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Research about Alaska

Source-linked reports with geographic coverage including Alaska.

At least 91 records · Page 5Linked to original sources
USGS2026

Biomarkers of mortality risks in Yukon Chinook salmon

Premature mortality of spawning adult Pacific salmon ( Oncorhynchus species) can strongly influence population dynamics and complicate escapement-based management. Heat stress and Ichthyophonus infections have been identified as probable drivers of premature mortality in Yukon River Chinook salmon ( Oncorhynchus tshawytscha ) and likely contributors to low spawning abundance. We leveraged a multiagency study focused on Ichthyophonus using lethally collected heart tissue as a rare opportunity to investigate these two stressors jointly in the same individuals to accomplish two tasks: (1) provide a more comprehensive premature mortality risk index that combines heat stress and Ichthyophonus detection and (2) investigate the feasibility of using skeletal muscle tissue gene transcription (mRNA of select genes) as a non-lethal biomarker of Ichthyophonus . Water temperatures ranged from ~12–22°C across four sites and two years. In both 2023 and 2024, effects were identified in ~30% of salmon at Pilot Station, Alaska, and ~70% of salmon by the time they reached mid river (Rapids, Fort Yukon). Mortality risk is presumably highest among fish with multiple stressors, which were detected in ~25% of Chinook salmon in the middle river sites in 2023 when it was warmer and 9—18% in 2024 when it was cooler. We explored Chinook salmon genes that respond to Ichthyophonus with a full transcriptome analysis that measured mRNA of 17,569 genes and identified 53 that were related to Ichthyophonus infection. The differentially expressed genes and their pathways included those known for involvement in immune functions, energy synthesis, cellular breakdown, and reproduction– all processes known to be influenced by senescence during spawning migrations and imply accelerated senescence of infected fish. Primers were developed for 21 of the differentially expressed Chinook salmon genes for qPCR measurements of their mRNA that could be used in classification models. Attempts to statistically deduce Ichthyophonus infection from Chinook salmon gene transcription at the individual and group levels included some potential for separating fish where Ichthyophonus was not detected compared to those with high infection intensities (as judged by qPCR that directly detects Ichthyophonus DNA). Fish with relatively low infection intensities did not have a separate gene transcription signature and grouped with the undetected Ichthyophonus fish in two-thirds of the cases and high infection in onethird of cases. Among the genes with the most utility to predict Ichthyophonus infection were retinoic acid receptor beta (regulates cellular states) and lysozyme CII (immune system gene). Interannual variation in the gene transcription of fish with undetected Ichthyophonus was a complicating factor that demonstrated a need for additional refinement and testing. Overall, this study identified two broad findings: (1) The proportion of migrating fish with one or both of the assessed stressors ( Ichthyophonus infections and/or elevated levels of heat shock protein) can be very high (~70%) and (2) we recommend measuring interannual variation of gene transcription in any study that seeks to develop gene transcription as a biomarker.

Alaska↗
USGS2025

Toward an efficient framework for remote sensing of river bathymetry: Comparing sensors and algorithms on an inaccessible proglacial river in Alaska

Remote sensing can provide reliable information on river depths and this approach might be particularly valuable in areas that are difficult to survey via conventional field methods. In this study, we assessed the potential to map the bathymetry of an inaccessible proglacial river in Alaska from both aerial orthophotos and a multispectral satellite image. In addition, we evaluated a variety of depth retrieval algorithms with different input data requirements, including some methods that require field measurements of water depth for calibration and other techniques that can be applied even when such field data are not available. These approaches might enable more efficient use of remote sensing methods by resource management agencies. Our results suggest that bathymetric mapping along the turquoise-colored river we examined was not only feasible but highly accurate ( R 2 up to 0.94) for both types of image data. Algorithms that use paired observations of depth and reflectance to train depth retrieval models were the most accurate, with errors on the order of 15%–20% and little or no bias. Alternative techniques based on hydraulic and statistical concepts also led to strong agreement between predicted and observed depths but were more susceptible to systematic biases toward under- or over-estimation of depth. In contrast to clear-flowing streams, bathymetric mapping in this environment was enabled by a direct relationship between the depth and brightness of the water due to scattering by suspended sediment. In selecting an appropriate depth retrieval method, a compromise might need to be reached between the level of field effort invested and the accuracy of the resulting image-derived bathymetry. Standalone software for implementing these techniques is freely available.

Alaska↗
USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗
USGS2025

Multi-temporal surface water mapping with high-resolution elevation and image data through weakly supervised deep learning

Monitoring the extent of surface water features (hydrography), accurately storing them in databases, and representing them on topographic maps are essential for various applications such as navigation and policy-making for legislative boundaries and permitting. In this context, hydrographic data includes features that generally have water present or image data showing signs that water is forming a terrain channel, and which would be included in 1:24,000 or larger scale topographic maps. In addition, reliable hydrographic data play a critical role to help manage environmental risks such as droughts, floods, fires, and landslides, as well as monitoring biological resources and pollutants. Inaccuracies in hydrography data can lead to modelling inaccuracies, resulting in economic, social, and environmental risks. However, generating sufficiently accurate high-resolution (HR) hydrography and terrain data for these purposes remains a substantial challenge primarily because of complex surface water dynamics and data handling limitations.

Alaska↗
USGS2025

River ice controls permafrost bank erosion across an Arctic delta

Bank erosion in Arctic rivers helps shape channel geometry, mobilizes carbon from permafrost and influences sediment delivery to the Arctic Ocean. On Alaska's Arctic coastal plain, rivers begin flowing during snowmelt in late spring while extensive river ice persists in channels, such that hydraulics are altered and water is kept cool. The effects of river ice on permafrost bank erosion are poorly understood, primarily due to a dearth of field observations and a lack of river ice in existing models. To address this knowledge gap, we developed a numerical model to simulate the melt of substrate interstitial ice and bank collapse along individual permafrost river banks. We parameterize the model with field observations from riverbanks in three different channels on the Canning River delta, which are disparately impacted by river ice during snowmelt. We explore the bank erosion produced without river ice in the model and with modern river ice model scenarios that we drive with different stages and water temperature boundary conditions. We also compare predicted erosion rates to observations from satellite imagery to validate this approach. In the model, banks are idealized as vertical profiles that rise 1–2 m above the river bed and are comprised of silt- to sand-sized sediment with dense roots in the active layer. Underneath, we generalize bank ice content underneath the active layer to represent ice-rich permafrost on the river corridor boundaries. The model predicts that these ice-rich river banks can erode by 2–6 m/yr. Scenarios without ice underpredict erosion in the distributary channels. Scenarios with varying river ice for different deltaic channels produce erosion rates similar to observations. Our results suggest that the prolonged melt of thick river ice in a delta nonlinearly impacts permafrost bank erosion by blocking river discharge to certain branches, heightening stage across the distributary network and locally limiting river water warming. Given expected changes in air temperature and hydrology, future estimates of Arctic river bank erosion could be improved by considering river ice.

Alaska↗
USGS2025

The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears

Omnivores often face tradeoffs between selecting for spatially dispersed energy-dense vertebrate prey versus densely distributed herbivorous resources that have limited energetic value per unit intake. Arctic grizzly bears ( Ursus arctos ) are large omnivores within a resource-limited ecosystem that are known to exhibit smaller body masses and occur at lower densities than grizzly bears in other regions of North America. We evaluated the energy balance of Arctic grizzly bears during a portion of the fall hyperphagic period in two ecologically differing regions on Alaska’s northern Arctic coast by monitoring mass change, food intake, activity, and energy expenditure of 12 individuals over 17–22 days. Bears in coastal areas were more carnivorous than bears in the foothills that were predominantly herbivorous and frugivorous. Carnivory was associated with greater movement, body fat, and energy expenditure and two of four carnivorous bears lost mass. Overall, the mean body fat of the bears in this study was 34% lower than other grizzly bear populations in North America in the fall. Furthermore, the bears in this study exhibited relatively small changes in body mass (x̄ = 3%, range =−2 to 11%) that were 60% lower than other grizzly bear populations which typically gain substantial mass in the fall in preparation for denning. Our results, while representing a snapshot from a small number of bears during the fall hyperphagic period, are consistent with previous studies and indicate limited availability of energy-dense food resources during this time for grizzly bears in this region of the Arctic.

Alaska↗
USGS2025

Late Quaternary pollen record from southwest Seward Peninsula, western Alaska, and the vegetation history of central Beringia

Pollen analysis of samples from a coastal exposure near Teller, southwestern Seward Peninsula, Alaska, provides a record of vegetation and climate spanning the Last Glacial Maximum (LGM) through the Holocene. The site is near the center of the former Bering Land Bridge (BLB). The oldest pollen-bearing sediment unit is a loess deposit of LGM age, with pollen assemblages that closely resemble LGM assemblages from other key sites in central Beringia spanning 16° of latitude. These fossil assemblages represent vegetation composed primarily of grasses, sedges, Artemisia , willows, and forbs and are interpreted to represent steppe–tundra, associated with dry climates and summer temperatures cooler than at present. LGM mosses did not accumulate insulating layers of peat; the summer active soil layer was deeper than at present. Permafrost with ice wedges and loess deposition were widespread. A regional transition from steppe–tundra vegetation to a dwarf shrub–sedge–moss mesic-to-wetland vegetation began in central Beringia with the onset of Bølling–Allerød (B-A) warming at 14,700 cal yr BP. Warming events of the B-A and early Holocene resulted in widespread development of thermokarst terrain on the BLB and on ice-rich terrain in Western Alaska. Mesic climates and vegetation developed on the BLB during the marine transgression and because of B-A and early Holocene warming. Early Holocene warming allowed some boreal forest species such as alders to begin colonizing Western Alaska from the interior.

Alaska↗
USGS2025

Land cover, elevation, and precipitation predict distribution and hotspots of three bird species of concern in boreal Alaska

The boreal forest biome is an important breeding area for migratory birds and is undergoing rapid changes, including drying of wetlands, changes to vegetation composition, and human development. Many boreal bird populations are declining, but information is often lacking on how these species associate with habitat characteristics and thus how they may respond to changing conditions. We used a large point-count dataset to describe habitat associations and hotspots for three boreal species of concern in Alaska, USA: Tringa flavipes (Lesser Yellowlegs), Contopus cooperi (Olive-sided Flycatcher), and Euphagus carolinus (Rusty Blackbird). We used an N-mixture model to evaluate covariates of abundance and two components of detection (availability and perceptibility). We then used the estimated relationships with covariates to predict density of each species across the Northwestern Interior Forest (Bird Conservation Region 4) in Alaska, including identifying hotspots where density was predicted to be in the top 10% of all locations. T. flavipes and E. carolinus were associated with wetlands and mean values of June precipitation; T. flavipes were also associated with low elevation and recent fire; and C. cooperi was associated with needleleaf forest and moderate elevation. Hotspots for T. flavipes and E. carolinus usually overlapped, while hotspots for C. cooperi almost never overlapped with those of the other two species. Following ground-truthing, these predicted distributions could be used to indicate areas of high importance for species of conservation concern and thus inform management decisions and mitigation measures. Our results could also help identify areas that are likely to be important for these species in the future, given the rapid changes now occurring across the boreal biome in response to climate warming and drying.

Alaska↗
USGS2025

The 1912 Ms 7.2 earthquake in the Denali region of central Alaska

The 2002 M w 7.9 earthquake in central Alaska ruptured 340 km on three faults—Susitna Glacier thrust fault, Denali fault, Totschunda fault—crossing both the Richardson Highway and the Alaska Pipeline. Its occurrence prompted renewed interest in historical large earthquakes that possibly originated on the Denali fault. One of these earthquakes was a M s 7.2 event on July 7, 1912, which we revisit with two approaches: (1) probabilistic relocation of the epicenter using globally recorded arrival times, and (2) compilation and reassessment of shaking intensity reports to estimate a macroseismic epicenter. Our preferred instrumental epicenter is west of the Parks Highway and in agreement with the maximum‐reported shaking, which was from the Parker–Browne expedition of Denali. We also relocated a M s 6.4 aftershock, whose epicenter is 11 km from the mainshock. Candidate faults for the 1912 earthquake include the Denali fault, the McLeod Creek thrust fault, and the Kantishna Hills thrust fault. Future analysis of active faults, paleoseismic results, 1912 instrumental data, and 1912 felt reports may help in interpreting the fault and mechanism of the 1912 earthquake.

Alaska↗
USGS2025

Searching for seismic precursors - The Barry Landslide hazard clean up

The Barry Landslide, located in Barry Arm of Prince William Sound, Alaska, poses a major hazard due to its steep, unstable slopes and the potential for a massive landslide-generated tsunami. With an estimated volume of 500–700 million cubic meters, the Barry Landslide could trigger highly destructive waves. In this study, we focus on seismic signals from the Barry Landslide, which are critical for providing timely tsunami warnings. Since the summer of 2020, the region has been instrumented to monitor the landslide, but the seismic record is complicated by the presence of nearby glaciers and frequent regional earthquakes. Among these signals, we analyze a specific class of short-duration, high-frequency seismic events that exhibit strong seasonal variability, increasing in rate from late summer to mid-winter before ceasing abruptly in late winter or early spring. Our analysis suggests that the source of these signals is likely near or beneath Cascade Glacier, adjacent to the landslide, rather than within the landslide mass itself. We apply detection algorithms to construct a time history for this signal type, which we then compare with environmental factors like precipitation, temperature, and slope displacement data from ground-based radar and remote sensing. Correlations indicate that these seismic events may be driven by seasonal hydrological changes, particularly the freeze-up of subglacial water pathways. While these events are not directly linked to landslide motion, they serve as indirect markers of subsurface hydrological conditions that influence slope stability. Our findings highlight the complex interplay between glaciers, groundwater, and landslide dynamics, emphasizing the need for multi-parameter monitoring to assess evolving geohazards in the region.

Alaska↗
USGS2025

High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting

The Minto Flats fault zone (MFFZ) in central Alaska is a left‐lateral strike‐slip fault system situated between the continental‐scale right‐lateral Denali and Kaltag‐Tintina faults. The MFFZ has the potential to generate magnitude 7 earthquakes, and it hosted a magnitude 6 earthquake in 1995. It has also produced exotic events, such as very‐low‐frequency earthquakes and nucleation signals. We use network‐matched filtering and relative earthquake relocation techniques to derive a detailed catalog of earthquake locations for the MFFZ. The catalog spans from August 2014 to December 2019, a time period including 13 temporary seismic stations in the region. Our results provide the most complete catalog for the MFFZ and include deeper events, clusters of shallow seismicity, and a complex and segmented fault structure not observed in the original regional catalog. We document right‐lateral strike‐slip faulting, conjugate to the main northeast‐striking left‐lateral faults of the MFFZ. Below Nenana basin, the relocated seismicity reveals northwest‐dipping left‐lateral faults, supporting the inference that deep crustal active faulting is associated with recent basin deformation.

Alaska↗
USGS2025

Geochemical evidence for the origin of late Quaternary loess, Seward Peninsula, Alaska

Loess is the most widespread surficial deposit in the state of Alaska. Although loess of last glacial age is common in mid-continental North America, records of last glacial loess in Alaska have been elusive. Here we report a record of last glacial loess on the Seward Peninsula, along with studies of a transect of loess localities also thought to date to the last glacial period. Highly diverse hypotheses on the origin of loess on the Seward Peninsula include local volcanic rocks and mountain ranges to the north and south, as well as offshore deposits. We present particle size and mineralogical and geochemical data that indicate that the most likely sources for loess in this part of eastern Beringia are glaciogenic silt particles of the Kobuk River and Noatak River, both of which drain the Brooks Range to the northeast. Northeasterly paleowinds were therefore responsible for loess on the Seward Peninsula. Such winds probably occurred during late summer or early autumn, when river discharge was at a minimum but temperatures were still above freezing. Northeasterly winds during the last glacial period are in good agreement with a recent paleoclimate model.

Alaska↗
USGS2025

Mount Spurr volcano, August 18, 1992: The eruption heard around Alaska

The August 18, 1992, eruption of Mount Spurr volcano, Alaska, produced an impressive Vulcanian to Subplinian eruption column reaching up to 40 km above sea level that blanketed the nearby city of Anchorage with ash. At the time of the eruption, the Alaska Volcano Observatory received reports of audible sound hundreds of kilometers from the source from a variety of azimuths from the volcano and found the pattern that did not solely depend on distance. Explosions are generally inaudible to the human ear at these distances due to the attenuation of sound in the atmosphere as the energy propagates, but low-frequency sound waves (infrasound) persist and can be used to detect and characterize eruptions. Similar reports of zones of audible sounds at great distances have been observed from notable eruptions such as Krakatau 1883, Mount St. Helens 1980, Mount Pinatubo 1991, and Hunga volcano 2022. We perform infrasound propagation modeling to help understand the unique distribution of audible reports, finding that areas with favorable infrasound propagation may help explain areas in which nonlinear propagation, including energy cascading effects into higher frequencies that are audible to the human ear, may have occurred.

Alaska↗
USGS2025

Assessing coastal wetland carbon and mineral accumulation response to changing climate, Cape Espenberg, Alaska

The Arctic is experiencing warming and ecological shifts due to climate change and the compounding effects of polar amplification. Arctic Alaskan coastal marsh environments, such as the Cape Espenberg barrier beach system, offer an opportunity to determine the carbon cycle response to changing climate by examining sediment records that have been preserved through time as shoreline-parallel, linear geometry prograding geomorphic features. This study determines the carbon and mineral accumulation trends in marsh environments at Cape Espenberg for both paleo (~776 CE to 1850 CE) and modern (post-1850 CE) time frames. A comprehensive physical and chemical dataset, including radioisotope (137Cs, 210Pb, 14C), stable isotope (δ13C), element concentration (%C, %N, C:N), and dry bulk density, has been built for several sediment cores. Results indicate that carbon and mineral accumulation rates have increased from paleo to modern times, potentially because of better growing and preservation conditions for organic matter in a modern climate. Paleoclimate trends in the Medieval Climate Anomaly (MCA) and warm periods interspersed within the Little Ice Age (LIA) also correlate with greater contributions of wetland organic matter, as evidenced by lighter δ13C values. Cold climate periods within the LIA correlate with increased aquatic organic matter sourcing and heavier δ13C values, with some spikes of wetland sources interspersed throughout the LIA. Future temperatures are predicted to rise with global climate change, which may continue to expand carbon stores in Arctic coastal wetland sediments. This has been observed in the swale environments at Cape Espenberg, where increasingly favourable growing and soil-preservation conditions (i.e. wet/anoxic soils and lower salinity to limit organic material decay, higher temperatures to promote growth) are increasing the carbon storage within Arctic coastal carbon reservoirs.

Alaska↗
USGS2025

Sea-level driven isolation of glacial plant refugia revealed by submerged lake sediment from the Bering Land Bridge and St. Matthew Island

Bering Land Bridge (BLB) climate and vegetation during the Last Glacial Maximum (LGM) remains largely understudied, given challenges associated with collecting records from the submerged BLB. Previous records, confined to the margins of the modern land area and adjacent shelf, reveal conflicting interpretations of Beringian vegetation during the LGM. Here, we reconstruct LGM vegetation, sedimentology, and stable isotopes from a central BLB paleo-lake (Lake Knebel, LK) and compare it with a Holocene peat record from nearby St. Matthew Island (SMI). Results show strong similarities between LGM and late Holocene pollen assemblages, although with differences in relative taxonomic abundance. LGM communities are consistent with a cold and dry steppe or herb tundra environment but suggest the possibility of localized Betula presence in low-lying areas. LK’s bedded lacustrine stratigraphy transitions into undisturbed marine sediments by ~19 ka, providing a maximum limiting age of the transgression. Shrub absence on SMI today and during the Holocene is consistent with island isolation before ~14 to 15 ka, when Betula expanded rapidly at most sites with Bølling-Allerød warming. The combined vegetation evidence indicates preservation of LGM tundra and steppe vegetation assemblages on SMI, suggesting that island vegetation communities may provide additional constraints on the timing of sea level transgression.

Alaska↗
USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗
USGS2025

Monitoring Pacific walrus coastal haulouts by satellite to estimate herd abundance and distribution

The Pacific walrus ( Odobenus rosmarus divergens ) has a single, panmictic stock that ranges across the Bering and Chukchi Seas. However, its seasonal distribution is incompletely described, particularly in autumn when herds gather on shore, and abundance is of interest to management entities. We monitored walrus herds using satellite imagery on shore across their summer and autumn range in the Chukchi Sea to provide insights on seasonal distribution and abundance. During each study year (2017–2024), we documented walrus herd abundance at 8 Chukchi Sea haulouts based on the herd area detected in satellite imagery multiplied by herd density estimates derived from aerial survey data. In contrast to historical seasonal use, we found large herds on shore at only 3 sites, 1 in Alaska and 2 in northern Chukotka (Russia). In 2022, we observed a very large herd with an abundance (and 90% prediction interval) of 184,000 (min–max = 153,000–214,000) northwest of the Bering Strait, which enabled us to estimate a minimum population size (N min ) by correcting the abundance estimate by the proportion of walruses that may be hauled out and available for detection. Our estimate of 250,000 was commensurate with the N min estimate (214,000) from a 2013–2017 Pacific walrus genetic mark-recapture study.

Alaska↗