations in the Plum Island Ecosystems (PIE) LTER site were collected and analyzed for salinity as well as ammonium, phosphate, sulfide and chloride concentrations throughout the growing season. Three sites (a Typha-dominated brackish marsh, a Spartina alterniflora-dominated salt marsh, and a S. patens-dominated salt marsh) are part of a long term study, and include fertilized and non-fertilized sample plots. Two additional, non-fertilized marsh sites, are located on Nelson Island, near Stackyard Road within the Parker River National Wildlife Refuge.
Dissolved Organic Carbon Concentration, Dissolved Organic Matter Optical Properties, and Water Quality Indicators in the Plum Island Estuary (PIE), Massachusetts, USA (2018-2023)
This is a data set of paired in situ measurements of water quality parameters, total suspended solids concentration, and concentration and optical properties (absorption coefficient spectra and fluorescence indices) of dissolved organic matter (DOM) collected between 2018 and 2023 in the Plum Island Estuary and nearshore waters. In situ water quality measurements (salinity, temperature, optical dissolved oxygen saturation, turbidity, and dissolved organic matter fluorescence) were collected with a water quality sonde from the surface (top 1 m of water column), along with corresponding samples that were processed and analyzed in the lab for dissolved organic carbon (DOC) concentration, chromophoric DOM (CDOM), absorption coefficient spectra, DOM excitation-emission matrix (EEM) fluorescence, and total suspended sediment (TSS) concentration. The data were used in multiple studies (see manuscripts listed below) focusing on the dynamics of DOC and CDOM in the Plum Island Estuary.
PIE LTER marsh sediment porewater nutrient concentrations from Spartina sp. and Typha sp. sites along the Parker River and Rowley River, MA.
Marsh sediment porewater nutrient concentrations [NH4+, NO3-, DOC, TDN, H2S] and salinity are reported from Spartina sp. and Typha sp. sites along the Parker and Rowley Rivers, MA. Porewater peeper poles are used for collection and the poles are located in the vicinity of the marsh water table sites for the Railroad, Typha, Shad and Nelson sites.
Advective nitrate fluxes, sea surface chlorophyll concentrations and other physical metrics in the Santa Barbara Channel (2012-2019)
This data package includes 6 files: (1 & 2) In-situ nitrate concentrations at the surface and mixed layer depth, and collocated remotely-sensed and reanalysis quantities of satellite sea surface temperature, 15-day cumulative wind stress, satellite sea surface chlorophyll with a 5-day lag, index of offshore position of the California Current, indices for along-channel and across-channel distance, and index for day of the year. (3) An R script for generating generalized additive models (GAMs) to predict nitrate concentrations at the surface and at the mixed layer depth using the collocated data in files 1 & 2. (4) Daily maps of satellite sea surface chlorophyll concentrations (SSChl), High-frequency radar (HFR) surface currents, weather research and forecasting (WRF) model wind-derived vertical velocities, estimated nitrate concentrations at the surface and mixed layer depth, horizontal advective nitrate fluxes at the surface and vertical advective nitrate fluxes. (5) Daily time series of spatial mean SSChl, principal component amplitude of the first mode of variability in surface currents estimated using complex empirical orthogonal function (EOF) analysis, alongshore pressure gradient, wind stress, spatial mean horizontal velocities at the western and eastern Santa Barbara Channel boundaries, spatial mean vertical velocities, spatial mean surface nitrate concentrations at the channel boundaries and across the entire channel, spatial mean mixed layer depth nitrate concentrations across the entire channel, spatial mean horizontal advective nitrate fluxes at the channel boundaries, and spatial mean vertical advective nitrate fluxes. (6) A MATLAB script for plotting examples of the daily maps and time series in files 4 & 5. These data were processed in order to investigate the impact of local nutrient delivery mechanisms on phytoplankton blooms in the Santa Barbara Channel, California, details of which are available in the study: Brokaw, R.J., D.A. Siegel, L. Washburn,
Ice Nucleating Particle number concentration from low-volume sampling over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract </strong></p> <p>Ice nucleating particles (INP) are a subclass of atmospheric aerosol particles, which can force heterogeneous freezing of cloud droplets at temperatures above -38 degrees C. In contrast, ice particles form from cloud droplets at temperatures below -38 degrees C due to homogeneous freezing, without INP. Due to their abundance, these particles can affect micro-physical properties of clouds, while acting as INP. During the Antarctic Circumnavigation Expedition (ACE) around the Southern Ocean, off-line filter sampling was performed. Filters were stored on the ship and analysed after the cruise at Leibniz-Institute for Tropospheric Research (TROPOS) concerning INP abundance. Here, we give INP number concentrations for sampling of 8 hour periods.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_ice_nucleating_particles_frozen_fraction_from_lowvolume_filters.csv, data file, comma-separated values</li> <li>ACESPACE_ice_nucleating_particles_number_concentration_from_lowvolume_filters.csv, data file, comma-separated values</li> <li>data_file_header_frozen_fraction.txt, metadata, text format</li> <li>data_file_header_number_concentration.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>change_log.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>change dataset title to reflect low-volume sampling method</li> <li>addition of INP number concentration data from different temperatures</li> <li>addition of fraction of frozen droplets data</li> <li>addition of field blank filter data</li> <li>create separate data_file_header files</li> <li>add change log</li> </ul> <p>v1.0 - initial release of dataset</p> <p> </p>
Cloud Condensation Nuclei number concentrations over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Cloud Condensation Nuclei (CCN) are a subclass of atmospheric aerosol particles, which can be activated to cloud droplets at a certain supersaturation, with respect to water. Due to their abundance, these particles can affect micro-physical properties of clouds, while acting as CCN. It was found that CCN are relevant for the Earth’s radiation budget, by affecting cloud albedo and lifetime. When giving a number concentration of CCN, also the supersaturation at which it was measured has to be given.</p> <p>With additional information on particle number size distribution, the hypothetical diameter of particle activation (critical diameter) was derived. Further, the particle hygroscopicity parameter (kappa) was calculated using the critical diameter. Values of kappa can be a proxy for bulk chemical composition of the sampled CCN population.</p> <p>Our dataset gives CCN number concentrations measured by a CCN counter (type CCN-100 by DMT, Boulder, US) operated at five different levels of supersaturation (0.15%, 0.2%, 0.3%, 0.5%, 1%) during the Antarctic Circumnavigation Expedition (ACE) cruise over the Southern Ocean, as part of the ACE-SPACE project. Temporal coverage is from December 20, 2016 to March 19, 2017. We give 5-minute averaged and quality controlled CCN number concentrations, critical diameter and kappa values.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_number_concentration_SS030.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_number_concentration_SS050.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_number_concentration_SS100.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_critical_diameter_SS015.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_critical_diameter_SS020.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_critical_diameter_SS030.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_critical_diameter_SS050.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_critical_diameter_SS100.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS015.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS020.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS030.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS050.csv, data file, comma-separated values</li> <li>ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS100.csv, data file, comma-separated values</li> <li>data_file_header_number_concentration.txt, metadata, text</li> <li>data_file_header_critical_diameter.txt, metadata, text</li> <li>data_file_header_hygroscopicity_parameter.txt, metadata, text</li> <li>change_log.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p>The files listed above contain Cloud Condensation Nuclei (CCN) number concentration (N_CCN), critical diameter (D_crit) and particle hygroscopicity parameter (KAPPA) values for the Antarctic Circumnavigation Expedition from in-situ measurements. Each file contains only N_CCN, D_crit or KAPPA values for one of the five measured levels of supersaturation (SS), e.g., N_CCN at SS=0.15% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv or N_CCN at SS=0.2% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv etc. In addition, for each N_CCN value the respective temperature of the CCNCs measurement column (T_col) is given. Values are from 1 Hz measurements and averaged to represent 5-minute intervals.</p> <p>For every given value of CCN number concentration, the respective supersaturation level is given, although files only contain values for one level only. Additionally, longitude and latitude for the ship’s position at the start time of the averaging period are given.</p> <p>For latitude and longitude nan values are given, in cases where positioning data was not available for the given time period. There are no nan values for CCN number concentration included, in a way that only quality assured data is given.</p> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>change dataset title to specify ACE cruise</li> <li>change time resolution to 5 minutes</li> <li>addition of critical diameter data</li> <li>addition of hygroscopicity parameter data</li> <li>create separate data_file_headers</li> <li>add change log</li> </ul> <p>v1.0 - initial release of dataset</p>
Curated mode-of-action data and effect concentrations for chemicals relevant for the aquatic environment
<p>Chemicals in the aquatic environment can be harmful to organisms and ecosystems. Knowledge on effect concentrations as well as on mechanisms and modes of interaction with biological molecules and signaling pathways is necessary to perform chemical risk assessment and identify toxic compounds. To this end, we developed criteria and a pipeline for harvesting and summarizing effect concentrations from the US ECOTOX database for the three aquatic species groups algae, crustaceans, and fish and researched the modes of action of more than 3,300 environmentally relevant chemicals in literature and databases. We provide a curated dataset ready to be used for risk assessment based on monitoring data and the first comprehensive collection and categorization of modes of action of environmental chemicals. Authorities, regulators, and scientists can use this data for the grouping of chemicals, the establishment of meaningful assessment groups, and the development of <em>in vitro</em> and <em>in silico</em> approaches for chemical testing and assessment.</p> <p> </p> <p> </p>
Concentration of gaseous iodic acid measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p>Measurements of iodic acid concentration in the gas phase obtained with a nitrate chemical ionization mass spectrometer (we used an APi-TOF mass spectrometer produced by Tofwerk AG coupled with a Chemical ionization inlet A70 produced by Airmodus). Iodic acid is detected in the mass spectrometer either as a deprotonated ion or as a cluster with the reagent ion (NO3-). The concentration is calculated as the area of these two peaks normalized to the concentration of the reagent ions (monomer, dimer and trimer) and multiplied by a calibration factor equal to 6.9E9 molecules cm<sup>-3</sup> that was experimentally derived at Paul Scherrer Institute in the summer 2017, after the campaign.</p> <p>Iodic acid can participate in both new particle formation and growth, affecting the Earth radiative balance and cloud properties. Iodic acid is produced from the iodine radical but the exact formation pathways is still unknown.</p> <p>Measurements were performed on the upper deck of the icebreaker Akademik Tryoshnikov along the track of the Antarctic Circumnavigation expedition. Temporal coverage is from January 22, 2017 to March 19, 2017. There are no data for the first leg of the expedition because the instrument was not on the ship. The instrument was operated during leg 4 but data has not been processed yet. Data were collected with one-second time resolution but integrated to five minutes to increase the signal to noise ratio. Concentrations are reported as molecules per cubic centimeter in five minutes averages. The lower limit of detection was estimated to be lower than 6E3 molecules cm<sup>-3</sup>. Data below the detection limit were replaced by the detection limit divided by the square root of 2.</p> <p>Pollution from the ship exhaust and other human activities (e.g. helicopter flights) was identified as described in Schmale et al. 2019 (<a href="https://doi.org/10.1175/BAMS-D-18-0187.1">https://doi.org/10.1175/BAMS-D-18-0187.1</a>) and a corresponding flag was associated to the data (with 1 meaning clean data and 2 polluted data). No direct influence of pollution on the iodic acid concentration was found.</p> <p>***** Dataset contents *****</p> <p>- 01_gas_iodic_acid_concentration_data.csv, data file, comma-separated values</p> <p>- 02_IodicAcid_file_header.txt, metadata, text format</p> <p>- 03_README.txt, metadata, text format</p> <p> </p>
Number concentration and fluorescent class fraction of fluorescent and hyper-fluorescent aerosol particles measured during the Antarctic Circumnavigation Expedition
<p><strong>Dataset abstract</strong></p> <p>This dataset consists of a 5-minute time series of number concentrations of fluorescent and total aerosol particles that were measured by wideband integrated by aerosol sensor during the Antarctic Circumnavigation Expedition in the austral summer of 2016/2017. Furthermore, the dataset includes the fraction of fluorescent classes of aerosol particles, according to the ABC classification of Perring et al. (2015). The dataset provides information on fluorescent and hyper-fluorescent aerosols which were obtained by considering low and high fluorescence thresholds. For this dataset, aerosol particles that have optical diameter greater than 1 μm are considered. Since the ship’s exhaust could considerably affect the fluorescence properties of aerosol particles, in this dataset we removed the periods where it is likely that the samples were contaminated by the ship's exhaust.</p> <p><strong>Dataset contents</strong></p> <ul> <li>N_fluorescent.csv, data file, comma-separated values</li> <li>N_hyper_fluorescent.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This number concentration and fluorescent class fraction of fluorescent and hyper-fluorescent aerosol particles dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Humic acid like concentration in seawater samples, collected from the trace metal rosettes in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>Humic acid like concentration (abbreviated HA) measured with respect to the Suwannee River Fulvic acid standards (µmol SRFA equivalent per litre).</p> <p>Seawater samples were collected from trace metal rosette (TMR) deployments at different depths in the water column during the Antarctic Circumnavigation Expedition (ACE). Humic acid like data from legs 1 and 2, from TMR cast numbers 3 to 16, were analysed by electrochemistry following standard additions of Suwannee River Fulvic Acid (standard 1, IHSS). This data is to support iron ligands and iron bioavailability as well as hydrolysable saccharides (TPZT) data, also collected during ACE.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_humics_data.csv, data file, comma-separated values</li> <li>ace_humics_data_visual_summary.png, metadata, portable network graphics</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This humics dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Chlorophyll a concentration, particulate organique carbon, and particle mean size index [gamma; 0.2 - 20 µm] measured using an hyperspectral spectrophotometer [ACS, Wetlabs] during the Tara Pacific Expedition 2016-2018
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from the hyperspectral and multispectral spectrophotometers [ACS] instruments acquiring continuously during the full course of the campaign. Surface seawater was pumped continuously through a hull inlet located 1.5 m under the waterline using a membrane pump (10 LPM; Shurflo), circulated through a vortex debubbler, a flow meter, and distributed to a number of flow-through instruments. An [ACS] spectrophotometer (WETLabs) measured hyper-spectral (4 nm resolution) attenuation and absorption in the visible and near infrared except between Panama and Tahiti where an AC-9 multispectral spectrophotometer (WETLabs) was used instead. The flow was automatically directed through a 0.2 µm filter for 10 minutes every hour before being circulated through the spectrophotometer to eliminate the impact of biofouling and instrument drift and estimate particulate absorption [ap] and attenuation [cp] (Slade et al. 2010). Chlorophyll a content was estimated from particulate absorption line height at 676 nm (Boss et al. 2001). The particulate organic carbon concentration [poc] was estimated using an empirical relation (Gardner et al. 2006) between measured [poc] and measured [cp]. An indicator for size distribution of particles between 0.2 and ~20 µm [gamma] was calculated from [cp] (Boss et al 2001). The data was processed with custom software for underway optical data (InLineAnalysis software available on GitHub). The detailed information regarding the data processing is given in the processing report attached with the data and in Lombard et al. (In prep.). These results are preliminary: no matchup with in-situ chlorophyll from HPLC or [poc] measurements were performed.</p>
Data from: Land use, season, and parasitism predict metal concentrations in Australian flying fox fur
<p>There are two .csv files in this upload. The "Pteropus_metal_data_wide.csv" file contains metal concentrations (reported in ng/g) measured in fur samples collected from <em>Pteropus </em>flying foxes (<em>P. alecto</em>, <em>P. conspicillatus</em>, <em>P. poliocephalus</em>). Flying foxes were captured from 2015-2018 at multiple sites across Australia. The file also contains capture information (e.g. date, location) and biological information (e.g. species, sex, age class, parasitism) for each flying fox. The "Pteropus_metadata.csv" file provides further details on all column names in the primary data file, including the specific metals that were quantified. Detailed information on the study methods and results can be found in the associated Science of the Total Environment publication, "Land use, season, and parasitism predict metal concentrations in Australian flying fox fur" by Sánchez et al.</p>
Field and laboratory measurements of suspended-sediment particle size and concentration from nine rivers draining to the Great Barrier Reef
<p>Dataset includes in-situ (n = 144,912) and laboratory-dispersed (n = 64) particle size measurements collected using laser diffractometry from nine rivers discharging along 800 km of Great Barrier Reef, Queensland Australia coastline. Two field campaigns (24 February to 5 March 2021 and 24<sup>th</sup> to 31<sup>st</sup> of April 2021) were undertaken to collect vertical profiles of in-situ particle size, water velocity, turbidity, and salinity. Water samples were collected for analysis of laboratory-dispersed particle size and suspended-sediment concentration. Water samples were collected using US-P61 or Van-Dorn samplers deployed alongside a LISST 200x laser diffractometer and an EXO2 YSI multiparameter water quality sonde. Total depth and water velocity were measured using a Nortek Signature ADCP and Teledyne RiverRay ADCP during the first and second field campaigns, respectively. During both campaigns, measurements were undertaken during relatively high discharge events when discharge exceeded the 90<sup>th</sup> percentile of 2020/2021 gauged wet season flows.</p> <p>Data are provided in three csv files. "In_situ_data.csv" contains in situ measurements of particle size, turbidity, salinity, and depth along with estimates of shear rate. Shear rate is estimated from theory and measurements of ADCP-measured total depth and depth-averaged flow (see equation 2 of Livsey et al., 2022). "Lab_data_this_study.csv" contains particle size measurements of suspended-sediment following laboratory dispersion along with coeval measurements of in-situ particle size, turbidity, salinity, and shear rate averaged over the filling time of the US-P61 sampler. "Lab_data_DES_WQI.csv" contains laboratory dispersed particle size measurements collected by the Department of Environment and Science Water Quality Investigation Unit of Queensland Australia (Turner et al., 2013) and compared to data in "Lab_data_this_study.csv" in Livsey et al (2022). </p> <p>Further details of the data collection effort and interpretation of the data are published in Livsey et al (2022) at https://doi.org/10.1029/2021JC017988. </p> <p>Additional data from the 24 February to 5 March 2021 field campaign, funded by CSIRO Oceans and Atmosphere, are available from Crosswell et al (2022) at https://doi.org/10.25919/2vbh-cx08.</p> <p>References:</p> <p>Crosswell, Joey; Carlin, Geoff; Daniel, Livsey; Hillyer, Katie; Steven, Andy (2022): FNQ_2021_V01 Voyage dataset: Feb - March 2021; Biogeochemical and hydrodynamic obervations along the river-reef continuum of estuaries in eastern Cape York, Australia. v1. CSIRO. Data Collection. 10.25919/2vbh-cx08</p> <p>Livsey, D. L., Crosswell, J. R., Turner, R. R., Steven, A. D. L., & Grace, P. R. (2022) Flocculation of riverine sediment draining to the Great Barrier Reef, implications for monitoring and modelling of sediment dispersal across continental shelves. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2021JC017988</p> <p>Turner. R, Huggins. R, Wallace. R, Smith. R, Vardy. S, Warne. M St. J. (2013). Total suspended solids, nutrient, and pesticide loads (2010-2011) for rivers that discharge to the Great Barrier Reef Great Barrier Reef Catchment Loads Monitoring 2010-2011 Department of Science, Information Technology, Innovation and the Arts, Brisbane.</p> <p> </p> <p> </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.