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9,568 results for “2021”

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edi56/100

Bacterial Production Data for lake and stream samples collected in summer 2012 through 2021, Arctic LTER, Toolik Lake Field Station, Alaska

File containing data on bacterial productivity in lakes and streams. Samples were collected at various sites near Toolik Lake Field Station (68 38'N, 149 36'W). Sample site descriptors include an assigned number (sortchem), site, date, time and depth, and bacterial production.

openCC (other)Mar 2022View details →
edi56/100

Wildlife in urban neighborhoods of the greater Phoenix, Arizona metropolitan area: patterns that span a social-ecological gradient in 2021

Wildlife communities are structured by numerous ecological filters in cities that influence their populations, and some species even manage to thrive in urban landscapes. CAP researchers were the first to observe “the luxury effect”, the hypothesis that biodiversity is positively related to income of residents. The luxury effect is still being tested worldwide twenty years later and has led to important new research on other socio-demographic factors that shape biodiversity but are vastly understudied, such as race and ethnicity, as well as the interaction of these factors with urban structural inequalities that may be hidden by income. This research aims to unpack the luxury effect by considering other landscape and socio-demographic factors that may influence wildlife communities across neighborhoods of metro Phoenix. Specifically, we are investigating if neighborhood income and ethnicity independently influence mammal occupancy in neighborhoods across the CAP ecosystem. To answer this question, we leveraged a wildlife camera array across CAP within community parks, in which cameras are placed across a gradient of average median household income and percent Latinx of residents. Incorporating socioeconomic data into urban mammal research will allow for the advancement in the understanding of socio-ecological patterns.

openCC0Nov 2022View details →
edi56/100

Urban habitat features and patterns of snake removals in the greater Phoenix, Arizona (USA) metropolitan area (March 2021 - March 2022)

In urban and suburban areas, wildlife and people are often in close quarters, leading to human-wildlife interactions (HWI). Understanding how wildlife interact with humans and the built environment is critical as urbanization contributes to habitat change and fragmentation globally. In our study, we partnered with a local business that removes and relocates snakes from homes and businesses in the Phoenix area. The most frequently removed were venomous (family Viperidae, e.g., rattlesnakes) and nonvenomous (family Colubridae, e.g., gophersnakes) snakes. Using these records, we investigated taxa-specific habitat trends at two spatial scales. The neighborhood scale focused on front yard measures of cover and vegetation classes and the landscape scale focused on variables related to vegetation indices and degree of urbanization. Both analyses compared areas where snakes were removed to random locations in the city to represent possible habitat available to snakes. At the neighborhood scale (n=60), we found that removals occurred in yards with abundant cover opportunities. At the landscape scale (n=764), we found species-specific differences with nonvenomous snakes removed from areas of higher urbanization compared to venomous snakes. Understanding these distinct habitat patterns in residential yards can identify areas with potential human-snake conflict.

openCC0Jul 2024View details →
edi56/100

Hubbard Brook Experimental Forest: Soil Fungal Communities, 2021-2023

Sporocarp (fungal fruiting body) observational data and fungal eDNA data extracted from soil samples collected primarily by Farrar Ransom in the summers of 2021, 2022, and 2023. Also included: detailed site metadata, soil moisture measurements, sample processing metadata, and R code used in publication analysis. Data are still being uploaded as of January 2026. The majority of these data were collected in study plots established around 2016 by Dr. Elizabeth Studer for her dissertation work. This factorial study design consists of approximately 60 plots on two hydropedological soil types beneath four canopy tree species. The four tree species we considered were white ash (Fraxinus americana), sugar maple (Acer saccharum), American beech (Fagus grandifolia), and yellow birch (Betula alleghaniensis). Some of these plots are now part of the ongoing Ash Protection Experiment. The following data tables and other entities were used in the analysis for the publication: Unique soil fungal communities are associated with disappearing ash trees in a northern temperate hardwood forest. Site_Metadata; eDNA_Abun_Table; eDNA_Taxa_Metadata; eDNA_Extraction_Metadata; iNext_Format_eDNA; Sporocarp_Count_Table; Sporocarp_Prop_Table; Soil_Moisture_Measurements; PCR_Plate_Gel_Photos; FR_DADA2_PlusFilter_CodePub; FR_eDNA_CodePub; FR_Sporocarp_CodePub; These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)Jan 2026View details →
edi56/100

Candida Pseudoglaebosa Ecology in Sarracenia Purpurea Pitcher Plants at Harvard Forest since 2021

Fungi and bacteria are common members of the microbiomes of carnivorous plants. In the pitcher plant Sarracenia purpurea these microorganisms enter carnivorous pitchers shortly after pitchers develop, and may be relevant for pitcher functioning. We are sampling pitchers repeatedly over several years to better understand the culturable diversity in this habitat, with a focus on the common pitcher yeast Candida pseudoglaebosa and fungi that have the potential to interact with it. C. pseudoglaebosa dominates pitcher plants by arriving early in pitchers, and we are interested in how this yeast’s populations change over time and in response to other pitcher microorganisms. Between 2021 and 2023, we collected pitcher water from Tom Swamp in Harvard Forest and cultured 118 yeast and bacteria colonies from this water. We have found C. pseudoglaebosa and some other yeasts (Papiliotrema, Rhodotorula, and Sporidiobolus); microbial identification is ongoing. We are planning to investigate changes in C. pseudoglaebosa genetic diversity and changes in C. pseudoglaebosa interactions with other pitcher microorganisms over time.

openCC0Feb 2024View details →
edi56/100

Tree-Associated Fungal and Bacterial Communities at Harvard Forest 2021

Cities are investing in tree-planting initiatives to protect their citizens from climate change-related heat and pollution exposure, yet Boston’s street trees are growing nearly four times as fast and dying twice as young as Massachusetts’ rural forest trees. Our research aims to characterize the belowground variables and microbial community composition that might explain the differences in growth and mortality rates observed between urban and rural trees. In 2021, soil, leaf, and root samples were taken from 25 trees in Harvard Forest to use as a rural comparison to Boston’s street trees and trees in other forests along an urban-to-rural gradient from Boston into Western Massachusetts. At each tree, three 12” deep, 2.4-centimeter radius soil cores were taken within the drip line, and soil cores were divided into the top 6” and lower 6” of soil. Fine roots were picked from each soil core. Six leaf samples were taken from the mid-canopy of each tree, where possible. Soil variables including temperature, moisture, percent organic matter, soluble nitrogen availability, bulk density, and root biomass were measured. Thus far, we have found that urban trees have fewer roots than Harvard Forest trees (F1,252) = 10.88, p = 0.0011), and that urban trees establish more root biomass deeper into the soil than Harvard Forest trees (p = 4.84e-5).

openCC0Mar 2025View details →
edi56/100

Microbial, Plant, and Soil Impacts on Soil Nutrient Cycling in Harvard Forest and Greater Boston 2021-2022

Microbes are the driving force behind nutrient cycling within soils, secreting enzymes necessary to break down organic matter, immobilizing nutrients and C, or transferring nutrients to plant hosts. Even though nutrients would almost never move through ecosystems without microbes, we know little about how their composition and activity is related to ecosystem nutrient cycling, and their importance relative to plant and soil abiotic factors. In this study, we sought to determine which commonly measured soil microbial community characteristics best explain soil N and P cycling, and the relative contributions of microbial, plant, and abiotic factors in explaining these processes.

openCC0Mar 2025View details →
edi56/100

National Phenology Network tree phenology at Crosby Farm Adaptive Silviculture for Climate Change study, 2021-2025

Phenology is the study of relations between climate and periodic biological phenomena, such as bud break or leaf drop in deciduous trees. Phenology is a leading indicator of climate change, and the response of urban tree species to climate can help inform how to manage for a more resilient, and adaptive urban tree canopy. This dataset contains tree phenology data from the The Mississippi National River and Recreation Area (MNRRA) Urban Affiliate Adaptive Silviculture for Climate Change (ASCC) project located at Crosby Farm Regional Park. This dataset includes Individual Phenometrics, Site Phenomentrics, Status and Intensity, and Magnitude Phenometrics. This data was collected through mobile app submissions to Nature's Notebook and downloaded from the National Phenology Network Observation Portal, filtered by date range 01/01/2021 to 02/26/2024 and for Crosby Farm ASCC. Data Attribution: USA National Phenology Network. 2024. Plant and Animal Phenology Data. Data type: Status & Intensity, Individual Phenometrics, Site Phenometrics, Magnitude Phenometricts. 01/01/2021-02/26/2024 for Region: 45.221627°, -92.554965° (UR); 44.599185°, -93.5712° (LL). USA-NPN, St. Paul, Minnesota, USA. Data set accessed 03/19/2024 at http://doi.org/10.5066/F78S4N1

openCC (other)Feb 2026View details →
edi56/100

Chloride Concentrations, Conductivity, and Water Temperature Data from Lake Mendota and Lake Monona Madison, WI: December 2019 – April 2021

Conductivity and chloride were measured for 2 years in Lake Mendota and Lake Monona in Madison, WI. Conductivity was continuously measured (every 30 minutes) on under-ice buoys in the eplimnia (1-2m below the surface) and hypolimnia (1m off the bottom of the lake) of the lakes. Depth-discrete chloride grab samples were collected from the lakes quarterly. Profile sampling in Mendota, which is approximately 25 m deep, occurred every 5m from 0-20m and at 23.5m. Profile sampling in Monona, which is approximately 21m deep, occurred every 4m from 0-20m. This data was needed for a master’s research thesis with the goal of identifying the lakes' mixing dynamics and how salinization may impact them.

openCC (other)Dec 2022View details →
edi56/100

Water quality, temperature, ash-free dry mass, photosynthetic activate radiation (PAR), and zooplankton data from a warming and DOC subsidy experiment, 2020 - 2021.

This dataset includes chlorophyll-a concentrations, periphyton biomass estimates, water quality measurements, and qualitative observations from a large-scale mesocosm experiment conducted in the Green Lakes Watershed, Colorado. The experiment was designed to test how earlier lake ice-off and increased dissolved organic material (DOM), associated with terrestrial plant encroachment in alpine watersheds, interactively influence aquatic food webs. In fall 2019, twenty 2600L “megacosms” were established at Sandy Corner (3300 m ASL; 40.042289, -105.584006), left to fill with snowmelt, and maintained throughout the 2020 open water season. The experiment followed a 2 × 2 randomized block design manipulating ice-off timing (via black vs. beige tank coloration) and DOM inputs (presence/absence of willow leaf packs), with five replicates per treatment. All tanks were seeded with sediments and zooplankton from both alpine and montane lakes (Green Lake 1 and Green Lake 4), and instrumented with thermistors recording surface and hypolimnion temperature every two hours year-round. Periphyton growth was monitored using clay tiles, sampled across five time points. Chlorophyll-a concentrations were extracted from filtered water samples and analyzed spectrophotometrically. Periphyton biomass was estimated via ash-free dry mass (AFDM) determinations, based on the mass lost on combustion of material scraped from tiles. Water quality was measured 1–2 times weekly using a YSI ProPlus multiprobe and Li-Cor quantum sensor, and snow/ice cover was qualitatively assessed monthly during winter.

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

PIE LTER 5-minute marsh water table height at Nelson Island, Rowley, MA from April-October 2021.

Measurements of water table height in the Nelson Island marsh located near the Nelson Island eddy flux tower, Rowley, MA. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Nelson stream bank at Nelson Island from April-October 2021.

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

Coastal Forest Aboveground Biomass Data at six sites in the Chesapeake Bay and Delaware Bay region, 2021

This dataset contains aboveground biomass measurement and vegetation inventory of 17 coastal forest sites collected during June 1-8 of 2021 across Virginia (n = 6 in Goodwin Island and Phillips Creek), Maryland (n = 4, Monie Bay and Moneystump Swamp) and Delaware (n = 7, Milford Neck and Donas landing). The aboveground biomass was computed with allometric equations and all study sites were located within a narrow elevation range of 0-5m above sea level.

openCustomMay 2022View details →
edi56/100

Barrier Island Plant and Soil Properties on Hog and Metompkin Islands, Virginia, 2021-2022

Dune building has the potential to impact the entire barrier island ecosystem, and these grasses therefore serve as ecosystem engineers. Protection offered by dune ridges directly impacts the adjacent swale habitat, modifying both biotic and abiotic factors. In order to better understand how dune building impacts the island ecosystem as a whole, we quantified sediment accretion, plant percent cover, stem numbers, and soil characteristics (chlorides, bulk density, %OM, %C, %N). These characteristics were assessed on two islands with varied disturbance intensities. Hog island is infrequently disturbed, and resists change driven by storms and overwash. Metompkin island is frequently disturbed and undergoes high rates of overwash and island migration.

openCustomMar 2025View details →
zenodo52/100

Data presented in Devenish and Cerminara, Journal of Geophysical Research Atmosphere, 2021. doi:10.1029/2020JD033699

<p>The files contain the raw data of the atmospheric and concentration profiles respectively used and calculated by the LES and LSM simulations presented in Devenish and Cerminara (2020).</p> <p>The concentration data have been stored in two ASCII columns, the first being the elevation with respect to the vent level, and the second the&nbsp;concentration normalised by the initial concentration, where the initial concentration is the product of the source mass flux and the exit velocity.</p> <p>For the two cases of the intercomparison study, the initial mass flux is 1.5e6 kg/s and 1.5e9 kg/s&nbsp;for the weak and strong cases, respectively. The respective&nbsp;exit velocities are 135 m/s and 275 m/s.</p> <p>For the twenty cases with ambient wind, the initial mass flux and exit velocities&nbsp;can be extracted from the information given in the paper.</p> <p>Additional information can be found in Costa et al. (2016) and Aubry et al. (2019).</p>

opencc-by-4.0Aug 2020View details →
zenodo52/100

Dataset to Manuscript: Key drivers of pyrogenic carbon redistribution during a simulated rainfall event, Bellè et al. 2021 (Biogeosciences)

<p>Dataset to manuscript: Bell&egrave;, S-L., Berhe, A., Hagedorn, F., Santin, C., Schiedung, M., van Meerveld, I. and Abiven, S.:&nbsp;Key drivers of pyrogenic carbon redistribution during a simulated rainfall event, Biogeosciences, https://doi.org/10.5194/bg-2020-361, 2021.&nbsp;</p> <p>All parameters and variables are described in the &quot;var_names&quot; file.</p>

opencc-by-4.0Jan 2021View details →
zenodo52/100

AMOC reconstruction between 1981 and 2016 from hydrographic data using an empirical linear regression model from Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, 2021.

<p>Dataset used to create Figure 8 in Worthington et al., 2021 (https://doi.org/10.5194/os-17-285-2021). Details of the data and methods can be found in the journal article.<br> <br> Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285&ndash;299,&nbsp;<a href="https://doi.org/10.5194/os-17-285-2021">https://doi.org/10.5194/os-17-285-2021</a>, 2021.</p>

opencc-by-4.0Jul 2022View details →
zenodo52/100

National Survey on the Effects of COVID-19 on the Wellbeing of Mexican Households (ENCOVID-19- MAY 2021)

<p>Amid the COVID-19 outbreak, the ENCOVID-19 provides information on the well-being of&nbsp;Mexican households in four main domains: labor, income, mental health, and food insecurity. It&nbsp;offers timely information to understand the social consequences of the pandemic and the&nbsp;lockdown measures. It is a project consisting of a series of cross-sectional telephone surveys&nbsp;collected in key moments of the COVID-19 pandemic. In addition to the four main domains and&nbsp;a set of COVID19-related questions, the survey includes new key indicators every month to&nbsp;capture the impact of the pandemic on issues like education, social programs, and crime. This is&nbsp;the ninth dataset of the project, corresponding to May 2021, collected thirteen months after&nbsp;the lockdown began in Mexico. Data collection was performed from May 21 to Jun 17, 2021.</p>

opencc-by-4.0Jul 2021View details →
zenodo52/100

National Survey on the Effects of COVID-19 on the Wellbeing of Mexican Households (ENCOVID-19- OCTOBER 2021)

<p>Amid the COVID-19 outbreak, the ENCOVID-19 provides information on the well-being of Mexican households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a project consisting of a series of cross-sectional telephone surveys collected in key moments of the COVID-19 pandemic. In addition to the four main domains and a set of COVID19-related questions, the survey includes new key indicators every month to capture the impact of the pandemic on issues like education, social programs, and crime. This is the tenth dataset of the project, corresponding to October 2021, collected 19 months after the lockdown began in Mexico. Data collection was performed from October 20 to November 13, 2021.</p>

opencc-by-4.0Dec 2021View details →
zenodo52/100

National Survey on the Effects of COVID-19 on the Wellbeing of Mexican Households (ENCOVID-19 - MARCH 2021)

<p>Amid the COVID-19 outbreak, the ENCOVID-19 provides information on the well-being of Mexican households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a project consisting of a series of cross-sectional telephone surveys collected in key moments of the COVID-19 pandemic. In addition to the four main domains and a set of COVID19-related questions, the survey includes new key indicators every month to capture the impact of the pandemic on issues like education, social programs, and crime. This is the sixth dataset of the project, corresponding to March 2021, collected one year after the lockdown began in Mexico. Data collection was performed from February 26 to March 27, 2021.</p>

opencc-by-4.0May 2021View details →
zenodo52/100

Mapping of a Mid-depth Salinity Maximum Intrusion south of New England in June 2021

<div> <div> <p>This dataset contains data from a process-oriented research cruise aboard the R/V Neil Armstrong from June 18th to July 2nd. The goal of this cruise was to map the three-dimensional structure of a mid-depth salinity maximum intrusion of warm salinity slope water extending onto the continental shelf south of New England. This was done through the use of Autonomous Underwater Vehicles (two REMUS 100 vehicles and one Tethys class AUV (Long Range AUV or LRAUV)), a towed Rockland Scientific Vertical Microstructure Profiler (VMP 250), and ship-board CTD and ADCP&nbsp;measurements. More details about the processing, data coverage, and usage can be found in the accompanying manuscript. This cruise took place on the shelf waters south of Cape Cod, MA, extending to the shelf break,&nbsp;with all of the data collected between 40&deg;N to 41&deg;N and 71.5&deg;W to 70&deg;W. Attached is a data map showing the location of all data included within this dataset.&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>File Descriptions:&nbsp;</p> </div> <div> <p><strong>Datamap.jpg&nbsp;</strong></p> </div> <div> <p>A map of the locations of all data included within this dataset.&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p><strong>CTD_summer2021.mat&nbsp;&nbsp;</strong></p> </div> <div> <p>This file contains profiles from the ship-board CTD (SeaBird 911+). Raw data was processed and gridded into 1 decibar bins using standard procedures in&nbsp; Seasave V 7.26.7.121 (Look at cnv file header for details about processing). This file is organized as a structure, with each variable in the data being a different field called by dot notation and each row with the structure being a different CTD profile. Biooptical variables are not quality-controlled.&nbsp;&nbsp;</p> </div> <div> <ul> <li> <p>CTD.time: the time of each profile in the MATLAB datetime format (from the processed SeaBird header file) in GMT&nbsp;</p> </li> <li> <p>CTD.lon: degrees longitude of the profile (from the processed SeaBird header file)&nbsp;</p> </li> <li> <p>CTD.lat: degrees latitude of the profile (from the processed SeaBird header file)&nbsp;</p> </li> <li> <p>CTD.pres: the pressure in decibar at each location of the profile&nbsp;&nbsp;</p> </li> <li> <p>CTD.sal: the seawater practical salinity in psu&nbsp;&nbsp;</p> </li> <li> <p>CTD.temp: the seawater in-situ temperature in &deg;C&nbsp;&nbsp;</p> </li> <li> <p>CTD.flor: seawater fluorescence in mg/ m3&nbsp;</p> </li> <li> <p>CTD.depth: depth at each location within the profile in meters&nbsp;</p> </li> <li> <p>CTD.density: sigmatheta (the potential seawater density with respect to a reference pressure of 0 db) in kg.m3 minus 1,000kg/m3&nbsp;</p> </li> </ul> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p><strong>CTD_Darter_MMMdd.mat and CTD_Edgar_MMMdd.mat&nbsp;</strong></p> </div> </div> <div> <div> <p>These files contain the data from the REMUS 100 missions, with Darter and Edgar being the two different REMUS 100 vehicles.&nbsp;&nbsp;</p> </div> <div> <ul> <li> <p>Conductivity: conductivity in mS/cm&nbsp;&nbsp;</p> </li> <li> <p>Depth: depth in meters&nbsp;</p> </li> <li> <p>Latitude: degrees latitude&nbsp;&nbsp;</p> </li> <li> <p>Longitude: degrees longitude&nbsp;</p> </li> <li> <p>Mission_number: the number of the REMUS mission&nbsp;</p> </li> <li> <p>Mission_time: time during the mission in seconds since midnight in GMT &nbsp;</p> </li> <li> <p>Salinity: the seawater practical salinity in psu&nbsp;&nbsp;</p> </li> <li> <p>Sound_speed: the sound speed in m/s&nbsp;&nbsp;</p> </li> <li> <p>Temperature: the seawater temperature in &deg;C&nbsp;</p> </li> </ul> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p><strong>LRAUV_20210623T194917.mat and LRAUV_20210624T145829.mat&nbsp;</strong></p> </div> <div> <p>These files contain data from the Tethys Class LRAUV (Long Range AUV) missions. Each file contains 10 structure variables.&nbsp;&nbsp;</p> </div> </div> <div> <div> <ul> <li> <p>CTD_Seabird: structure containing the bin median temperature in &deg;C and salinity in PSU. &nbsp;</p> </li> <li> <p>depth: the depth at each data point in meters.&nbsp;&nbsp;&nbsp;</p> </li> <li> <p>fix_residual_percent_distance_traveled: underwater dead-reckoned navigation error (based on GPS fix when on surface) as a percentage of distance traveled&nbsp;</p> </li> <li> <p>latitude: Latitude at each data point (not corrected for vehicle drift in underwater current) &nbsp;</p> </li> <li> <p>latitude_fix: latitude of GPS fix (vehicle surfaced)&nbsp;</p> </li> <li> <p>longitude: Longitude at each data point (not corrected for vehicle drift in underwater current)&nbsp;</p> </li> <li> <p>longitude_fix: longitude of GPS fix (vehicle surfaced)&nbsp;</p> </li> <li> <p>platform_battery_charge: The battery charge in ampere-hour&nbsp;&nbsp;</p> </li> <li> <p>time_fix: time in seconds since January 1, 1970 (epoch time)&nbsp;</p> </li> </ul> </div> <div> <p>&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p><strong>VMPtransact_YYYYMMdd.mat</strong></p> <p>Vertical Microstructure Profiler (Rockland Scientific VMP 250)&nbsp;</p> </div> <div> <p>These files contain the processed data for each Vertical Microstructure Profiler (Rockland Scientific VMP 250) transect, consisting of multiple profiles. Data has been gridded on a 1 decibar equidistant grid using standard procedures in Rockland Scientific&rsquo;s processing software. Note: Bio-optical variables and dissipation rates have not been quality-controlled.&nbsp;&nbsp;</p> </div> <div> <ul> <li> <p>Time: Time in MATLAB datenum format (days since 0000-00-00 00:00:00) in GMT&nbsp;</p> </li> <li> <p>z: Pressure in decibar&nbsp;</p> </li> <li> <p>T: in-situ temperature in degC&nbsp;</p> </li> <li> <p>cnd: conductivity in mS/cm&nbsp;&nbsp;</p> </li> <li> <p>Chl: Chlorophyll from fluorescence in mg/ m3&nbsp;</p> </li> <li> <p>turb: Turbidity in NTU&nbsp;</p> </li> <li> <p>eps: dissipation rate inferred from microstructure shear in m^2/s^3. (Note: Dissipation estimates come from standard fitting of microstructure data within a 1 decibar bin to a turbulence spectrum within Rockland Scientific&rsquo;s standard processing. The&nbsp;dissipation data in the provided files has not been quality-controlled.&nbsp;</p> </li> </ul> </div> <div> <p>&nbsp;VMP-data was georeferenced by comparing the time stamps of VMP and processed ADCP files.&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;</p> </div> <div> <p><strong>ADCP_ar50_wh300.mat&nbsp;</strong></p> </div> <div> <p>This file contains the data from the shipboard ADCP (Teledyne WH300 kHz). ADCP data was processed aboard using standard procedures in UHDAS/CODAS (University of Hawaii Technical Services Program, servicing UNOLS vessels (<a href="https://currents.soest.hawaii.edu/docs/adcp_doc/index.html" target="_blank" rel="noreferrer noopener">https://currents.soest.hawaii.edu/docs/adcp_doc/index.html). Vertical bin size is 2 m. </a>u: zonal (positive towards east) velocity component in m/s&nbsp;</p> <ul> <li> <p>v: meridional (positive towards north) component in m/s&nbsp;&nbsp;&nbsp;</p> </li> </ul> </div> </div> <div> <div> <ul> <li> <p>txy: time, longitude, and latitude of the velocity profiles. Time is in decimal days, with noon of Jan 1 being 0.5 decimal days and noon of January 20th being 19.5 decimal days of the reference year. For another example, 6am on June 18, 2021, is decimal day 168.25. All times are in GMT.&nbsp;&nbsp;&nbsp;&nbsp;</p> </li> <li> <p>refyear: The reference year from which the decimal days are calculated.&nbsp;</p> </li> <li> <p>depth: vertical coordinate of the velocity bin center&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> </li> <li> <p>pgood: percent good, a quality parameter showing the fraction of good pings within an ensemble average.&nbsp;</p> </li> <li> <p>spd_u: zonal ship speed in m/s&nbsp;</p> </li> <li> <p>spd_v: meridional ship speed in m/s&nbsp;</p> </li> <li> <p>tr_temp: ADCP transducer temperature in deg C&nbsp;</p> </li> <li> <p>amp: backscatter amplitude in relative units&nbsp;</p> </li> </ul> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;&nbsp;</p> </div> <div> <p>&nbsp;</p> </div> <div> <p>&nbsp;</p> </div> </div>

opencc-by-4.0May 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

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