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92 results for “Beaufort Sea”

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edi60/100

Primary producer biomarker profiles of bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA) and their fatty acid (FA) collected from the Beaufort Sea coastal lagoons,2021-2024

Within Stefansson Sound in Prudhoe Bay, AK various organic matter sources were collected to determine multiple biomarker baseline profiles (i.e., bulk carbon and nitrogen stable isotopes (SI), compound specific stable isotopes of carbon in essential amino acids (CSIA-EAA), fatty acids (FA)). Some organic matter sources were collected from Elson lagoon in Utqiaġvik, AK and Kaktovik and Jago lagoons in Kaktovik, AK to supplement low sample sizes in some organic matter source groups. Kelp, red algae, terrestrial plants, phytoplankton, and ice algae were collected in 2024 with some supplement samples collected in 2021 - 2023. Stable isotope values of δ13C and δ15N are reported as “del_13c” and “del_15n”, respectively. Individual fatty acids are reported as the percent relative to total fatty acids for 23 fatty acids: C11:0, C12:0, C14:0, C15:1, C15:0, C16:0, C16:1n7, C17:0, C17:1, C18:0, C18:1n9 trans, C18:2n6 cis, C18:1n7, C18:3n3, C20:0, C18:3n6, C20:4n6, C21:0, C22:0, C22:1n9, C23:0, C24:0, C22:6n3. Stable isotope values of δ13C are reported in the following essential amino acids: Valine (Val), Leucine (Leu), iLeu (isoleucine), Methionine (Met), Phenylalanine (Phe). Additionally, we used ice algal diatoms collected in the Arctic (landfast ice near Utqiaġvik, Alaska) and cultured in a laboratory setting at the University of Alaska Fairbanks to compare the CSIA-EAA fingerprints of field (composites) ice algal samples and isolate diatoms samples.

openCC0Jan 2026View details →
edi60/100

Circulation dynamics: currents, waves, temperature measurements from moorings in lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing

Starting August 2018, five moorings deployed on the seafloor of multiple lagoons in the Beaufort Sea will record currents, waves, temperature, and pressure. Moorings are retrieved and re-deployed each August. This data is being collected to better understand the multi-seasonal circulation dynamics between the Beaufort Sea and coastal lagoons. Two moorings are deployed in Elson Lagoon, one in Stefansson Sound, one in Jago Lagoon, and one in Kaktovik Lagoon. Each mooring contains two data loggers: RBRduo3 T.D wave loggers and Lowell Instruments LLC TCM-1 tilt current meters. The RBR instruments measure temperature, pressure, and derived wave energy, average wave period, average wave height, maximum wave period, maximum wave height, 1/10 wave period, 1/10 wave height, significant wave period, significant wave height, tidal slope, depth, and sea pressure. The Lowell LLC TML-1 tilt current meters measure water velocity, heading, and temperature.

openCC0Aug 2021View details →
edi56/100

Seasonal Ice Mass-balance Buoy (SIMB) measurements from sites along the Beaufort Sea Coast, Alaska, 2018-ongoing

Measurements of the thickness of sea ice and the depth of its snow cover allow us to calculate how their mass changes in response to the varying fluxes of heat between the ocean and atmosphere over the course of a season. Repeated drill measurements are not ideal for this purpose since each drill hole disturbs the ice and its insulating snow cover. Also, spatial variability in ice thickness can mask temporal changes if holes are not drilled in the same place each time. Hence, methods that do not require re-drilling are preferred. Automated systems such as the Seasonal Ice Mass-balance Buoy (SIMB; Planck et al, 2019) provide high temporal resolution for capturing sub-daily variations and typically include sensor strings to measure the vertical temperature profile from the air to the ocean, which can be used to infer other properties of the ice cover such as strength and porosity. Under the Beaufort Lagoon Ecosystems LTER (BLE LTER) research program, several SIMBs are deployed at sites along the Beaufort Sea coast and record a suite of parameters including but not limited to snow depth, ice thickness, position of ice surface and bottom, water/air temperature, and vertical profiles of temperature. Planck, C. J., J. Whitlock, C. Polashenski, and D. Perovich (2019), The evolution of the seasonal ice mass balance buoy, Cold Regions Science and Technology, 165, 102792, doi: https://doi.org/10.1016/j.coldregions.2019.102792.

openCC0Mar 2021View details →
edi56/100

Time series of water column pH from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing

Beginning in August 2018, the Beaufort Lagoon Ecosystems Long Term Ecological Research (BLE LTER) program will record water column pH time series (hourly) from a benthic mooring containing a Seabird SeaFET V2 buoyed 10 cm from the lagoon seafloor. pH values are logged from the instrument’s internal sensor and reported on the total hydrogen ion scale. Site bottom water is collected and analyzed in the laboratory to employ a single point calibration to the data during post-processing. Another discrete water sample is collected months after instrument deployment to determine uncertainty (2018-2019 season: 0.002).

openCC0Jan 2020View details →
edi52/100

Carbon flux from aquatic ecosystems of the Arctic Coastal Plain along the Beaufort Sea, Alaska, 2010-2018

Multiple aquatic ecosystems (pond, lake, river, lagoon, ocean) on the Arctic Coastal Plain (ACP) near Utqiaġvik, AK were visited to determine their relative contribution to landscape-level atmospheric CO2 flux and how this may have changed over time. pCO2 (partial pressure of carbon dioxide) was monitored in late summer (late July to mid-August) over a period of four years (2013, 2015, 2017, 2018) from open water areas and is related to habitat type, dissolved organic carbon (DOC) and environmental factors (temperature, radiation, rainfall). Data include both daily averages from most sites, as well as spatial representation of pCO2 in Elson Lagoon and diel cycles of pCO2 from a tundra pond. Pond NEP (net ecosystem production) is estimated by free water metabolism and presented as daily estimates over a four summer period.

openCC0Jan 2020View details →
edi52/100

Photosynthetically active radiation (PAR) time series from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing

To understand seasonality and production as part of the Beaufort Lagoon Ecosystem Long Term Ecological Research program, photosynthetically active radiation (PAR) is recorded in situ, starting August 2018 across the Beaufort Sea coast. Spherical quantum sensors measure PAR ~0.5 m above the benthos at underwater mooring locations and cosine sensors measure incident PAR at the surface at a permanent land-based station.

openCC0Jan 2020View details →
edi48/100

Catalog of GenBank sequence read archive (SRA) entries of 16S and 18S rRNA genes from bacterial and protistan planktonic communities along the Eastern Beaufort Sea coast, North Slope, Alaska, 2011-2013

Microbial communities in the coastal Arctic Ocean experience extreme variability in organic matter and inorganic nutrients driven by seasonal shifts in sea ice extent and freshwater inputs. Lagoons border more than half of the Beaufort Sea coast and provide important habitats for migratory fish and seabirds; yet, little is known about the planktonic food webs supporting these higher trophic levels. To investigate seasonal changes in bacterial and protistan planktonic communities, amplicon sequences of 16S and 18S rRNA genes were generated from samples collected during periods of ice-cover (April), ice break-up (June), and open water (August) from shallow lagoons along the eastern Alaska Beaufort Sea coast from 2011 through 2013. This data package catalogs sequence read archive (SRA) entries available through GenBank BioProject PRJNA530074 at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA530074. This data package is associated with the following publication: Kellogg CTE, McClelland JW, Dunton KH and Crump BC (2019) Strong Seasonality in Arctic Estuarine Microbial Food Webs. Front. Microbiol. 10:2628. doi: 10.3389/fmicb.2019.02628 Environmental variables (physiochemical data from YSI and HOBO data loggers, as well as organic matter analysis and stable isotope data from discrete water samples) associated with this genomic dataset are available from the Arctic Data Center: Kenneth Dunton, Byron Crump, and James McClelland. Physical, chemical, and biological data from lagoons and open coastal waters in the nearshore environment of the eastern Alaska Beaufort Sea, 2011-2013. Arctic Data Center. doi:10.18739/A2DG13. To join the two datasets together, please use the provided site codes (column "site_name" here) and collection dates (column "collection_date" here) in each dataset. Note that the site codes in this package are without hyphens (e.g. JAA) while site codes in the above environmental data package have hyphens (e.g. JA-A). Instead of citing this package which is jus

openCC0Jan 2020View details →
edi48/100

Catalog of GenBank sequence read archive (SRA) entries of metagenomic DNA sequence analyses of bacterial and archaeal water column communities along the Eastern Beaufort Sea coast, North Slope, Alaska, 2012

In contrast to temperate systems, Arctic lagoons that span the Alaska Beaufort Sea coast face extreme seasonality. Nine months of ice cover up to ∼1.7 m thick is followed by a spring thaw that introduces an enormous pulse of freshwater, nutrients, and organic matter into these lagoons over a relatively brief 2–3 week period. Prokaryotic communities link these subsidies to lagoon food webs through nutrient uptake, heterotrophic production, and other biogeochemical processes, but little is known about how the genomic capabilities of these communities respond to seasonal variability. This study characterizes the metabolic capabilities of microbial communities across three seasons in two lagoons and one open coastal site along the eastern Alaska Beaufort Sea coast. We used metagenomic DNA sequence data of bacterial and archaeal water column communities to identify genes of relevant biogeochemical pathways. This data package catalogs sequence read archive (SRA) entries available through GenBank BioProject PRJNA642637 at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA642637. This data package is associated with the following publication: Baker, Kristina D., Colleen T. E. Kellogg, James W. McClelland, Kenneth H. Dunton, and Byron C. Crump. “The Genomic Capabilities of Microbial Communities Track Seasonal Variation in Environmental Conditions of Arctic Lagoons.” Frontiers in Microbiology 12 (2021). https://doi.org/10.3389/fmicb.2021.601901. Environmental variables (physiochemical data from YSI and HOBO data loggers, as well as organic matter analysis and stable isotope data from discrete water samples) associated with this genomic dataset are available from the Arctic Data Center: Kenneth Dunton, Byron Crump, and James McClelland. Physical, chemical, and biological data from lagoons and open coastal waters in the nearshore environment of the eastern Alaska Beaufort Sea, 2011-2013. Arctic Data Center. doi:10.18739/A2DG13. To join the two datasets together, please use the provi

openCC0Apr 2021View details →
zenodo44/100

Audiovisual Vignettes of Sea Ice Ridging in the Beaufort Sea in 2007

<p>This presents footage demonstrating the scales of sea ice motion involved in creating ridges under varied degrees of compression and shear.&nbsp; Sound heard in these vignettes is associated with frictional dissipation of kinetic energy during vertical ice displacement. Images shown were recorded during April 2-15, 2007 UTC, as part of the field campaign: Sea Ice Experiment - Dynamic Nature of the Arctic (SEDNA). Footage and photographs presented in this vignette were taken by Andrew Roberts with the assistance of Jennifer Hutchings and Cathleen Geiger.&nbsp; Funding for SEDNA was provided by&nbsp; the National Science Foundation, grant number OPP ARC 0612527.&nbsp; An overview of the SEDNA field campaign is given in: Hutchings, J. K. et al. (2008), Role of Ice Dynamics in the Sea Ice Mass Balance, <em>Eos Trans. AGU</em>, <em>89</em>(50), doi:10.1029/2008EO500003. &nbsp;</p> <p>[Version 2 includes minor corrections and additions to text in Version 1]</p>

opencc-by-4.0May 2018View details →
zenodo44/100

Water Body Checklists 2019: Beaufort Sea Species List

Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Beaufort Sea using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.

opencc-by-4.0Aug 2024View details →
zenodo44/100

Water Body Checklists: Beaufort Sea Species List

Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Beaufort Sea using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.

opencc-zeroAug 2024View details →
dryad40/100

Morphology of Arctic cod (Boreogadus saida) assessed according to habitat preference and age in the Beaufort Sea

<p><span>Arctic cod (<em>Boreogadus</em> <em>saida</em>) represents the most widespread and abundant fish in the Arctic and is a critical trophic link in its ecosystems. Like many species endemic to the region, it has lost essential habitat as the extent and thickness of sea ice </span><span>have </span><span>declined substantially in recent </span><span>decades. Extreme warming induced by climate change continues to deteriorate polar marine environments. Thus, understanding how Arctic cod uses and partitions its habitat/environment is central to its conservation. We assessed Arctic cod functional morphology using traditional (including gill rakers) and geometric morphometrics and explored whether these differed among habitats and age classes using multivariate techniques. While distinct ecotypes have been proposed, these were not detected in our analyses. Rather, results show similar patterns in the external morphology of Arctic cod across habitats and age classes in the Beaufort Sea. However, analysis of gill rakers revealed concurrent habitat- and age-specific changes likely associated with dietary preferences. Findings indicate that although Arctic cod does not specialise in external morphological features in any habitat, important aspects of its internal feeding morphology </span><span>shift </span><span>as it grows, likely underpinning important distributional changes and the species' critical role in transferring energy in Arctic marine ecosystems.</span></p>

opencc-zeroJul 2023View details →
dryad40/100

Morphology of Arctic cod (Boreogadus saida) assessed according to habitat preference and age in the Beaufort Sea

Open the record for dataset details and reuse information.

publicJul 2023View details →
zenodo36/100

Monitoring recent changes in the Beaufort Sea coast using very high resolution remote sensing

<p>Arctic permafrost coasts are major carbon (Schuur et al., 2015) and mercury pools (Schuster et al., 2018). They represent about 34% of the Earth&rsquo;s coastline, with long sections affected by high erosion rates (Fritz et al, 2017), increasingly threatening coastal communities. Year-round reduction in Arctic sea ice is forecasted and by the end of the 21st century, models indicate a decrease in sea ice area from 43 to 94% in September and from 8 to 34% in February (IPCC, 2014). An increase of the sea-ice free season leads to a longer exposure of coasts to wave action. Further, climate warming is also expected to modify the contribution of terrestrial erosion (Fritz et al., 2015, Ramage et al., 2018, Irrgang et al., 2018). Within the project EU Horizon2020 project NUNATARYUK, we are updating the mapping of the Arctic coast, with the Canadian Beaufort coast as a case-study. The surveying methodology includes: i. a high resolution update of the coastline mapping and change rates using Pleiades (CNES) satellite acquisitions from 2018, ii. a survey using RTK-UAV aerial imagery of long-term monitoring sites from the Canada-US border to King Point, and iii. the experimental use of TerraSAR-X staring spotlight scenes and PAZ at key sites to monitor intraseasonal dynamics of cliff edge retreat. This research is funded by the EC H2020 Project NUNATARYUK. Support on remote sensing imagery access by the WMO Polar Space Task Group.</p>

opencc-by-4.0Nov 2020View details →
dryad36/100

Modeling polar bear (Ursus maritimus) snowdrift den habitat on Alaska's Beaufort Sea coast using SnowDens-3D and ArcticDEM data

<p>Pregnant polar bears (<em>Ursus maritimus</em>) excavate maternal dens in seasonal snowdrifts during fall along Alaska's Beaufort Sea coast to shelter their altricial young during birth and development. With recent sea ice decreases, bears are denning more frequently on land. Each year, the weather and blowing-snow conditions control the creation of snowdrifts across the landscape, and the available snowdrift den habitat can vary widely from one year to the next, depending on the late fall and early winter air temperature, snowfall, and wind speed and direction. We implemented a physics-based, spatiotemporal, polar bear snowdrift den habitat model (SnowDens-3D) across the eastern Alaska Beaufort Sea coast (an area of approximately 17,000 km^2^). High-resolution (2.0 m) topography data were provided by the ArcticDEM, and daily meteorological forcings were provided by NASA's MERRA-2 reanalysis. A 21-year (2000–2020) SnowDens-3D simulation was performed, and model outputs were compared with 91 historical polar bear den locations. The year-specific simulations produced viable den habitat for 98% of the observed den locations. The interannual variation in den habitat area over the 21-year period increased by approximately a factor of three from the minimum year (2001; 554 km^2^) to the maximum year (2017; 1,566 km^2^). This data archive provides the key den and den-habitat datasets produced, used, and analyzed by this project.</p>

opencc-zeroJun 2024View details →
zenodo36/100

Roach et al. (2019) coupled wave-ice model output (hourly coupling version): Beaufort Sea 2012-2019

<p>Wavewatch III model output from Roach et al. (2019) coupled wave-ice model with hourly coupling from the central Beaufort Sea, spanning 2012-2019.</p> <p>See manuscript below for further details:</p> <p>Roach, L., C. Bitz, C. Horvat, and S. Dean (2019), Advances in modelling interactions between sea ice and ocean surface waves. Journal of Advances in Modeling Earth Systems</p>

opencc-by-4.0Oct 2021View details →
dryad36/100

Modeling polar bear (Ursus maritimus) snowdrift den habitat on Alaska’s Beaufort Sea coast using SnowDens-3D and ArcticDEM data

Open the record for dataset details and reuse information.

publicJun 2024View details →
dryad36/100

Summer marine fog distribution in the Chukchi–Beaufort Seas

Open the record for dataset details and reuse information.

publicAug 2022View details →
zenodo32/100

FIGURE 8 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea

FIGURE 8. Plots of principal component scores for (A) morphometric, (B) meristic, and (C) combined morphometric and meristic characters of eastern Pacific and Arctic species of the Careproctus rastrinus species complex lacking a postorbital pore: C. lerikimae n. sp. (♦), C. phasma (□), C. spectrum (▲).

opennotspecifiedDec 2015View details →
zenodo32/100

FIGURE 7 in Snailfishes of the Careproctus rastrinus complex (Liparidae): redescriptions of seven species in the North Pacific Ocean region, with the description of a new species from the Beaufort Sea

FIGURE 7. Plots of principal component scores for (A) morphometric, (B) meristic, and (C) combined morphometric and meristic characters of western Pacific species of the Careproctus rastrinus species complex: C. rastrinus (□), C. trachysoma (), C. acanthodes (♦), and C. pellucidus (▲).

opennotspecifiedDec 2015View 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