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At least 1,657 records · Page 92Linked to original sources
USGS2018

Remotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LiDAR data

This study uses an airborne Light Detection and Ranging (LiDAR) survey, historical aerial photography and historical climate data to describe the character and dynamics of the Nogahabara Sand Dunes, a sub-Arctic dune field in interior Alaska’s discontinuous permafrost zone. The Nogahabara Sand Dunes consist of a 43-km 2 area of active transverse and barchanoid dunes within a 3200-km 2 area of vegetated dune and sand sheet deposits. The average dune height in the active portion of the dune field is 5.8 m, with a maximum dune height of 28 m. Dune spacing is variable with average crest-to-crest distances for select transects ranging from 66–132 m. Between 1952 and 2015, dunes migrated at an average rate of 0.52 m a −1 . Dune movement was greatest between 1952 and 1978 (0.68 m a −1 ) and least between 1978 and 2015 (0.43 m a −1 ). Dunes migrated predominantly to the southeast; however, along the dune field margin, net migration was towards the edge of the dune field regardless of heading. Better constraining the processes controlling dune field dynamics at the Nogahabara dunes would provide information that can be used to model possible reactivation of more northerly dune fields and sand sheets in response to climate change, shifting fire regimes and permafrost thaw.

Remote Sensing↗
USGS2021

Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs

Observational data of coastal change over much of the Arctic are limited largely due to its immensity, remoteness, harsh environment, and restricted periods of sunlight and ice-free conditions. Barter Island, Alaska, is one of the few locations where an extensive, observational dataset exists, which enables a detailed assessment of the trends and patterns of coastal change over decadal to annual time scales. Coastal bluff and shoreline positions were delineated from maps, aerial photographs, and satellite imagery acquired between 1947 and 2020, and at a nearly annual rate since 2004. Rates and patterns of shoreline and bluff change varied widely over the observational period. Shorelines showed a consistent trend of southerly erosion and westerly extension of the western termini of Barter Island and Bernard Spit, which has accelerated since at least 2000. The 3.2 km long stretch of ocean-exposed coastal permafrost bluffs retreated on average 114 m and at a maximum of 163 m at an average long-term rate (70 year) of 1.6 ± 0.1 m/yr. The long-term retreat rate was punctuated by individual years with retreat rates up to four times higher (6.6 ± 1.9 m/yr; 2012–2013) and both long-term (multidecadal) and short-term (annual to semiannual) rates showed a steady increase in retreat rates through time, with consistently high rates since 2015. A best-fit polynomial trend indicated acceleration in retreat rates that was independent of the large spatial and temporal variations observed on an annual basis. Rates and patterns of bluff retreat were correlated to incident wave energy and air and water temperatures. Wave energy was found to be the dominant driver of bluff retreat, followed by sea surface temperatures and warming air temperatures that are considered proxies for evaluating thermo-erosion and denudation. Normalized anomalies of cumulative wave energy, duration of open water, and air and sea temperature showed at least three distinct phases since 1979: a negative phase prior to 1987, a mixed phase between 1987 and the early to late 2000s, followed by a positive phase extending to 2020. The duration of the open-water season has tripled since 1979, increasing from approximately 40 to 140 days. Acceleration in retreat rates at Barter Island may be related to increases in both thermodenudation, associated with increasing air temperature, and the number of niche-forming and block-collapsing episodes associated with higher air and water temperature, more frequent storms, and longer ice-free conditions in the Beaufort Sea.

Alaska↗
USGS2024

Segment anything model can not segment anything: Assessing AI foundation model's generalizability in permafrost mapping

This paper assesses trending AI foundation models, especially emerging computer vision foundation models and their performance in natural landscape feature segmentation. While the term foundation model has quickly garnered interest from the geospatial domain, its definition remains vague. Hence, this paper will first introduce AI foundation models and their defining characteristics. Built upon the tremendous success achieved by Large Language Models (LLMs) as the foundation models for language tasks, this paper discusses the challenges of building foundation models for geospatial artificial intelligence (GeoAI) vision tasks. To evaluate the performance of large AI vision models, especially Meta’s Segment Anything Model (SAM), we implemented different instance segmentation pipelines that minimize the changes to SAM to leverage its power as a foundation model. A series of prompt strategies were developed to test SAM’s performance regarding its theoretical upper bound of predictive accuracy, zero-shot performance, and domain adaptability through fine-tuning. The analysis used two permafrost feature datasets, ice-wedge polygons and retrogressive thaw slumps because (1) these landform features are more challenging to segment than man-made features due to their complicated formation mechanisms, diverse forms, and vague boundaries; (2) their presence and changes are important indicators for Arctic warming and climate change. The results show that although promising, SAM still has room for improvement to support AI-augmented terrain mapping. The spatial and domain generalizability of this finding is further validated using a more general dataset EuroCrops for agricultural field mapping. Finally, we discuss future research directions that strengthen SAM’s applicability in challenging geospatial domains.

Remote Sensing↗
USGS2012

Characterizing post-drainage succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI data

Drained thermokarst lake basins accumulate significant amounts of soil organic carbon in the form of peat, which is of interest to understanding carbon cycling and climate change feedbacks associated with thermokarst in the Arctic. Remote sensing is a tool useful for understanding temporal and spatial dynamics of drained basins. In this study, we tested the application of high-resolution X-band Synthetic Aperture Radar (SAR) data of the German TerraSAR-X satellite from the 2009 growing season (July–September) for characterizing drained thermokarst lake basins of various age in the ice-rich permafrost region of the northern Seward Peninsula, Alaska. To enhance interpretation of patterns identified in X-band SAR for these basins, we also analyzed the Normalized Difference Vegetation Index (NDVI) calculated from a Landsat-5 Thematic Mapper image acquired on July 2009 and compared both X-band SAR and NDVI data with observations of basin age. We found significant logarithmic relationships between (a) TerraSAR-X backscatter and basin age from 0 to 10,000 years, (b) Landat-5 TM NDVI and basin age from 0 to 10,000 years, and (c) TerraSAR-X backscatter and basin age from 50 to 10,000 years. NDVI was a better indicator of basin age over a period of 0–10,000 years. However, TerraSAR-X data performed much better for discriminating radiocarbon-dated basins (50–10,000 years old). No clear relationships were found for either backscatter or NDVI and basin age from 0 to 50 years. We attribute the decreasing trend of backscatter and NDVI with increasing basin age to post-drainage changes in the basin surface. Such changes include succession in vegetation, soils, hydrology, and renewed permafrost aggradation, ground ice accumulation and localized frost heave. Results of this study show the potential application of X-band SAR data in combination with NDVI data to map long-term succession dynamics of drained thermokarst lake basins.

Alaska↗
USGS2018

Alaska snowpack response to climate change: Statewide snowfall equivalent and snowpack water scenarios

Climatically driven changes in snow characteristics (snowfall, snowpack, and snowmelt) will affect hydrologic and ecological systems in Alaska over the coming century, yet there exist no projections of downscaled future snow pack metrics for the state of Alaska. We updated historical and projected snow day fraction (PSF, the fraction of days with precipitation falling as snow) from McAfee et al. We developed modeled snowfall equivalent (SFE) derived from the product of snow-day fraction (PSF) and existing gridded precipitation for Alaska from Scenarios Network for Alaska and Arctic Planning (SNAP). We validated the assumption that modeled SFE approximates historical decadally averaged snow water equivalent (SWE) observations from snowcourse and Snow Telemetry (SNOTEL) sites. We present analyses of future downscaled PSF and two new products, October–March SFE and ratio of snow fall equivalent to precipitation (SFE:P) based on bias-corrected statistically downscaled projections of Coupled Model Intercomparison Project 5 (CMIP5) Global Climate Model (GCM) temperature and precipitation for the state of Alaska. We analyzed mid-century (2040–2069) and late-century (2070–2099) changes in PSF, SFE, and SFE:P relative to historical (1970–1999) mean temperature and present results for Alaska climate divisions and 12-digit Hydrologic Unit Code (HUC12) watersheds. Overall, estimated historical the SFE is reasonably well related to the observed SWE, with correlations over 0.75 in all decades, and correlations exceeding 0.9 in the 1960s and 1970s. In absolute terms, SFE is generally biased low compared to the observed SWE. PSF and SFE:P decrease universally across Alaska under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 emissions scenarios, with the smallest changes for RCP 4.5 in 2040–2069 and the largest for RCP 8.5 in 2070–2099. The timing and magnitude of maximum decreases in PSF vary considerably with regional average temperature, with the largest changes in months at the beginning and end of the snow season. Mean SFE changes vary widely among climate divisions, ranging from decreases between −17 and −58% for late twenty-first century in southeast, southcentral, west coast and southwest Alaska to increases up to 21% on the North Slope. SFE increases most at highest elevations and latitudes and decreases most in coastal southern Alaska. SFE:P ratios indicate a broad switch from snow-dominated to transitional annual hydrology across most of southern Alaska by mid-century, and from transitional to rain-dominated watersheds in low elevation parts of southeast Alaska by the late twenty-first century.

Alaska↗
USGS1997

Gas hydrate resources of northern Alaska

Large amounts of natural gas, composed mainly of methane, can occur in arctic sedimentary basins in the form of gas hydrates under appropriate temperature and pressure conditions. Gas hydrates are solids, composed of rigid cages of water molecules that trap molecules of gas. These substances are regarded as a potential unconventional source of natural gas because of their enormous gas-storage capacity. Most published gas hydrate resource estimates are highly simplified and based on limited geological data. The gas hydrate resource assessment for northern Alaska presented in this paper is based on a "play analysis" scheme, in which geological factors controlling the accumulation and preservation of gas hydrates are individually evaluated and risked for each hydrate play. This resource assessment identified two gas hydrate plays; the in-place gas resources within the gas hydrates of northern Alaska are estimated to range from 6.7 to 66.8 trillion cubic metres of gas (236 to 2,357 trillion cubic feet of gas), at the 0.50 and 0.05 probability levels respectively. The mean in-place hydrate resource estimate for northern Alaska is calculated to be 16.7 trillion cubic metres of gas (590 trillion cubic feet of gas). If this assessment is valid, the amount of natural gas stored as gas hydrates in northern Alaska could be almost seven times larger then the estimated total remaining recoverable conventional natural gas resources in the entire United States.

Alaska↗
USGS2022

Comparison of indices to infer population dynamics of black brant

To aid managers in assessing status of Pacific black brant Branta bernicla nigricans (hereafter brant), I examined pre-existing long-term data series from summer, fall staging, and wintering areas to infer overall population processes and assessed the utility of the various data sources. Variation in demographic parameters measured in subarctic and Arctic locations suggests some form of metapopulation structure likely exists for brant. I used serial autocorrelation coefficients to assess the ability of various indices to track population processes. Based on this approach, the Lincoln–Petersen estimator and the fall aerial survey estimate partitioned using age ratios of staging brant at Izembek Lagoon, Alaska, appear to be the best indicators. However, these two indexes show different trends for the overall brant population. The Lincoln–Petersen estimates showed biologically implausible changes in size among sequential years, whereas the fall Izembek index did not. Annual estimates of survival and productivity fit the patterns of annual variation in the fall Izembek index better than the Lincoln–Petersen estimates. I conclude that the fall age–partitioned Izembek Lagoon index appears to be the best for tracking population processes in brant.

Journal of Fish and Wildlife Management↗
USGS1991

Birds of the Kilbuck and Ahklun mountain region, Alaska

Between 1952 and 1988, we studied the abundance, distribution, occurrence, and habitats used by birds in the northwest portion of Bristol Bay and the adjacent Kilbuck and Ahklun mountains. In the 809 days we were present, we conducted 53 studies or surveys of birds in the region. We gathered information on 185 species, of which 65% (121) nested, 10% (19) probably nested, and 11% (21) were permanent residents in the region. Most breeding or probably breeding forms were of North American (58%; 81) or Beringian (24%; 33) affinity, while the remainder of the species were of Panboreal (17%; 24) and Old World (1%; 2) affinity. Similarly, most of the 44 migrants and visitants were of North American (41%; 18) affinity, while the remainder were of Beringian (32%; 14) and Panboreal (27%; 12) affinity. Of the 140 species that nested or probably nested, 53% (73) were abundant to fairly common, 29% (40) were uncommon to very rare, and 20% (27) were localized. Shrub thicket, dwarf shrub mat, coniferous forest, deciduous forest, mixed deciduous-coniferous forest, and fluviatile water and shoreline habitats supported the greatest diversity of species breeding and suspected of breeding. The highest concentrations of birds occurred in the estuaries of Nanvak, Chagvan, and Goodnews bays during spring and fall migrations and on the coastal and island cliffs during the breeding season. The information presented here provides the basis for range extensions of several species. Our records further clarify the known or probable Alaska breeding ranges of 11 species (fork-tailed storm-petrel, Oceanodroma furcata ; double-crested cormorant, Phalacrocorax auritus ; red-faced cormorant, Phatacrocorax utile , brant, Branta bernicla ; king eider, Somateria spectabilis ; white-tailed ptarmigan, Lagopus leucurus ; black-bellied plover, Pluvialis squatarola ; Pacific golden-plover, Pluvialis fulva ; lesser yellowlegs, Tringa flavipes ; Say's phoebe, Sayomis saya ; and Bohemian waxwing, Bombycilla garrulus ). We also provide further information on distributions or documentation of unusual occurrences for nine taxa (frigatebird, Fregata spp.; Baikal teal, Anas formosa ; American kestrel, Falco sparverius ; Terek sandpiper, Xenus cinereus ; bristle-thighed curlew, Numenius tahitiensis ; slaty-backed gull, Larus schistisagus ; rufous hummingbird, Selasphorus rufus ; song sparrow, Melospiza melodia ; and red-winged blackbird, Agelaius phoeniceus ). We provide quantitative data on the coastal migration of 11 species along Bristol Bay (red-throated loon, Gavia stellata ; Pacific loon, Gavia pacifica ; pelagic cormorant, Phalacrocorax pelagicus ; emperor goose, Chen canagica ; brant; Steller's eider, Polysticta stellen ; common eider, Somateria mollissima ; king eider; black scoter, Melanina nigra ; white-winged scoter, Melanina fusca ; and surf scoter, Melanina perspicillatd ). We document changes in nesting densities, differences in numbers, or habitat variations of 32 species in response to human activities (e.g., semipalmated plover, Charadrius semipalmatus ; arctic tern, Sterna paradisaea ; tree swallow, Tachycineta bicolor , varied thrush, Ixoreus naevius ; yellow-rumped warbler, Dendroica coronata ; and American tree sparrow, Spizella arborea ). We report the changes in a major colony of Aleutian terns ( Sterna aleatico ) at irregular intervals over 50 years.

Alaska↗
USGS2025

Avak Creek oil occurrence, North Slope, Alaska: Newly discovered oil seep on Native lands, near village of Utqiagvik

An unknown occurrence of oil was detected near Avak Creek on Native lands on the North Slope of Alaska. Determining the source of oil was imperative for allowing stakeholders (Federal, State, and local government agencies and the landowner, an Alaska Native corporation) to make timely and informed decisions and mount a mitigation response, if required. The regional and local geological framework of the Avak Creek site was constructed using seismic surveys, well data, and basin modeling results, to identify local petroleum systems, map structural geometry and faults, define source rock thermal maturity distributions, and infer likely oil-migration pathways. Molecular hydrocarbon fingerprints (biomarkers, diamondoids, compound-specific isotopes) of the oil were compared to those of local and regional oil seeps, exploration well tests, and produced oils. Biomarker acid distributions characterized the history and extent of petroleum biodegradation. Integrating subsurface and geochemical parameters, the oil is interpreted to be a natural seep generated locally, predominantly from the Brookian Lower Cretaceous Hue Shale/gamma-ray zone, rather than an anthropogenic source of pollution. Results highlight sophisticated analytical technologies used to characterize complex, compositionally altered hydrocarbons. Results also advance our understanding of Brookian source rock distribution, subsurface petroleum migration pathways, and Arctic Alaska petroleum systems.

Alaska↗
USGS2014

Sources of global climate data and visualization portals

Climate is integral to the geophysical foundation upon which ecosystems are structured. Knowledge about mechanistic linkages between the geophysical and biological environments is essential for understanding how global warming may reshape contemporary ecosystems and ecosystem services. Numerous global data sources spanning several decades are available that document key geophysical metrics such as temperature and precipitation, and metrics of primary biological production such as vegetation phenology and ocean phytoplankton. This paper provides an internet directory to portals for visualizing or servers for downloading many of the more commonly used global datasets, as well as a description of how to write simple computer code to efficiently retrieve these data. The data are broadly useful for quantifying relationships between climate, habitat availability, and lower-trophic-level habitat quality - especially in Arctic regions where strong seasonality is accompanied by intrinsically high year-to-year variability. If defensible linkages between the geophysical (climate) and the biological environment can be established, general circulation model (GCM) projections of future climate conditions can be used to infer future biological responses. Robustness of this approach is, however, complicated by the number of direct, indirect, or interacting linkages involved. For example, response of a predator species to climate change will be influenced by the responses of its prey and competitors, and so forth throughout a trophic web. The complexities of ecological systems warrant sensible and parsimonious approaches for assessing and establishing the role of natural climate variability in order to substantiate inferences about the potential effects of global warming.

Conference Paper↗
USGS2017

Deglacial sea level history of the East Siberian Sea and Chukchi Sea margins

Deglacial (12.8–10.7 ka) sea level history on the East Siberian continental shelf and upper continental slope was reconstructed using new geophysical records and sediment cores taken during Leg 2 of the 2014 SWERUS-C3 expedition. The focus of this study is two cores from Herald Canyon, piston core SWERUS-L2-4-PC1 (4-PC1) and multicore SWERUS-L2-4-MC1 (4-MC1), and a gravity core from an East Siberian Sea transect, SWERUS-L2-20-GC1 (20-GC1). Cores 4-PC1 and 20-GC were taken at 120 and 115 m of modern water depth, respectively, only a few meters above the global last glacial maximum (LGM; ∼ 24 kiloannum or ka) minimum sea level of ∼ 125–130 meters below sea level (m b.s.l.). Using calibrated radiocarbon ages mainly on molluscs for chronology and the ecology of benthic foraminifera and ostracode species to estimate paleodepths, the data reveal a dominance of river-proximal species during the early part of the Younger Dryas event (YD, Greenland Stadial GS-1) followed by a rise in river-intermediate species in the late Younger Dryas or the early Holocene (Preboreal) period. A rapid relative sea level rise beginning at roughly 11.4 to 10.8 ka ( ∼ 400 cm of core depth) is indicated by a sharp faunal change and unconformity or condensed zone of sedimentation. Regional sea level at this time was about 108 m b.s.l. at the 4-PC1 site and 102 m b.s.l. at 20-GC1. Regional sea level near the end of the YD was up to 42–47 m lower than predicted by geophysical models corrected for glacio-isostatic adjustment. This discrepancy could be explained by delayed isostatic adjustment caused by a greater volume and/or geographical extent of glacial-age land ice and/or ice shelves in the western Arctic Ocean and adjacent Siberian land areas.

Chukchi Sea, East Siberian Sea↗
USGS2023

Assessing environmental change associated with early Eocene hyperthermals in the Atlantic Coastal Plain, USA

Eocene transient global warming events (hyperthermals) can provide insight into a future warmer world. While much research has focused on the Paleocene–Eocene Thermal Maximum (PETM), hyperthermals of a smaller magnitude can be used to characterize climatic responses over different magnitudes of forcing. This study identifies two events, namely the Eocene Thermal Maximum 2 (ETM2 and H2), in shallow marine sediments of the Eocene-aged Salisbury Embayment of Maryland, based on magnetostratigraphy, calcareous nannofossil, and dinocyst biostratigraphy, as well as the recognition of negative stable carbon isotope excursions (CIEs) in biogenic calcite. We assess local environmental change in the Salisbury Embayment, utilizing clay mineralogy, marine palynology, δ 18 O of biogenic calcite, and biomarker paleothermometry (TEX 86 ). Paleotemperature proxies show broad agreement between surface water and bottom water temperature changes. However, the timing of the warming does not correspond to the CIE of the ETM2 as expected from other records, and the highest values are observed during H2, suggesting factors in addition to p CO 2 forcing have influenced temperature changes in the region. The ETM2 interval exhibits a shift in clay mineralogy from smectite-dominated facies to illite-rich facies, suggesting hydroclimatic changes but with a rather dampened weathering response relative to that of the PETM in the same region. Organic walled dinoflagellate cyst assemblages show large fluctuations throughout the studied section, none of which seem systematically related to CIE warming. These observations are contrary to the typical tight correspondence between climate change and assemblages across the PETM, regionally and globally, and ETM2 in the Arctic Ocean. The data do indicate very warm and (seasonally) stratified conditions, likely salinity-driven, across H2. The absence of evidence for strong perturbations in local hydrology and nutrient supply during ETM2 and H2, compared to the PETM, is consistent with the less extreme forcing and the warmer pre-event baseline, as well as the non-linear response in hydroclimates to greenhouse forcing.

Atlantic Coastal Plain↗
USGS2021

FLUXNET-CH4: A global, multi-ecosystem database and analysis of methane seasonality from freshwater wetlands

Methane (CH 4 ) emissions from natural landscapes constitute roughly half of global CH 4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH 4 flux are ideal for constraining ecosystem-scale CH 4 emissions due to quasi-continuous and high-temporal-resolution CH 4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH 4 Version 1.0, the first open-source global dataset of CH 4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/ , last access: 7 April 2021). FLUXNET-CH 4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH 4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH 4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH 4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH 4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH 4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH 4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20 ∘ S to 20 ∘ N) the spring onset of elevated CH 4 emissions starts 3 d earlier, and the CH 4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH 4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH 4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH 4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH 4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH 4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH 4 peak). FLUXNET-CH 4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH 4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH 4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Earth System Science Data↗
USGS2025

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗
USGS2022

The effect of changing sea ice on wave climate trends along Alaska's central Beaufort Sea coast

Diminishing sea ice is impacting the wave field across the Arctic region. Recent observation- and model-based studies highlight the spatiotemporal influence of sea ice on offshore wave climatologies, but effects within the nearshore region are still poorly described. This study characterizes the wave climate in the central Beaufort Sea coast from 1979 to 2019 by utilizing a wave hindcast model that uses ERA5 winds, waves, and ice concentrations as input. The spectral wave model SWAN (Simulating Waves Nearshore) is calibrated and validated based on more than 10 000 in situ time point measurements collected over a 13-year time period across the region, with friction variations and empirical coefficients for newly implemented empirical ice formulations for the open-water and shoulder seasons. Model results and trends are analyzed over the 41-year time period using the non-parametric Mann–Kendall test, including an estimate of Sen's slope. The model results show that the reduction in sea ice concentration correlates strongly with increases in average and extreme wave conditions. In particular, the open-water season extended by ∼96 d over the 41-year time period (∼2.4 d yr−1), resulting in a 5-fold increase in the yearly cumulative wave power. Moreover, the open-water season extends later into the year, resulting in relatively more open-water conditions during fall storms with high wind speeds. The later freeze-up results in an increase in the annual offshore median wave heights of 1 % yr−1 and an increase in the average number of rough wave days (defined as days when maximum wave heights exceed 2.5 m) from 1.5 in 1979 to 13.1 d in 2019. Trends in the nearshore areas deviate from the patterns offshore. Model results indicate a saturation limit for high wave heights in the shallow areas of Foggy Island Bay. Similar patterns are found for yearly cumulative wave power.

Alaska↗
USGS2025

Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning

Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. Existing snow cover products do not reliably distinguish seasonal snow from glacier ice and firn, preventing their use for glacier snow cover detection. Despite previous efforts to classify glacier surface facies using machine learning on local scales, currently there is no published comparison of machine learning models for classifying glacier snow cover across different satellite image products. We present an automated snow detection workflow for mountain glaciers using supervised machine-learning-based image classifiers and Landsat 8 and 9, Sentinel-2, and PlanetScope satellite imagery. We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. Geological Survey Benchmark Glacier Project glaciers. The workflow produces daily to twice monthly time series of several glacier mass balance and snowmelt indicators (snow-covered area, accumulation area ratio, and seasonal snow line) from 2013 to present. Workflow performance is assessed by comparing automatically classified images and snow lines to manual interpretations at each glacier site. The image classifiers exhibit overall accuracies of 92%–98%, K scores of 84%–96%, and F scores of 93%–98% for all image products. The median difference between automatically and manually delineated median snow line altitudes is 31m (IQR of 73to0m)across all image products. The Sentinel-2 classifier (support vector machine) produces the most accurate glacier mass balance and snowmelt indicators and distinguishes snow from ice and f irn the most reliably. Although they are less accurate, the Landsat- and PlanetScope-derived estimates greatly enhance the temporal coverage of observations. The transient accumulation area ratio produces the least noisy time series, making it the most reliable indicator for characterizing seasonal snow trends. The temporally detailed accumulation area ratio time series reveal that the timing of minimum snow cover conditions varies by up to a month between Arctic (63°N) and midlatitude (48°N) sites, underscoring the potential for bias when estimating glacier minimum snow cover conditions from a single late-summer image. Widespread application of our automated snow detection workflow has the potential to improve regional assessments of glacier mass balance, land ice representations within Earth system models, water resources, and the impacts of climate change on snow cover across broad spatial scales.

The Cryosphere↗
USGS2011

The ANTOSTRAT legacy: Science collaboration and international transparency in potential marine mineral resource exploitation of Antarctica

The Antarctic Offshore Stratigraphy project (ANTOSTRAT; 1989–2002) was an extremely successful collaboration in international marine geological science that also lifted the perceived “veil of secrecy” from studies of potential exploitation of Antarctic marine mineral resources. The project laid the groundwork for circum-Antarctic seismic, drilling, and rock coring programs designed to decipher Antarctica’s tectonic, stratigraphic, and climate histories. In 2002, ANTOSTRAT evolved into the equally successful and currently active Antarctic Climate Evolution research program. The need for, and evolution of, ANTOSTRAT was based on two simple tenets within SCAR and the Antarctic Treaty: international science collaboration and open access to data. The ANTOSTRAT project may be a helpful analog for other regions of strong international science and geopolitical interests, such as the Arctic. This is the ANTOSTRAT story.

Book chapter↗
USGS2022

Pre-breeding foraging ecology of three tern species nesting in the Gulf of Maine

A variety of seabird species migrate annually from wintering grounds in the Southern Hemisphere to the Gulf of Maine, USA to breed and raise their young. Post-migration, adult seabirds depend on the spatio-temporal match of reliable food resources to replenish energy reserves before breeding. However, the conditions during this critical window of time are becoming increasingly uncertain given the magnitude and pace at which climate change is impacting the Gulf of Maine region. We investigated the pre-breeding foraging ecology of Arctic Terns ( Sterna paradisaea ), Common Terns ( S. hirundo ), and the federally endangered Roseate Tern ( S. dougallii ) by analyzing stable carbon (δ 13 C) and nitrogen (δ 15 N) isotopes in eggshell tissues collected from seven islands in the Gulf of Maine from 2016 to 2018. Results show at the interspecific level, adult foraging patterns are consistent with expectations based on chick diets. At interisland and interannual scales, variation in isotopic values and niche breadths suggest foraging habits are highly localized. Although uncertainty remains, interannual trends also suggest warmer ocean conditions are either affecting tern foraging behaviors and/or prey resource availability during the late spring and early summer. Overall, results provide new information on adult tern foraging ecology in an important breeding area experiencing rapid environmental change.

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