Rapid changes in sea ice extent and changes in freshwater inputs from land are rapidly changing the nature of Arctic estuarine ecosystems. In the Beaufort Sea, these nearshore habitats are known for their high productivity and mix of marine resident and diadromous fishes that have great subsistence value for Indigenous communities. There is, however, a lack of information on the spatial variation among Arctic nearshore fish communities as related to environmental drivers. In summers of 2017–2019, we sampled fishes in four estuarine ecosystems to assess community composition and relate fish abundance to temperature, salinity, and wind conditions. We found fish communities were heterogeneous over larger spatial extents with rivers forming fresh estuarine plumes that supported diadromous species (e.g., broad whitefish Coregonus nasus), while lagoons with reduced freshwater input and higher salinities were associated with marine species (e.g., saffron cod Eleginus gracilis). West–East directional winds accounted for up to 66% of the community variation, indicating importance of the wind-driven balance between fresh and marine water masses. Salinity and temperature accounted for up to 54% and 37% of the variation among lagoon communities, respectively. Recent sea ice declines provide more opportunity for wind to influence oceanographic conditions and biological communities. Current subsistence practices, future commercial fishing opportunities, and on-going oil and gas activities benefit from a better understanding of current fish community distributions. This work provides important data on fish spatial distributions and community composition, providing a basis for fish community response to changing climatic conditions and anthropogenic use.
The great 1957 Aleutian Islands earthquake ruptured ∼1200 km of the plate boundary along the Aleutian subduction zone and produced a destructive tsunami across Hawaiʻi. Early seismic and tsunami analyses indicated that large megathrust fault slip was concentrated in the western Aleutian Islands, but tsunami waves generated by slip in the west cannot explain the large observed runup in Hawaiʻi far to the southeast. Recently mapped 1957 geologic deposits on eastern Aleutian Islands suggest occurrence of very large nearby slip. Jointly modeling tsunami runup along the eastern Aleutian and Hawaiian Islands together with tide gauge recordings across the Pacific resolves 12-26 m shallow slip along 600 km of the eastern Aleutian Islands in addition to modest, deeper western slip inferred from seismic records. The eastern near-trench slip results in an MW 8.3-8.6 tsunami earthquake component of the MW 8.6-8.8 rupture, comparable in size to the adjacent 1946 Aleutian tsunami earthquake to the east. The reexamination of the 1957 rupture confirms the tsunami hazards posed by the eastern Aleutian subduction zone to Hawaiʻi and lays the groundwork for investigation of large prehistoric earthquakes through modeling tsunami runup inferred from stratigraphic observations to constrain their rupture processes.
Ediacara-type macrofossils appear as early as ~575 Ma in deep-water facies of the Drook Formation of the Avalon Peninsula, Newfoundland, and the Nadaleen Formation of Yukon and Northwest Territories, Canada. Our ability to assess whether a deep-water origination of the Ediacara biota is a genuine reflection of evolutionary succession, an artifact of an incomplete stratigraphic record, or a bathymetrically controlled biotope is limited by a lack of geochronological constraints and detailed shelf-to-slope transects of Ediacaran continental margins. The Ediacaran Rackla Group of the Wernecke Mountains, NW Canada, represents an ideal shelf-to-slope depositional system to understand the spatiotemporal and environmental context of Ediacara-type organisms' stratigraphic occurrence. New sedimentological and paleontological data presented herein from the Wernecke Mountains establish a stratigraphic framework relating shelfal strata in the Goz/Corn Creek area to lower slope deposits in the Nadaleen River area. We report new discoveries of numerous Aspidella hold-fast discs, indicative of frondose Ediacara organisms, from deep-water slope deposits of the Nadaleen Formation stratigraphically below the Shuram carbon isotope excursion (CIE) in the Nadaleen River area. Such fossils are notably absent in coeval shallow-water strata in the Goz/Corn Creek region despite appropriate facies for potential preservation. The presence of pre-Shuram CIE Ediacara-type fossils occurring only in deep-water facies within a basin that has equivalent well-preserved shallow-water facies provides the first stratigraphic paleobiological support for a deep-water origination of the Ediacara biota. In contrast, new occurrences of Ediacara-type fossils (including juvenile fronds, Beltanelliformis, Aspidella, annulated tubes, and multiple ichnotaxa) are found above the Shuram CIE in both deep- and shallow-water deposits of the Blueflower Formation. Given existing age constraints on the Shuram CIE, it appears that Ediacaran organisms may have originated in the deeper ocean and lived there for up to ~15 million years before migrating into shelfal environments in the terminal Ediacaran. This indicates unique ecophysiological constraints likely shaped the initial habitat preference and later environmental expansion of the Ediacara biota.
No abstract available.
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II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":902510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":902511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":902512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":902513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Macqueen, Patricia Grace 0000-0001-7692-3416","orcid":"https://orcid.org/0000-0001-7692-3416","contributorId":337137,"corporation":false,"usgs":true,"family":"Macqueen","given":"Patricia","email":"","middleInitial":"Grace","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":902514,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":902515,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Solano, Federico 0000-0002-0308-5850","orcid":"https://orcid.org/0000-0002-0308-5850","contributorId":213145,"corporation":false,"usgs":true,"family":"Solano","given":"Federico","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":902516,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Case, George N.D. 0000-0001-9826-5661 gcase@usgs.gov","orcid":"https://orcid.org/0000-0001-9826-5661","contributorId":224941,"corporation":false,"usgs":true,"family":"Case","given":"George","email":"gcase@usgs.gov","middleInitial":"N.D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":902517,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pineault, David George 0000-0003-3613-2497","orcid":"https://orcid.org/0000-0003-3613-2497","contributorId":337568,"corporation":false,"usgs":true,"family":"Pineault","given":"David","email":"","middleInitial":"George","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":902518,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70254455,"text":"70254455 - 2024 - Drought, fire, and archeology in the Jemez Mountains, New Mexico","interactions":[],"lastModifiedDate":"2024-05-28T11:57:17.911019","indexId":"70254455","displayToPublicDate":"2024-05-01T06:52:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17785,"text":"Intermountain Park Science","active":true,"publicationSubtype":{"id":10}},"title":"Drought, fire, and archeology in the Jemez Mountains, New Mexico","docAbstract":"In the Jemez Mountains of New Mexico, cultural resources and traditional cultural landscapes are vulnerable to compounded impacts of changing climate and wildfires. Here, we discuss impacts to archeological resources observed in recent, high-severity fires, including at Bandelier National Monument and Valles Caldera National Preserve, and describe an interdisciplinary effort to quantity archeological fire effects.","language":"English","publisher":"National Park Service","usgsCitation":"Steffen, A., Civitello, J., Loehman, R.A., and Parmenter, R., 2024, Drought, fire, and archeology in the Jemez Mountains, New Mexico: Intermountain Park Science, v. 2, no. 1, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-149005","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":429320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.61072300933778,\n 36.66992633929999\n ],\n [\n -107.61072300933778,\n 35.363708672581055\n ],\n [\n -105.69910191558768,\n 35.363708672581055\n ],\n [\n -105.69910191558768,\n 36.66992633929999\n ],\n [\n -107.61072300933778,\n 36.66992633929999\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Steffen, Anastasia","contributorId":174053,"corporation":false,"usgs":false,"family":"Steffen","given":"Anastasia","email":"","affiliations":[],"preferred":false,"id":901435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Civitello, Jamie","contributorId":336931,"corporation":false,"usgs":false,"family":"Civitello","given":"Jamie","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":901436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":901437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parmenter, Robert","contributorId":243994,"corporation":false,"usgs":false,"family":"Parmenter","given":"Robert","affiliations":[{"id":48788,"text":"Valles Caldera National Preserve, U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":901438,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254152,"text":"70254152 - 2024 - Snow avalanches are a primary climate-linked driver of mountain ungulate populations","interactions":[],"lastModifiedDate":"2024-05-10T12:04:31.268887","indexId":"70254152","displayToPublicDate":"2024-04-29T07:01:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17775,"text":"Nature Communications Biology","active":true,"publicationSubtype":{"id":10}},"title":"Snow avalanches are a primary climate-linked driver of mountain ungulate populations","docAbstract":"Snow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in rapidly changing mountain ecosystems is particularly critical. Whereas effects of snow on food availability, energy expenditure, and predation are well documented, we report how avalanches exert major impacts on an ecologically significant mountain ungulate - the coastal Alaskan mountain goat (Oreamnos americanus). Using long-term GPS data and field observations across four populations (421 individuals over 17 years), we show that avalanches caused 23−65% of all mortality, depending on area. Deaths varied seasonally and were directly linked to spatial movement patterns and avalanche terrain use. Population-level avalanche mortality, 61% of which comprised reproductively important prime-aged individuals, averaged 8% annually and exceeded 22% when avalanche conditions were severe. Our findings reveal a widespread but previously undescribed pathway by which snow can elicit major population-level impacts and shape demographic characteristics of slow-growing populations of mountain-adapted animals.
An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.
We integrate the existing detrital zircon data from multiple modern river sediment samples on Viti Levu, Fiji, with the most current available geological and topographic mapping of the respective river drainage basins to compare detrital populations with potential bedrock sources. The temporal and spatial variations in zircon geochemistry supplement what is known from igneous rocks and confirm the petrological differences between plutonic and volcanic rocks from the Eocene to early Oligocene (Yavuna age, >30 Ma), middle Oligocene to middle Miocene (Wainimala age, 30–12.5 Ma), late Miocene (Colo age, 12.5–6.5 Ma) and latest Miocene (Namosi age, 6.5–5 Ma). The >30 Ma Yavuna-age zircons are restricted to areas that drain the previously mapped Yavuna Group. The 30–12.5 Ma zircons are found across central Viti Levu from west to east, and the 30–15 Ma zircons have distinctively low U/Yb and high Dy/Yb ratios. They are the best radiometric evidence of widespread early to middle Miocene arc magmatism in Fiji that was relatively U-poor. Peak deconvolution of the Colo age zircons from individual basins suggests the following ages for undated or poorly dated plutons from central Viti Levu. The large Mavuvu pluton is probably composed of multiple intrusions in the 12–10 Ma range, the Waiqa pluton is probably ca 10 Ma, and the Noikoro pluton is probably ca 9 Ma. There are zircons from unknown plutonic or volcanic sources between 8 and 7 Ma in western Viti Levu that have distinct Eu/Eu* ratios. We attribute the highest U/Yb ratios in some Colo age zircons to crustal anatexis. Namosi-age zircons are abundant in the Medrausucu Group and can be found scattered across Viti Levu.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08120099.2024.2332916","usgsCitation":"Stork, A., Gill, J.B., Todd, E., and Drewes-Todd, E.K., 2024, Detrital zircons and the magmatic history of Viti Levu, Fiji: Australian Journal of Earth Sciences, v. 71, no. 4, p. 600-614, https://doi.org/10.1080/08120099.2024.2332916.","productDescription":"15 p.","startPage":"600","endPage":"614","ipdsId":"IP-158927","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":462590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Fiji","otherGeospatial":"Viti Levu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 177.43906669533374,\n -17.500913430772442\n ],\n [\n 177.19873064880753,\n -17.88906860947432\n ],\n [\n 177.260818220212,\n -18.13326652784113\n ],\n [\n 178.16732836567263,\n -18.29999120264695\n ],\n [\n 178.69067436768728,\n -18.16406457548949\n ],\n [\n 178.60696342416523,\n -17.611114359471088\n ],\n [\n 178.46384444475365,\n -17.49057290416684\n ],\n [\n 178.2912423489197,\n -17.285531380045587\n ],\n [\n 177.91342986027942,\n -17.297020685568988\n ],\n [\n 177.43906669533374,\n -17.500913430772442\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"71","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Stork, Allen","contributorId":292914,"corporation":false,"usgs":false,"family":"Stork","given":"Allen","email":"","affiliations":[{"id":63071,"text":"Department of Geology, Western Colorado University, Gunnison CO, USA","active":true,"usgs":false}],"preferred":false,"id":915046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, James B 0000-0003-2584-9687","orcid":"https://orcid.org/0000-0003-2584-9687","contributorId":248602,"corporation":false,"usgs":false,"family":"Gill","given":"James","email":"","middleInitial":"B","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":915047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, Erin 0000-0002-4871-9730 etodd@usgs.gov","orcid":"https://orcid.org/0000-0002-4871-9730","contributorId":202811,"corporation":false,"usgs":true,"family":"Todd","given":"Erin","email":"etodd@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":915048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drewes-Todd, Elizabeth Kathleen 0000-0003-0692-3714","orcid":"https://orcid.org/0000-0003-0692-3714","contributorId":243351,"corporation":false,"usgs":true,"family":"Drewes-Todd","given":"Elizabeth","email":"","middleInitial":"Kathleen","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":915049,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252942,"text":"70252942 - 2024 - Where east meets west: Phylogeography of the high Arctic North American brant goose","interactions":[],"lastModifiedDate":"2024-04-12T12:02:10.336507","indexId":"70252942","displayToPublicDate":"2024-04-10T06:57:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Where east meets west: Phylogeography of the high Arctic North American brant goose","docAbstract":"Genetic variation in Arctic species is often influenced by vicariance during the Pleistocene, as ice sheets fragmented the landscape and displaced populations to low- and high-latitude refugia. The formation of secondary contact or suture zones during periods of ice sheet retraction has important consequences on genetic diversity by facilitating genetic connectivity between formerly isolated populations. Brant geese (Branta bernicla) are a maritime migratory waterfowl (Anseriformes) species that almost exclusively uses coastal habitats. Within North America, brant geese are characterized by two phenotypically distinct subspecies that utilize disjunct breeding and wintering areas in the northern Pacific and Atlantic. In the Western High Arctic of Canada, brant geese consist of individuals with an intermediate phenotype that are rarely observed nesting outside this region. We examined the genetic structure of brant geese populations from each subspecies and areas consisting of intermediate phenotypes using mitochondrial DNA (mtDNA) control region sequence data and microsatellite loci. We found a strong east–west partition in both marker types consistent with refugial populations. Within subspecies, structure was also observed at mtDNA while microsatellite data suggested the presence of only two distinct genetic clusters. The Western High Arctic (WHA) appears to be a secondary contact zone for both Atlantic and Pacific lineages as mtDNA and nuclear genotypes were assigned to both subspecies, and admixed individuals were observed in this region. The mtDNA sequence data outside WHA suggests no or very restricted intermixing between Atlantic and Pacific wintering populations which is consistent with published banding and telemetry data. Our study indicates that, although brant geese in the WHA are not a genetically distinct lineage, this region may act as a reservoir of genetic diversity and may be an area of high conservation value given the potential of low reproductive output in this species.
In 2021, the Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, increased seismicity, and other significant activity at 15 volcanic centers in Alaska and the Commonwealth of the Northern Mariana Islands. Eruptive activity in Alaska consisted of repeated small, ash-producing, phreatomagmatic explosions from Mount Young on Semisopochnoi Island; an explosion at Great Sitkin Volcano followed by the eruption of a thick lava flow that filled and overflowed the summit crater; weak explosive activity and the eruption of small, channelized flows at Pavlof Volcano; and a short-lived eruption at Mount Veniaminof that produced ash emissions from an intracaldera cone, as well as lava flows confined to a melt pit in the ice mantling the cone’s flank. Mount Cleveland had a period of unrest, but no eruptive activity took place there. Anomalous seismicity was also detected at Atka volcanic complex, Mount Gareloi, and Davidof volcano. New warm springs opened and deposited mud at the summit and north base of Shrub mud volcano. Other activity of note in Alaska consisted of large ice and rock avalanches at Iliamna Volcano and Mount Spurr, ash resuspension events at Mount Katmai and Aniakchak Crater, and anomalous deformation at Mount Okmok that was consistent with a shallow intrusion of magma. In the Commonwealth of the Northern Marianas Islands, a brief, ash-producing eruption occurred at Mount Pagan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245014","collaboration":"The Alaska Volcano Observatory is a consortium between the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Orr, T.R., Dietterich, H.R., Fee D., Girona, T., Grapenthin, R., Haney, M.M., Loewen, M.W., Lyons, J.J., Power, J.A., Schwaiger, H.F., Schneider, D.J., Tan, D., Toney, L., Wasser, V.K., Waythomas, C.F., 2024, 2021 Volcanic activity in Alaska and the Commonwealth of the Northern Mariana Islands—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2024–5014, 64 p., https://doi.org/10.3133/sir20245014.","productDescription":"ix, 64 p.","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-139235","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":427361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5014/sir20245014.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5014"},{"id":427360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5014/covrthb.jpg"}],"country":"Northern Mariana Islands, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -180.91039541038674,\n 52.397333461784\n ],\n [\n -179.15258291038657,\n 50.647658713281515\n ],\n [\n -154.36742666038634,\n 54.59269911796724\n ],\n [\n -144.8752391603861,\n 61.7067556778085\n ],\n [\n -148.56664541038634,\n 63.09098661447797\n ],\n [\n -154.01586416038626,\n 61.95569747993264\n ],\n [\n -158.93773916038643,\n 59.28407472678845\n ],\n [\n -165.7932079103864,\n 55.399337204164055\n ],\n [\n -173.17602041038666,\n 53.76976304468752\n ],\n [\n -178.62523916038657,\n 52.71793714020785\n ],\n [\n -180.91039541038674,\n 52.397333461784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 146,\n 20\n ],\n [\n 146,\n 14\n ],\n [\n 144,\n 14\n ],\n [\n 144,\n 20\n ],\n [\n 146,\n 20\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
The Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, increased seismicity, and other significant activity at nine volcanic centers in Alaska in 2020. The most notable volcanic activity in 2020 was an eruption of Shishaldin Volcano, which produced lava flows, lahars, and ash. Mount Cleveland had one small ash-producing eruption in June but was quiet thereafter. Other activity documented in 2020 consisted of elevated seismicity at the volcanoes Mount Veniaminof, Pavlof Volcano, Makushin Volcano, Atka volcanic complex (Korovin Volcano), Great Sitkin Volcano, and Semisopochnoi Island. Finally, the resuspension of ash deposited during the 1912 Novarupta-Katmai eruption was documented on three occasions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245004","collaboration":"The Alaska Volcano Observatory is a consortium between the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Orr, T., Cameron, C., Dietterich, H., Loewen, M., Lopez, T., Lyons, J., Nakai, J., Power, J., Searcy, C., Tepp, G., and Waythomas, C., 2024, 2020 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory (ver. 1.1, September 2024): U.S. Geological Survey Scientific Investigations Report 2024–5004, 34 p., https://doi.org/10.3133/sir20245004.","productDescription":"vii, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-139376","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":428469,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5004/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":427363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5004/sir20245004.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":427362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5004/covrthb2.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -180.91039541038674,\n 52.397333461784\n ],\n [\n -179.15258291038657,\n 50.647658713281515\n ],\n [\n -154.36742666038634,\n 54.59269911796724\n ],\n [\n -144.8752391603861,\n 61.7067556778085\n ],\n [\n -148.56664541038634,\n 63.09098661447797\n ],\n [\n -154.01586416038626,\n 61.95569747993264\n ],\n [\n -158.93773916038643,\n 59.28407472678845\n ],\n [\n -165.7932079103864,\n 55.399337204164055\n ],\n [\n -173.17602041038666,\n 53.76976304468752\n ],\n [\n -178.62523916038657,\n 52.71793714020785\n ],\n [\n -180.91039541038674,\n 52.397333461784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: April 9, 2024; Version 1.1: September 9, 2024","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate-based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling-Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non-optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions.
We developed an open source, extensible Python-based framework, that we call the Versatile Modeling of Deformation (VMOD), for forward and inverse modeling of crustal deformation sources. VMOD abstracts from specific source model implementations, data types and inversion methods. We implement the most common geodetic source models which can be combined to model and analyze multi-source deformation. VMOD supports Global Navigation Satellite System (GNSS), InSAR, electronic distance measurement, Leveling and tilt data. To infer source characteristics from observations, VMOD implements non-linear least squares and Markov Chain Monte-Carlo Bayesian inversions, including joint inversions using different sources of data. VMOD's structure allows for easy integration of new geodetic models, data types, and inversion strategies. We benchmark the forward models against other published results and the inversion approaches against other implementations. We apply VMOD to analyze deformation at Unimak Island, Alaska, observed with continuous and campaign GNSS, and ascending and descending InSAR time series generated from Sentinel-1 satellite radar acquisitions. These data show an inflation pattern at Westdahl volcano and subsidence at Fisher Caldera. We use VMOD to test a range of source models by jointly inverting the GNSS and InSAR data sets. Our final model simultaneously constrains the parameters of two sources. Our results reveal a depressurizing spheroid under Fisher Caldera ∼4–6 km deep, contracting at a rate of ∼2–3 Mm3/yr, and a pressurizing spherical source underneath Westdahl volcano ∼6–8 km deep, inflating at ∼5 Mm3/yr. This and past applications of VMOD to volcanic unrest benefit from an extensible framework which supports jointly inversions of data sets for parameters of easily composable multi-source models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC011341","usgsCitation":"Angarita, M., Grapenthin, R., Henderson, S., Christoffersen, M.S., and Anderson, K.R., 2024, Versatile modeling of deformation (VMOD) inversion framework: Application to 20 years of observations at Westdahl Volcano and Fisher Caldera, Alaska, US: Geochemistry, Geophysics, Geosystems, v. 25, e2023GC011341, 19 p., https://doi.org/10.1029/2023GC011341.","productDescription":"e2023GC011341, 19 p.","ipdsId":"IP-159327","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":439914,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc011341","text":"Publisher Index Page"},{"id":427557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Unimak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166.24763757080336,\n 55.437699893466515\n ],\n [\n -166.24763757080336,\n 53.85001704010827\n ],\n [\n -162.27182660949765,\n 53.85001704010827\n ],\n [\n -162.27182660949765,\n 55.437699893466515\n ],\n [\n -166.24763757080336,\n 55.437699893466515\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2024-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Angarita, Mario","contributorId":215655,"corporation":false,"usgs":false,"family":"Angarita","given":"Mario","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":898366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grapenthin, Ronni","contributorId":257035,"corporation":false,"usgs":false,"family":"Grapenthin","given":"Ronni","email":"","affiliations":[{"id":7026,"text":"New Mexico Tech","active":true,"usgs":false}],"preferred":false,"id":898367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henderson, Scott","contributorId":206392,"corporation":false,"usgs":false,"family":"Henderson","given":"Scott","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":898368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christoffersen, Michael S","contributorId":237038,"corporation":false,"usgs":false,"family":"Christoffersen","given":"Michael","email":"","middleInitial":"S","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":898379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":898370,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70253270,"text":"70253270 - 2024 - Variability in coastal habitat available for Longfin Smelt Spirinchus thaleichthys in the northeastern Pacific Ocean","interactions":[],"lastModifiedDate":"2024-05-01T12:00:48.338194","indexId":"70253270","displayToPublicDate":"2024-04-05T06:59:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Variability in coastal habitat available for Longfin Smelt Spirinchus thaleichthys in the northeastern Pacific Ocean","docAbstract":"An understanding of oceanographic conditions and processes important to marine animal ecology is fundamental to the development of effective management and conservation actions. Longfin Smelt (Spirinchus thaleichthys) is a pelagic forage fish found in coastal and estuarine waters along the Pacific coast of North America from Alaska to central California. Substantial population declines in California’s San Francisco Estuary, where Longfin Smelt are protected under California’s Endangered Species Act, have prompted extensive study of estuarine factors associated with the decline. However, coastal factors that affect up to two-thirds of the Longfin Smelt life cycle are poorly understood and may be important drivers of population dynamics. We compiled coastal observations from numerous sources to estimate the range-wide coastal marine distribution of Longfin Smelt and assess habitat factors affecting distribution in the northeast Pacific Ocean. Based on maximum entropy species distribution models, Longfin Smelt distribution was correlated with depth, distance from the nearest estuary, sea surface temperature, and sea surface chlorophyll. Longfin Smelt were found in shallow, higher productivity coastal waters closer to estuaries, with depth and temperature the most consistent factors influencing distribution. Habitat suitability was highly variable at the southern extent of the range, particularly off the California coast, and was largely driven by habitat contractions associated with warm-water conditions. Study results provide insights into the habitat and range-wide distribution of an at-risk estuarine-reliant forage fish and are the first step toward identifying processes that affect the marine portion of the Longfin Smelt life cycle.
Globally, coastal communities experience flood hazards that are projected to worsen from climate change and sea level rise. The 100-year floodplain or record flood are commonly used to identify risk areas for planning purposes. Remote communities often lack measured flood elevations and require innovative approaches to estimate flood elevations. This study employs observation-based methods to estimate the record flood elevation in Alaska communities and compares results to elevation models, infrastructure locations, and sea level rise projections. In 46 analyzed communities, 22% of structures are located within the record floodplain. With sea level rise projections, this estimate increases to 30–37% of structures by 2100 if structures remain in the same location. Flood exposure is highest in western Alaska. Sea level rise projections suggest northern Alaska will see similar flood exposure levels by 2100 as currently experienced in western Alaska. This evaluation of record flood height, category, and history can be incorporated into hazard planning documents, providing more context for coastal flood exposure than previously existed for Alaska. This basic flood exposure method is transferable to other areas with similar mapping challenges. Identifying current and projected hazardous zones is essential to avoid unintentional development in floodplains and improve long-term safety.
Demand for oil and natural gas continues to increase, leading to the development of remote regions where it is riskier to operate. Many of these regions have had limited development, so understanding potential impacts to wildlife could inform management decisions. In 2017, the United States passed legislation allowing oil and gas development in the coastal plain of the Arctic National Wildlife Refuge in northeastern Alaska. This area has received limited industrial development and is an important region for polar bears that use the coastline as a travel corridor in autumn. We sought to understand how an autumn near-shore oil spill in the Refuge could affect polar bears. We simulated oil spills from shallow sub-sea pipelines at 3 locations along the coastline of the Refuge and allowed spills to discharge 4800 barrels of oil per day for 6 days, and tracked oil for 50 days. We interacted the trajectories with simulated polar bear movements to estimate how many bears might be exposed. Oil spread quickly along the coastline and during some weeks exposed an average of 10 bears (95 % CI: 0–37) to lethal levels of oil, and 60 (95 % CI: 9–120) to sub-lethal levels. Our results suggest a significant number of polar bears could become oiled from a spill in the region and require decontamination. Therefore, future mitigation strategies could include careful siting of future development and additional capacity to capture and decontaminate bears in the event of an oil spill.
The Arctic National Wildlife Refuge is a unique landscape in northern Alaska with limited water resources, substantial biodiversity of rare and threatened species, as well as oil and gas resources. The region has unique hydrology related to perennial springs, and the formation of large aufeis fields—sheets of ice that grow in the river channels where water reaches the surface in the winter and freezes. This work aims to update our understanding of water resources and water quality in the springs, streams, rivers, and lakes of this region, returning to sites sampled by the U.S. Geological Survey in the 1970s. We resampled eight streams, four springs, and six lakes for hydrological metrics, water quality, and macroinvertebrates, and recalculated flood-frequency metrics for rivers using updated data and modern techniques. Aufeis field melt rates were also assessed for the past several decades. Although the available data preclude trend determinations in most cases, our analysis and comparison to the historical sampling indicates an increase in dissolved ions for streams and springs, faster and earlier aufeis melt, and similar macroinvertebrate populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245008","usgsCitation":"Koch, J.C., Best, H., Baughman, C., Couvillion, C., Carey, M.P., and Conaway, J., 2024, A comparison of contemporary and historical hydrology and water quality in the foothills and coastal plain of the Arctic National Wildlife Refuge, Arctic Slope, northern Alaska: U.S. Geological Survey Scientific Investigations Report 2024–5008, 24 p., https://doi.org/10.3133/sir20245008.","productDescription":"Report: viii, 24 p.; 2 Data Releases; Correction Note","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-151990","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":499422,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116206.htm","linkFileType":{"id":5,"text":"html"}},{"id":498378,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2024/5008/correctionNote.txt","text":"Correction note","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":430506,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KK98VP","text":"USGS data release","description":"USGS data release","linkHelpText":"Rasters of observed aufeis deposits within rivers of the 1002 Area based on historical Landsat imagery, 1985-2022"},{"id":430429,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X34VHM","text":"USGS data release","description":"USGS data release","linkHelpText":"Macroinvertebrates from streams and springs in the 1002 region of the Arctic National Wildlife Refuge, Alaska, 2021"},{"id":427077,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.XML"},{"id":427076,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5008/images"},{"id":427075,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5008"},{"id":427074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5008"},{"id":427073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.35991062435545,\n 70.47943246978403\n ],\n [\n -147.35991062435545,\n 68.94103321326239\n ],\n [\n -141.60307468685548,\n 68.94103321326239\n ],\n [\n -141.60307468685548,\n 70.47943246978403\n ],\n [\n -147.35991062435545,\n 70.47943246978403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Northern high-latitudes are projected to get warmer and wetter, which will affect rates of permafrost thaw and mechanisms by which thaw occurs. To better understand the impact of rain, as well as other factors such as snow depth, canopy cover, and microtopography, we instrumented a degrading permafrost plateau in south-central Alaska with high-resolution soil temperature sensors. The site contains ecosystem-protected permafrost, which persists in unfavorable climates due to favorable ecologic conditions. Our study (2020–2022) captured three of the snowiest years and three of the four wettest years since the site was first studied in 2015. Average thaw rates along an across-site transect increased nine-fold from 6 ± 5 cm yr−1 (2015–2020) to 56 ± 12 cm yr−1 (2020–2022). This thaw was not uniform. Hummock locations, residing on topographic high points with relatively dense canopy, experienced only 8 ± 9 cm yr−1 of thaw, on average. Hollows, topographic low points with low canopy cover, and transition locations, which had canopy cover and elevation between hummocks and hollows, thawed 44 ± 6 cm yr−1 and 39 ± 13 cm yr−1, respectively. Mechanisms of thaw differed between these locations. Hollows had high warm-season soil moisture, which increased thermal conductivity, and deep cold-season snow coverage, which insulated soil. Transition locations thawed primarily due to thermal energy transported through subsurface taliks during individual rain events. Most increases in depth to permafrost occurred below the ∼45 cm thickness seasonally frozen layer, and therefore, expanded existing site taliks. Results highlight the importance of canopy cover and microtopography in controlling soil thermal inputs, the ability of subsurface runoff from individual rain events to trigger warming and thaw, and the acceleration of thaw caused by consecutive wet and snowy years. As northern high-latitudes become warmer and wetter, and weather events become more extreme, the importance of these controls on soil warming and thaw is likely to increase.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ad31d7","usgsCitation":"Eklof, J., Jones, B., Dafflon, B., Devoie, E., Ring, K.M., English, M., Waldrop, M., and Neumann, R., 2024, Canopy cover and microtopography control precipitation-enhanced thaw of ecosystem-protected permafrost: Journal of Geophysical Research-Biogeosciences, v. 19, 044055, 15 p., https://doi.org/10.1088/1748-9326/ad31d7.","productDescription":"044055, 15 p.","ipdsId":"IP-162428","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad31d7","text":"Publisher Index Page"},{"id":464623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.08008194818692,\n 60.7350967339373\n ],\n [\n -151.08008194818692,\n 59.91705332357239\n ],\n [\n -149.68740720063502,\n 59.91705332357239\n ],\n [\n -149.68740720063502,\n 60.7350967339373\n ],\n [\n -151.08008194818692,\n 60.7350967339373\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2024-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Eklof, Joel","contributorId":346833,"corporation":false,"usgs":false,"family":"Eklof","given":"Joel","email":"","affiliations":[{"id":82988,"text":" Civil and Environmental Engineering, University of Washington, Seattle, WA, USA. ","active":true,"usgs":false}],"preferred":false,"id":919973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":208625,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin M.","affiliations":[{"id":37848,"text":"Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":true,"id":919974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dafflon, Baptiste","contributorId":245441,"corporation":false,"usgs":false,"family":"Dafflon","given":"Baptiste","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":919975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Devoie, Elise","contributorId":346836,"corporation":false,"usgs":false,"family":"Devoie","given":"Elise","email":"","affiliations":[{"id":82991,"text":" Department of Civil Engineering, Queen’s University, Kingston, ON, Canada ","active":true,"usgs":false}],"preferred":false,"id":919976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ring, Katie M.","contributorId":346837,"corporation":false,"usgs":false,"family":"Ring","given":"Katie","email":"","middleInitial":"M.","affiliations":[{"id":82993,"text":"Civil and Environmental Engineering, University of Washington, Seattle, WA, USA.","active":true,"usgs":false}],"preferred":false,"id":919977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"English, Marie","contributorId":346838,"corporation":false,"usgs":false,"family":"English","given":"Marie","email":"","affiliations":[{"id":82988,"text":" Civil and Environmental Engineering, University of Washington, Seattle, WA, USA. ","active":true,"usgs":false}],"preferred":false,"id":919978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":919979,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Neumann, Rebecca","contributorId":224763,"corporation":false,"usgs":false,"family":"Neumann","given":"Rebecca","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":919980,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70253209,"text":"70253209 - 2024 - Seabirds and humpback whales give early warning to marine heatwaves","interactions":[],"lastModifiedDate":"2024-04-29T11:17:49.978216","indexId":"70253209","displayToPublicDate":"2024-03-27T06:13:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17473,"text":"Open Access Government","active":true,"publicationSubtype":{"id":10}},"title":"Seabirds and humpback whales give early warning to marine heatwaves","docAbstract":"Between 2014 and 2016, an extreme marine heatwave struck the North Pacific Ocean, affecting nearshore and pelagic (offshore, open ocean) ecosystems from southern California to Alaska. This unprecedented event, characterized by unusually warm ocean temperatures over a large area, was the longest-duration marine heatwave recorded to date. The Gulf of Alaska endured some of the most severe consequences of this heatwave, now known as the Pacific Marine Heatwave or “the Blob” (Fig. 1). Marine heatwaves, like the Blob, are increasing in frequency and intensity over time, and they can cause large-scale disruptions to marine ecosystems. The increased occurrence of these events across the world's oceans in recent decades necessitates an understanding of their impact on biological communities.","language":"English","publisher":"Open Access Government","doi":"10.56367/OAG-042-10703","usgsCitation":"Bien, L., Suryan, R., Arimitsu, M.L., and Moran, J., 2024, Seabirds and humpback whales give early warning to marine heatwaves: Open Access Government, 4 p., https://doi.org/10.56367/OAG-042-10703.","productDescription":"4 p.","ipdsId":"IP-163021","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":497984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.56367/oag-042-10703","text":"Publisher Index Page"},{"id":428175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bien, Lauren","contributorId":335900,"corporation":false,"usgs":false,"family":"Bien","given":"Lauren","email":"","affiliations":[{"id":80573,"text":"PWSSC","active":true,"usgs":false}],"preferred":false,"id":899687,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suryan, Rob","contributorId":335901,"corporation":false,"usgs":false,"family":"Suryan","given":"Rob","affiliations":[{"id":80574,"text":"NOAA Auke Bay Lab","active":true,"usgs":false}],"preferred":false,"id":899688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":899689,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moran, John","contributorId":335902,"corporation":false,"usgs":false,"family":"Moran","given":"John","affiliations":[{"id":80574,"text":"NOAA Auke Bay Lab","active":true,"usgs":false}],"preferred":false,"id":899690,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252071,"text":"ofr20231094 - 2024 - Database and time series of nearshore waves along the Alaskan coast from the United States-Canada border to the Bering Sea","interactions":[],"lastModifiedDate":"2026-01-28T17:53:24.07879","indexId":"ofr20231094","displayToPublicDate":"2024-03-13T12:35:19","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1094","displayTitle":"Database and Time Series of Nearshore Waves Along the Alaskan Coast from the United States-Canada Border to the Bering Sea","title":"Database and time series of nearshore waves along the Alaskan coast from the United States-Canada border to the Bering Sea","docAbstract":"Alaska’s Arctic coast has some of the highest coastal erosion rates in the world, primarily driven by permafrost thaw and increasing wave energy. In the Arctic, a warming climate is driving sea ice cover to decrease in space and time. A lack of long-term observational wave data along Alaska’s coast challenges the ability of engineers, scientists, and planners to study and address threats and effects from wave-driven erosion and flooding. To overcome the lack of available observational wave data in the nearshore in this study by the U.S. Geological Survey, waves were downscaled with the Simulating WAves Nearshore numerical wave model (SWAN) for the hindcast period of 1979 to 2019 from the United States-Canada border to the Bering Sea utilizing nine model domains. For each domain, the model was forced at the open boundary with 2,500 representative “sea states,” which are likely combinations of significant wave heights, mean wave periods, mean wave directions, and wind speeds and directions. The sea states were obtained from the European Centre for Medium-Range Weather Forecasts “ERA5” dataset for reanalysis of winds and waves using a multivariant maximum-dissimilarity algorithm. The SWAN runs created a downscaled wave database at each grid point, which was used to reconstruct the 40-year time series in the nearshore along the 5- and 10-meter isobaths at locations approximately 400 m apart and corresponding to transects spaced approximately 50 m alongshore, as developed for USGS shoreline-change assessments. Reconstructed time series were compared to observations to validate the numerical model and the downscaled wave database method and showed overall good agreements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231094","programNote":"Prepared in cooperation with Deltares USA and the University of California, Santa Cruz","usgsCitation":"Engelstad, A.C., Erikson, L.H., Reguero, B.G., Gibbs, A.E., and Nederhoff, K., 2024, Database and time series of nearshore waves along the Alaskan coast from the United States-Canada border to the Bering Sea: U.S. Geological Survey Open-File Report 2023–1094, 23 p., https://doi.org/10.3133/ofr20231094.","productDescription":"Report: v, 23 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-132323","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499201,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116169.htm","linkFileType":{"id":5,"text":"html"}},{"id":426586,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231094/full"},{"id":426585,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1094/images"},{"id":426584,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1094/ofr20231094.xml"},{"id":426583,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1094/covrthb.jpg"},{"id":426582,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1094/ofr20231094.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426581,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P931CSO9","text":"USGS Data Release","description":"Engelstad, A.C., Erikson, L.H., Reguero, B.G., Gibbs, A.E., Nederhoff, K.M., 2024, Nearshore wave time-series along the coast of Alaska computed with a numerical wave model: U.S. Geological Survey data release, https://doi.org/10.5066/P931CSO9.","linkHelpText":"Nearshore wave time-series along the coast of Alaska computed with a numerical wave model"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.34514806758992,\n 65.52631288766165\n ],\n [\n -140.04436681759015,\n 65.52631288766165\n ],\n [\n -140.04436681759015,\n 71.42344314984271\n ],\n [\n -168.34514806758992,\n 71.42344314984271\n ],\n [\n -168.34514806758992,\n 65.52631288766165\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Changes in abundance and distribution of schooling forage fish, such as the Pacific Sand Lance Ammodytes hexapterus and Pacific Herring Clupea pallasii, can be difficult to document using traditional boat-based methods, especially in the shallow, nearshore habitats frequented by these species. In contrast, nearshore fish schools are easily observed and quantified from aircraft when light and sea conditions are favorable. We used aerial shoreline surveys to assess interannual variability in the distribution and abundance of schooling forage fish in Prince William Sound, Alaska, during the summers of 2010 and 2012–2022.
During the surveys, aerial observers classified fish schools by their size, species, and (in some cases) age-class. All observations were georeferenced along the flight path, converted to estimated surface area (m2) based on school diameter, and standardized by effort (shoreline kilometers surveyed).
Pacific Herring were widely distributed, and school densities varied annually; there were several spikes in school density of up to 54.38 m2/km interspersed among years of lower average densities (7.73–25.57 m2/km). In contrast, Pacific Sand Lance were usually limited in their distribution to a few predictable locations. School density in these consistent areas varied across years, from a high of 50.98 m2/km in 2010 to a low of 0.15 m2/km in 2017. We validated 88 schools during aerial surveys conducted in 2014–2016 and 2019–2022, of which 76 (86%) were correctly identified to species.
Here, we provide indices of Pacific Herring and Pacific Sand Lance school density over time in shallow nearshore coastal areas of Prince William Sound, Alaska. These indices were generated from aerial surveys, which offer an effective alternative to boat-based surveys for tracking forage fish schools when they occur in shallow and nearshore coastal habitats.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10283","usgsCitation":"Donnelly, D.S., Arimitsu, M.L., Pegau, S., and Piatt, J., 2024, Quantifying spatiotemporal variation of nearshore forage fish schools with aerial surveys in Prince William Sound, Alaska: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 16, no. 2, e10283, 13 p., https://doi.org/10.1002/mcf2.10283.","productDescription":"e10283, 13 p.","ipdsId":"IP-153843","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":440139,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10283","text":"Publisher Index Page"},{"id":426886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.11070413926757,\n 61.89148342543791\n ],\n [\n -150.11070413926757,\n 59.371398030413445\n ],\n [\n -142.8157822642675,\n 59.371398030413445\n ],\n [\n -142.8157822642675,\n 61.89148342543791\n ],\n [\n -150.11070413926757,\n 61.89148342543791\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Donnelly, Daniel Stephen 0000-0001-9456-885X","orcid":"https://orcid.org/0000-0001-9456-885X","contributorId":333573,"corporation":false,"usgs":true,"family":"Donnelly","given":"Daniel","email":"","middleInitial":"Stephen","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":897079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":897080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pegau, Scott","contributorId":316285,"corporation":false,"usgs":false,"family":"Pegau","given":"Scott","email":"","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":897081,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piatt, John F. 0000-0002-4417-5748","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":244053,"corporation":false,"usgs":true,"family":"Piatt","given":"John F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":897082,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252861,"text":"70252861 - 2024 - Sulphide petrology and ore genesis of the stratabound Sheep Creek sediment-hosted Zn–Pb–Ag–Sn prospect, and U–Pb zircon constraints on the timing of magmatism in the northern Alaska Range","interactions":[],"lastModifiedDate":"2024-09-23T15:25:30.720271","indexId":"70252861","displayToPublicDate":"2024-03-12T07:06:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Sulphide petrology and ore genesis of the stratabound Sheep Creek sediment-hosted Zn–Pb–Ag–Sn prospect, and U–Pb zircon constraints on the timing of magmatism in the northern Alaska Range","docAbstract":"