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49 results for “Gulf of Alaska”
Temperature, Salinity, Sound Velocity, Location, Depth, Heading, and Velocity measured aboard the R/V Nanuq for the Northern Gulf of Alaska LTER site, 2020-2021
This dataset describes measurements from a thermosalinograph and navigation device used aboard the R/V Nanuq during cruises in Resurrection Bay and the Gulf of Alaska. Thermosalinograph data includes temperature, salinity, conductivity, and sound speed measurements every five seconds while the instrument was in use. Navigation data describes latitude, longitude, depth, heading, course over ground, and speed over ground. Data are collected on R/V Nanuq using the ship's GPS devices and a Seabird Electronics SBE-45 thermosalinograph (TSG) that samples uncontaminated pumped seawater. Temperature and conductivity data are sampled every 5 seconds and salinity and sound velocity are derived parameters. No data quality control has been applied to this data, so users should be cautious that conductivity, salinity and sound speed dropouts to due bubbles are common when the ship is plowing through large waves. Data are collected by a variety of projects, including from the NSF-funded Northern Gulf of Alaska Long Term Ecological Research (NGA LTER) program, the Exxon Valdez Oil Spill Trustee Council (EVOSTC) Gulf Watch Alaska GAK1 project, the UAF Sub-Arctic Oceanography Field Course, the Alaska Ocean Observing System (AOOS) glider program, and others.
Rhizaria abundance, biomass, and trophic interactions at the Northern Gulf of Alaska LTER site during summer 2023 cruise KM2308
This dataset consists of Rhizaria abundance, biomass, number of individuals with captured prey, and number of individuals that interacted with algal cells, by taxonomic group. Taxonomic group ID characteristics and biomass calculation details are also presented. Sampling occurred on NGA-LTER research cruise KM2308 during summer 2023 at four stations and four different depth-intervals. Seawater samples were collected from CTD-secured Niskin bottles, concentrated by reverse filtration with 50 μm mesh, and analyzed back in the lab with inverted epi-fluorescence microscopy. Excel spreadsheets were converted to CSV files for preservation. These data are part of the Northern Gulf of Alaska Long Term Ecological Research (NGA LTER) program. The LTER program is a National Science Foundation–funded network of 28 sites nationwide that focus on the influence of long-term and large-scale phenomenon on ecosystems. Additional funding for sampling is provided by the North Pacific Research Board (NPRB), the Alaska Ocean Observing System (AOOS), and the Exxon Valdez Oil Spill Trustee Council (EVOS) via the Gulf Watch Alaska program.
Water Body Checklists 2019: Gulf of Alaska 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 Gulf of Alaska 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.
Water Body Checklists: Gulf of Alaska 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 Gulf of Alaska 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.
Exploring variability in the diet of depredating sperm whales in the Gulf of Alaska through stable isotope analysis
Sperm whales interact with commercially important groundfish fisheries offshore in the Gulf of Alaska (GOA). This study aims to use stable isotope analysis to better understand the trophic variability of sperm whales and their potential prey, and to use dietary mixing models to estimate the importance of prey species to sperm whale diets. We analyzed tissue samples from sperm whales and seven potential prey (five groundfish and two squid species). Samples were analyzed for stable carbon and nitrogen isotope ratios, and diet composition was estimated using Bayesian isotopic mixing models. Mixing model results suggest that an isotopically combined sablefish/dogfish group, skates, and rockfish make up the largest proportion of sperm whale diets (35%, 28% and 12%) in the GOA. The top prey items of whales that interact more frequently with fishing vessels consisted of skates (49%) and the sablefish/dogfish group (24%). This is the first known study to provide an isotopic baseline of adult male sperm whales and these adult groundfish and offshore squid species, and to assign contributions of prey to whale diets in the GOA. This study provides information to commercial fishermen and fisheries managers to better understand trophic connections of important commercial species.
Concentrations of the rare earth elements (REE) and Thorium-232 (232Th) in glacial dust from the northern Gulf of Alaska region
<p>Concentrations of the rare earth elements (REE) and Thorium-232 (232Th) are presented for filtered air (dust) samples collected from the northern Gulf of Alaska region, including from Middleton Island (AK)(59.4214 N, 146.3493 W) and the Copper River delta (60.4324 N, 145.0954 W). Size-fractionated samples were collected in November 2019, using a Tisch Volumetric Flow Controlled (VFC) high volume sampler (Tisch Environmental, TE-5170V- BL) outfitted with a Cascade impactor. The six size fractions collected ranged from <0.49 micrometers (um) to >7.2 um in diameter. This sampler technology is discussed in greater detail in Morton et al, 2013. Samples were filtered with acid-washed Whatman 41 (W41) cellulose fiber filters. Additional bulk dust samples were collected in October 2012, using a Thermo Partisol Plus 2025 using Teflon filters. Samples were fully digested using concentrated nitric and hydrofluoric acids, following the approach of Morton et al, 2013. Samples were analyzed using a Thermofisher iCAP inductively coupled plasma mass spectrometer (ICP-MS) in KED mode, with He as a collision cell gas, adapted from the approach of Trommetter et al (2020). Concentrations were determined from standard curves using a REE ICP-MS standard from High-Purity Standards (that also contained 232Th). Three internal standards (Ge, In, and Bi) were added to both samples and standards, to correct for short-term variability in the instrument response and to evaluate stability of mass response during the ICP-MS run. Concentration estimates for the REE and 232Th were blank-corrected using full-process blanks that included filters deployed during times when there was no known dust deposition. Most of the full-process blank concentrations were 100 times or more smaller than the concentrations of our lowest standard (with the exception of Ce, the concentration of which was ~seven times smaller than our lowest standard. This means that our blank concentrations were very low but also not quantified extremely accurately. Our best estimates are that the full-process blanks, including filters, ranged from 0.02 picograms per square centimeter (pg cm-2) for Eu, Tb, and Ho, to 2 pg cm-2 for Ce. These blank concentrations were in all cases 40 times or more smaller than our lowest REE sample concentration for the <0.49 um size fraction with the smallest amount of dust, and ~3 orders of magnitude smaller than the signal of the largest samples. The REE data are also presented in a double-normalized format that first normalizes to concentrations of Post Archean Australian Shale and then normalizes to the mean REE concentration. The normalization approach is slightly modified from that of Serno et al, 2014.</p>
Fig. 1 in Catch of Coho Salmon (Oncorhynchus kisutch) Infected with the Freshwater Parasite Salvelinema walkeri (Nematoda: Cystidicolidae) in the Gulf of Alaska in the Early Winter
Fig. 1. Locations of salmonid collection along a south-north transect (from 44°32′N to 52°06′N along ca. 145°W) in the Gulf of Alaska in mid-December 1992 and those of salmonids infected with Salvelinema walkeri in marine and estuarine waters based in this and past papers. Open circles, catch locations of infected salmonids; closed circles, locations with salmonid catch; and crosses, locations without salmonid catch. Location 1, 52°06′N, 145°56′W (this paper); location 2, the Columbia River estuary (Claxton et al. 2013); location 3, off Newport, Oregon (Olson 1978); locations 4 and 5, the Strait of Georgia near Nanoose (Margolis 1967a) and Nanaimo (Ekbaum 1935, 1936; Margolis 1967a), respectively; and locations 6–10, Cowichan Bay, Satellite Channel, the Strait of Juan de Fuca, Sechelt Inlet, and Howe Sound, respectively (Godfrey 1968).
Exploring variability in the diet of depredating sperm whales in the Gulf of Alaska through stable isotope analysis
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Concentrations of the rare earth elements (REE) and Thorium-232 (232Th) in glacial dust from the northern Gulf of Alaska region
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Spatio-temporal persistence of zooplankton communities in the Gulf of Alaska
<p class="BodyAA">Spatial structuring of mid-trophic level forage communities in the Gulf of Alaska (GoA) is poorly understood, even though it has clear implications for the health of fisheries and marine wildlife populations. Here, we test the hypothesis that summertime (May-August) mesozooplankton communities are spatially-persistent across years of varying ocean conditions, including during the marine heatwave of 2014-2016<span><span>. </span></span> We use spatial ordinations and hierarchical clustering of Continuous Plankton Recorder (CPR) sampling over 17 years (2000-2016) to (1) characterize typical zooplankton communities in different regions of the GoA, and (2) investigate spatial structuring relative to variation in ocean temperatures and circulation. Five regional communities were identified, each representing distinct variation in the abundance of 18 primary zooplankton taxa: a distinct cluster of coastal taxa on the continental shelf north of Vancouver Island; a second cluster in the western GoA associated with strong currents and cold water east of Unimak Pass; a shelf break cluster rich in euphausiids found at both the eastern and western margins of the GoA; a broad offshore cluster of abundant pelagic zooplankton in the southern GoA gyre associated with stable temperature and current conditions; and a final offshore cluster exhibiting low zooplankton abundance concentrated along the northeastern arm of the subarctic gyre where ocean conditions are dominated by eddy activity. When comparing years of anomalous warm and cold sea surface temperatures, we observed change in the spatial structure in coastal communities, but little change (i.e., spatial persistence) in the northwestern GoA basin. Whereas previous studies have shown within-region variability in zooplankton communities in response to ocean climate, we highlight both consistency and change in regional communities, with interannual variability in shelf communities and persistence in community structure offshore. These results suggest greater variability in coastal food webs than in the central portion of the GoA, which may be important to energy exchange from lower to upper trophic levels in the mesoscale biomes of this ecosystem.</p>
Data from: Non-stationary climate-salmon relationships in the Gulf of Alaska
Studies of climate effects on ecology often account for non-stationarity in individual physical and biological variables, but rarely allow for non-stationary relationships among variables. Here, we show that non-stationary relationships among physical and biological variables are central to understanding climate effects on salmon (Onchorynchus spp.) in the Gulf of Alaska during 1965-2012. The relative importance of two leading patterns in North Pacific climate, the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), changed around 1988/89 as reflected by changing correlations with leading axes of sea surface temperature variability. Simultaneously, relationships between the PDO and Gulf of Alaska environmental variables weakened, and long-standing temperature-salmon and PDO-salmon covariance declined to zero. We propose a mechanistic explanation for changing climate-salmon relationships in terms of non-stationary atmosphere-ocean interactions coinciding with changing PDO-NPGO relative importance. We also show that regression models assuming stationary climate-salmon relationships are inappropriate over the multidecadal time scale we consider. Relaxing assumptions of stationary relationships markedly improved modeling of climate effects on salmon catches and productivity. Attempts to understand the implications of changing climate patterns in other ecosystems might also be aided by the application of models that allow associations among environmental and biological variables to change over time.
Data from: Non-stationary climate-salmon relationships in the Gulf of Alaska
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Spatio-temporal persistence of zooplankton communities in the Gulf of Alaska
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Data from: Geographic variation in diet, prey resources and exposure to parasites and saxitoxin in Steller sea lions in the Gulf of Alaska
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Examples of killer whale (Orcinus orca) calls from passive acoustic monitoring in the Gulf of Alaska
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FIGURE 16 in New species of sponges (Porifera, Demospongiae) from the Aleutian Islands and Gulf of Alaska
FIGURE 16. Raspailia (Hymerhaphiopsis) fruticosa n. sp. A. Holotype on a bivalve shell (Astarte sp.). Grid marks are 1 cm. B. Polyspicular tract with echinating acanthotylostyle. Scale bar is 100 µm. C. Two echinating acanthotylostyles. Scale bar is 100 µm. D. Smooth choanosomal style. Scale bar is 100 µm. E. Echinating acanthotylostyle among styles. Scale bar is 20 µm.
FIGURE 15.Stelodoryx siphofuscus n in New species of sponges (Porifera, Demospongiae) from the Aleutian Islands and Gulf of Alaska
FIGURE 15.Stelodoryx siphofuscus n. sp. A. Thick choanosomal styles and thin ectosomal anisotornotes and scattered isochelas. Scale bar is 100 µm. B. Terminal tooth on thicker end of ectosomal anisotornote. Scale bar is 10 µm. C. Large category of isochela, shaft twisted. Scale bar is 20 µm. D. Detail of (C), showing the shaft merging into alae. Scale bar is 10 µm. E. Small category of isochelas. Scale bar is 20 µm. F. Small category of isochela. View on top of alae. Scale bar is 2 µm.
FIGURE 14. Stelodoryx siphofuscus n in New species of sponges (Porifera, Demospongiae) from the Aleutian Islands and Gulf of Alaska
FIGURE 14. Stelodoryx siphofuscus n. sp. A. Holotype, probably broken stalk on the right. Scale is 5 x 1 cm. B. Smooth outer surface of the tube. Square is 1 cm. C. Section through the tube. Tube walls are light brown. Inner wall (darker brown) with larger openings visible. Square is 1 cm. D. Ectosome, nearly square brushes of thin ectosomal anisotornotes. Scale bar is 300 µm. E. Choanosomal reticulation of ascending thicker spicule tracts and connecting thinner tracts. Scale bar is 300 µm.
FIGURE 12. Stelodoryx mucosa n in New species of sponges (Porifera, Demospongiae) from the Aleutian Islands and Gulf of Alaska
FIGURE 12. Stelodoryx mucosa n. sp. A. Holotype. Grid marks are 1 cm. B. Detail of holotype surface. C. Section perpendicular to surface showing choanosomal reticulation of acanthostyles and ectosomal tylote bundles. Scale bar is 400 µm. D. Ectosomal brushes of tylotes on choanosomal reticulation. Scale bar is 400 µm. E. Choanosomal reticulation of acanthostyles. Scale bar is 400 µm. F. Ectosomal tylote with microspined ends among acanthostyles and numerous sigmas. Scale bar is 100 µm.
FIGURE 11 in New species of sponges (Porifera, Demospongiae) from the Aleutian Islands and Gulf of Alaska
FIGURE 11. Coelosphaera (Histodermion) kigushimkada n. sp. A. Choanosomal acanthostyle among other spicules. Scale bar is 100 µm. B. Ectosomal tornote (upper left to lower right) among other spicules. Scale bar is 100 µm. C. Arcuate isochelae. Scale bar is 20 µm.
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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)
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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.