Using Alaskan lake sediment oxygen isotope records (δ18O), which trace the δ18O of precipitation, we establish that abrupt atmospheric shifts occurred during the last deglacial period in the North Pacific-Arctic. The robust lake δ18O chronologies confidently correlate Younger-Dryas (YD) atmospheric adjustments in Alaska with Greenland ice-core records and their seasonal sensitivity are consistent with cooling during winter. In contrast, abrupt δ18O decreases during the late Holocene observed in our records, of similar magnitude as the YD, are best explained by atmospheric modes involving long-distance transport of sub-tropical Pacific moisture. Our sediment cores are among the most reliably dated records yet produced in the circum-Arctic and show that similar decreases in δ18O of winter precipitation during the YD and late Holocene were driven by different atmospheric teleconnections. These results underscore major roles for seasonality and atmospheric patterns in the conceptual understanding of global scale climate oscillations, both past and future.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-026-68841-2","usgsCitation":"Anderson, L., Finney, B.P., and Baxter, W.B., 2026, Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals: Nature Communications, v. 17, 2287, 11 p., https://doi.org/10.1038/s41467-026-68841-2.","productDescription":"2287, 11 p.","ipdsId":"IP-173518","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":502072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-026-68841-2","text":"Publisher Index Page"},{"id":501859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.5838715688011,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 61.71714669073339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -54.47050647646307,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 76.12487765561002\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":368960,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":368961,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","middleInitial":"P.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":958186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, W. Brad","contributorId":368962,"corporation":false,"usgs":false,"family":"Baxter","given":"W.","middleInitial":"Brad","affiliations":[{"id":87683,"text":"U.S. Army Corps of Engineers, Cold Regions Research and Engineering Lab","active":true,"usgs":false}],"preferred":false,"id":958187,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273876,"text":"70273876 - 2026 - Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave","interactions":[],"lastModifiedDate":"2026-02-11T15:25:43.001543","indexId":"70273876","displayToPublicDate":"2026-02-04T09:17:59","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave","docAbstract":"Chinook salmon population declines span their geographic range with climate hypothesized as a major driver. Concerns of warming freshwater temperatures in their northern range gained urgency during 2019 when a heatwave coincided with premature mortality. This study examined heat stress during the 2019 heatwave compared to subsequent years and described water temperatures in western Alaska to understand the degree to which freshwater temperatures may be a stressor. Heat stress was prevalent among Chinook salmon captured in the 2019 heatwave (Kuskokwim tributaries: 90% in Kwethluk and 63% Takotna river), and variable in subsequent years (∼8% to 60% across Kuskokwim tributaries and Norton Sound rivers). A review of water temperature data indicated that potentially stressful temperatures (≥18 °C) were most common and prolonged in the Yukon River, moderately common and prolonged in the Kuskokwim River, and relatively rare in the Norton Sound region. Water temperatures in 2019 broke several records for overall maximum and frequency of temperatures ≥ 18 °C. Migration water temperatures and heat stress in northern Pacific salmon habitats vary more widely than previously recognized (up to 25 °C).
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0109","usgsCitation":"von Biela, V.R., Regish, A.M., McCormick, S.D., Spaeder, J., Whitworth, K., Leon, J., Gillikin, D., Liller, Z., Ivanoff, R., Bell, J., Larson, S.D., Carey, M.P., and Zimmerman, C.E., 2026, Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave: Canadian Journal of Fisheries and Aquatic Sciences, https://doi.org/10.1139/cjfas-2025-0109.","ipdsId":"IP-171279","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":499750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"western Alaska","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":955346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science 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D.","contributorId":366146,"corporation":false,"usgs":false,"family":"Larson","given":"Sean","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":955356,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":955357,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":955358,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70274206,"text":"70274206 - 2026 - Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation","interactions":[],"lastModifiedDate":"2026-03-12T14:13:31.609824","indexId":"70274206","displayToPublicDate":"2026-02-02T09:08:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation","docAbstract":"The Fairbanks region of central Alaska is part of a broad zone of intraplate crustal deformation, situated north of the Denali fault and north of the ongoing collision and flat‐slab subduction of the Yakutat oceanic plateau. Seismicity in the Fairbanks region occurs both in diffuse areas as well as in well‐defined lineaments, such as the left‐lateral Salcha fault, which hosted the 1937 M8 7.3 earthquake. Starting with the regional seismicity catalog, we perform waveform cross‐correlation, network‐matched filtering, and relative relocation to obtain an enhanced seismicity catalog over the time period 2014–2024. Based on the relocated catalog, we interpret a set of 15 fault segments, including two conjugate faults and two new faults east of the previously documented fault system. Considering the combined seismicity in the Minto and Fairbanks regions, the median depth of seismicity decreases from east (6 km) to west (20 km). Our interpreted faults provide guidance for future tectonic modeling and assessment of seismic hazards in this region.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250342","usgsCitation":"Sims, N.E., Tape, C., Ruppert, N., and West, M.E., 2026, Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation: Seismological Research Letters, v. 97, no. 2A, p. 877-896, https://doi.org/10.1785/0220250342.","productDescription":"20 p.","startPage":"877","endPage":"896","ipdsId":"IP-184501","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250342","text":"Publisher Index Page"},{"id":500986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Fairbanks region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154,\n 66.5\n ],\n [\n -154,\n 63\n ],\n [\n -144,\n 63\n ],\n [\n -144,\n 66.5\n ],\n [\n -154,\n 66.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"2A","noUsgsAuthors":false,"publicationDate":"2026-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Sims, Nealey E.","contributorId":367184,"corporation":false,"usgs":false,"family":"Sims","given":"Nealey","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":956981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":956982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Natalia A. 0000-0003-0589-1159","orcid":"https://orcid.org/0000-0003-0589-1159","contributorId":351514,"corporation":false,"usgs":true,"family":"Ruppert","given":"Natalia A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"West, Michael E.","contributorId":367185,"corporation":false,"usgs":false,"family":"West","given":"Michael","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":956984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274214,"text":"70274214 - 2026 - Living with wildfire in Funny River, Alaska: 2023 Data report","interactions":[],"lastModifiedDate":"2026-03-13T13:58:40.781766","indexId":"70274214","displayToPublicDate":"2026-02-01T08:50:25","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":72,"text":"Research Note","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"RMRS-RN-109","title":"Living with wildfire in Funny River, Alaska: 2023 Data report","docAbstract":"Homeowner wildfire risk mitigation and preparedness are important components of community wildfire readiness. This report describes the data collected through two efforts conducted in the Funny River, Alaska, study area: (1) parcel-level rapid wildfire risk assessments performed by trained assessors and (2) homeowner surveys in which respondents provided self-assessments of their parcel-level wildfire risk. This project was undertaken to support the Kenai Peninsula Borough Office of Emergency Management and Central Emergency Services to inform decisions about wildfire adaptation. The household surveys explored the social dimensions of wildfire, including understanding of wildfire risk, outreach or communication preferences, mitigation and evacuation preparedness activities, and perceptions of community risk reduction strategies. Overall, the study indicated a community that was engaged in preparing for and mitigating the risk of wildfire; however, more mitigation work with respect to defensible space and home hardening could help reduce overall wildfire risk.
","language":"English","publisher":"USDA Forest Service","doi":"10.2737/RMRS-RN-109","usgsCitation":"Donovan, C., Wittenbrink, S., Brenkert-Smith, H., Kuehn, J., McBride, P., Champ, P.A., Barth, C.M., Meldrum, J., Wagner, C., and Taniguchi, C., 2026, Living with wildfire in Funny River, Alaska: 2023 Data report: Research Note RMRS-RN-109, vi, 161 p., https://doi.org/10.2737/RMRS-RN-109.","productDescription":"vi, 161 p.","ipdsId":"IP-180325","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":501126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Funny River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.89402263513273,\n 60.555695875687434\n ],\n [\n -150.89402263513273,\n 60.47080634420749\n ],\n [\n -150.61232052087988,\n 60.47080634420749\n ],\n [\n -150.61232052087988,\n 60.555695875687434\n ],\n [\n -150.89402263513273,\n 60.555695875687434\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2026-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":957062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wittenbrink, Suzanne","contributorId":333353,"corporation":false,"usgs":false,"family":"Wittenbrink","given":"Suzanne","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":957063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":957064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuehn, Josh","contributorId":269634,"corporation":false,"usgs":false,"family":"Kuehn","given":"Josh","email":"","affiliations":[{"id":56021,"text":"Colorado State Forest Service","active":true,"usgs":false}],"preferred":false,"id":957065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McBride, Paul","contributorId":367213,"corporation":false,"usgs":false,"family":"McBride","given":"Paul","affiliations":[{"id":87597,"text":"Office of Emergency Management, Kenai Peninsula Borough, Alaska","active":true,"usgs":false}],"preferred":false,"id":957066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Champ, Patricia A. 0000-0003-1917-883X","orcid":"https://orcid.org/0000-0003-1917-883X","contributorId":360956,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","middleInitial":"A.","affiliations":[{"id":86128,"text":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":957067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barth, Christopher M.","contributorId":367214,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","middleInitial":"M.","affiliations":[{"id":86132,"text":"U.S. Department of Agriculture, Forest Service, Washington Office","active":true,"usgs":false}],"preferred":false,"id":957068,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":957069,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":957070,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Taniguchi, Christine","contributorId":355605,"corporation":false,"usgs":false,"family":"Taniguchi","given":"Christine","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":957071,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273920,"text":"70273920 - 2026 - Earthquake-hazard exposure of residents with potential access and functional needs in the United States","interactions":[],"lastModifiedDate":"2026-02-17T17:31:14.852","indexId":"70273920","displayToPublicDate":"2026-01-23T11:24:56","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake-hazard exposure of residents with potential access and functional needs in the United States","docAbstract":"Earthquake response plans and earthquake early warning (EEW) systems designed for general populations may not consider potential access and functional needs (AFN) of individuals with physical, sensory, cognitive, or social limitations. Previous efforts to map the distribution of these populations have focused on social-vulnerability indices that ignore or oversimply these limitations. The descriptive and exploratory analysis summarized in this United States (U.S.) case study addresses this gap by identifying and integrating spatially explicit data for AFN-related residential populations, earthquake hazards, and county and county equivalents for the conterminous U.S., Alaska, Puerto Rico, and Hawaii. We focus on 13 AFN-related attributes that relate to an individual's ability to access information contained in an EEW alert, to understand and process earthquake information or observed ground shaking, and to take self-protective actions based on this information and physical cues of an earthquake. Depending on the demographic attribute, there are millions to tens of millions of U.S. residents with AFN-related attributes in areas considered to have varying likelihoods (2%, 10%, and 50%) of exceedance of a damaging earthquake in the next 50 years. Although these amounts represent low percentages at the national level, the percentage of individuals with AFN-related attributes in many counties and county equivalents substantially exceeds national percentages. No one county, county equivalent, U.S. state, or U.S. territory has the highest percentage of individuals in all AFN-related attributes; therefore, future efforts to increase individual resilience to earthquakes may benefit from understanding the local context of individuals with potential access and functional needs.
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bears","interactions":[],"lastModifiedDate":"2026-01-23T15:24:10.860219","indexId":"70273704","displayToPublicDate":"2026-01-21T09:14:16","publicationYear":"2026","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":"An energetic tradeoff best explains parturition timing in grizzly bears","docAbstract":"Timing of grizzly bear (Ursus arctos) parturition during hibernation has been explained by ancestral traits (delayed implantation, altricial young, obligate maternal denning), but the ultimate driver underlying precise timing has not been fully explored. Capitalizing on an observed latitudinal increase in denning duration among four populations in interior North America, we tested two alternative hypotheses. First, that birth timing results from a physiological cue that synchronizes implantation with the onset of hibernation, allowing females to forgo reproduction should they lack adequate fat stores. Alternatively, that parturition is optimally timed relative to den exit to balance an energetic tradeoff between minimizing lactation time to protect the mother and maximizing developmental time to increase cub survival. Using parturition dates previously predicted from accelerometer data (27 Dec–28 Feb), we classified 115 females according to apparent litter survival when first visually observed after den exit: 57% successful (with cubs), 22% unsuccessful (alone), and 21% unknown (not observed). The number of days between birth and den exit showed no association with latitude (p = 0.29). It averaged 103 days among successful females but only 77 days among unsuccessful females (p < 0.001) owing to later births and earlier exit. With each increasing degree of latitude, birth date increased by 1.0 and number of days between den entry and birth increased by 2.5 (p < 0.001). Implantation dates were not centered on den entry dates (p < 0.001). These results supported the energetic tradeoff hypothesis and suggested natural selection has favored a consistent number of days between parturition and den exit under average body conditions and shifts toward later or earlier births for females with lower or higher levels of bodily stored energy, respectively. This flexible tradeoff may support resilience to climate change and present a possible mechanism explaining reduced natality and cub survival in high-density populations.
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E.","contributorId":365515,"corporation":false,"usgs":false,"family":"Teisberg","given":"J.","middleInitial":"E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954358,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954359,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vinks, M. A.","contributorId":365519,"corporation":false,"usgs":false,"family":"Vinks","given":"M.","middleInitial":"A.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":954360,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70273942,"text":"70273942 - 2026 - Harmonization of aggregated freshwater biotic data to support continental and global assessment","interactions":[],"lastModifiedDate":"2026-02-19T14:32:03.770691","indexId":"70273942","displayToPublicDate":"2026-01-20T08:29:18","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11111,"text":"PLOS Water","active":true,"publicationSubtype":{"id":10}},"title":"Harmonization of aggregated freshwater biotic data to support continental and global assessment","docAbstract":"Biodiversity loss and conservation are increasingly coming into focus in global policy fora, requiring information and assessments at wider spatial and temporal scales than previously considered. However, the monitoring framework required to support such data collection and assessment is lacking in many countries and is not harmonized across countries, hampering these efforts. Aggregation of existing freshwater data offers a solution to the problem of assessing status and trends of ecosystems and biodiversity at large spatial scales in the absence of nationally coordinated monitoring efforts. Analysis of aggregated data from different sources, collected using different protocols and with varying levels of metadata and supporting data, can be challenging and requires decisions regarding data comparability. In this paper, we identify the challenges inherent in harmonizing aggregated freshwater data for analysis, including general concerns related to research goals, spatial and temporal scale, sample selection, sampling effort, and site integrity. We also discuss the challenges related to measured parameters, sampled habitats, sample collection and processing methods, and data integrity for phytoplankton, benthic algae, macrophytes, zooplankton, benthic macroinvertebrates, fish, and supporting variables such as water and sediment chemistry. We provide a workflow to evaluate each of these challenges and make decisions about how best to work with the data. Finally, we review a case study from a large-scale analysis of freshwater data from the circumpolar Arctic region that exemplifies the encountered challenges and the chosen solutions. Through the description of the case study, we provide practical solutions to support aggregation and analysis of existing freshwater data. As global conversations about biodiversity status and trends continue, the demand for large-scale analyses of data from different sources will only grow. In the absence of globally harmonized monitoring, we are faced with the need to ensure comparability of data, making expert judgements where needed to support sound conclusions.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000502","usgsCitation":"Lento, J., Laske, S.M., Culp, J.M., Goedkoop, W., Kahlert, M., Lau, D.C., Lavoie, I., Musetta-Lambert, J., Ólafsson, J.S., and Christoffersen, K.S., 2026, Harmonization of aggregated freshwater biotic data to support continental and global assessment: PLOS Water, v. 5, no. 1, e0000502, 27 p., https://doi.org/10.1371/journal.pwat.0000502.","productDescription":"e0000502, 27 p.","ipdsId":"IP-180104","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":500254,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000502","text":"Publisher Index Page"},{"id":500141,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lento, Jennifer","contributorId":221451,"corporation":false,"usgs":false,"family":"Lento","given":"Jennifer","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":955855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":955856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Culp, Joseph M.","contributorId":366416,"corporation":false,"usgs":false,"family":"Culp","given":"Joseph","middleInitial":"M.","affiliations":[{"id":87479,"text":"Cold Regions Research Centre and Department of Biology, Wilfrid Laurier University","active":true,"usgs":false}],"preferred":false,"id":955857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goedkoop, Willem","contributorId":366417,"corporation":false,"usgs":false,"family":"Goedkoop","given":"Willem","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kahlert, Maria","contributorId":366418,"corporation":false,"usgs":false,"family":"Kahlert","given":"Maria","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lau, Danny C.P.","contributorId":366419,"corporation":false,"usgs":false,"family":"Lau","given":"Danny","middleInitial":"C.P.","affiliations":[{"id":87480,"text":"Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment","active":true,"usgs":false}],"preferred":false,"id":955860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lavoie, Isabelle","contributorId":255561,"corporation":false,"usgs":false,"family":"Lavoie","given":"Isabelle","email":"","affiliations":[{"id":51586,"text":"Institut national de la recherche scientifique, Centre Eau Terre Environnement","active":true,"usgs":false}],"preferred":false,"id":955861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Musetta-Lambert, Jordan","contributorId":366420,"corporation":false,"usgs":false,"family":"Musetta-Lambert","given":"Jordan","affiliations":[{"id":87481,"text":"Watershed Hydrology and Ecology Research Division, National Hydrology Research Centre, Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":955862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ólafsson, Jón S.","contributorId":366421,"corporation":false,"usgs":false,"family":"Ólafsson","given":"Jón","middleInitial":"S.","affiliations":[{"id":40381,"text":"Marine and Freshwater Research Institute, Iceland","active":true,"usgs":false}],"preferred":false,"id":955863,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christoffersen, Kirsten S.","contributorId":366422,"corporation":false,"usgs":false,"family":"Christoffersen","given":"Kirsten","middleInitial":"S.","affiliations":[{"id":87482,"text":"Freshwater Biological Section, Department of Biology, University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":955864,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273983,"text":"70273983 - 2026 - Season and antecedent conditions impact concentration-discharge relationships for dissolved organic carbon and alkalinity in southeast Alaskan watershed","interactions":[],"lastModifiedDate":"2026-02-23T16:39:57.697198","indexId":"70273983","displayToPublicDate":"2026-01-06T09:32:45","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9326,"text":"JGR Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Season and antecedent conditions impact concentration-discharge relationships for dissolved organic carbon and alkalinity in southeast Alaskan watershed","docAbstract":"Fluvial export of dissolved carbon plays an important role in watershed-scale biogeochemistry. Predicted changes in climate are expected to impact watershed hydrologic regimes, and in turn, the sources and export of dissolved carbon from watersheds. Here, we utilize high resolution measurements of discharge and dissolved carbon concentration to examine how concentration-discharge (CQ) relationships vary seasonally and during high flow events over the main runoff season (May–October) in a temperate forested watershed in Southeast Alaska. Concentration-discharge relationships for dissolved organic carbon (DOC) and alkalinity demonstrated strong seasonal patterns, with more linear relationships in May and June versus other months. Changing power law model slopes (b values; the exponent in a power law regression between runoff and carbon yields) indicated potentially shifting watershed sources (biogenic vs. geologic) and contrasting dominant flowpaths (shallow vs. deeper groundwater) for DOC and alkalinity over the sampling period. During the largest storm event of the study, DOC and alkalinity b values shifted from an overall pattern of transport (mean b = 1.58 values >1.0 indicate transport limitation) and source limitation (mean b = 0.48, values <1.0 indicate source limitation) to chemostatic (DOC, b = 0.99; alkalinity, b = 1.019). In June through August, patterns in hysteresis index suggest that CQ relationships were altered when storms followed in close succession to each other. Together, these findings indicate that seasonal and antecedent flow conditions play a role in dissolved carbon export from forested watersheds. Understanding these dynamics, particularly during winter months, will become increasingly important as changes to hydroclimate impact riverine carbon export.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JG009090","usgsCitation":"Delbecq, C., Fellman, J.B., Bellmore, J.R., Whitney, E.J., Fitzgerald, K., Falke, J.A., 2026, Season and antecedent conditions impact concentration-discharge relationships for dissolved organic carbon and alkalinity in southeast Alaskan watershed: JGR Biogeosciences, v. 131, no. 1, e2025JG009090, 15 p., https://doi.org/10.1029/2025JG009090.","productDescription":"e2025JG009090, 15 p.","ipdsId":"IP-174690","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jg009090","text":"Publisher Index Page"},{"id":500420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Montana Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.63915248759182,\n 59.21990475595436\n ],\n [\n -136.63915248759182,\n 57.522914720234525\n ],\n [\n -134.63466688093874,\n 57.522914720234525\n ],\n [\n -134.63466688093874,\n 59.21990475595436\n ],\n [\n -136.63915248759182,\n 59.21990475595436\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"131","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Delbecq, Claire","contributorId":337162,"corporation":false,"usgs":false,"family":"Delbecq","given":"Claire","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":955990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fellman, Jason B.","contributorId":366494,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason","middleInitial":"B.","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":955991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bellmore, J. Ryan","contributorId":366495,"corporation":false,"usgs":false,"family":"Bellmore","given":"J.","middleInitial":"Ryan","affiliations":[{"id":27863,"text":"U. S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":955992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitney, Emily J.","contributorId":366496,"corporation":false,"usgs":false,"family":"Whitney","given":"Emily","middleInitial":"J.","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":955993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzgerald, Kevin","contributorId":332288,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Kevin","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":955994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955995,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274052,"text":"70274052 - 2026 - Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins","interactions":[],"lastModifiedDate":"2026-02-23T15:27:36.372921","indexId":"70274052","displayToPublicDate":"2026-01-06T08:21:05","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins","docAbstract":"Climatic extremes can impact the productivity of aquatic species, affecting ecosystems and fishery-dependent communities. Advances in climate products, such as gridded datasets and downscaled projections, may be useful for quantifying freshwater habitat conditions and predicting climate change effects on fish. However, limited guidance exists for selecting climate products to develop indicators of freshwater habitat conditions that influence fish population dynamics. Here, we develop an approach for identifying streamflow and stream temperature models to address this need. We evaluated skill in predicted versus observed streamflow and stream temperature, with predictions depending on different models and gridded climate data as inputs. The best performing models were used in a case study exploring habitat conditions influencing Chinook salmon in the Yukon and Kuskokwim River basins, two remote high-latitude watersheds with few in situ habitat observations and recent salmon declines. Three modeled streamflow datasets had variable performance (median Nash–Sutcliffe efficiencies from 0.39 to 0.70). Three gridded temperature products differed in their ability to explain variation in weekly stream temperatures (median r2 from 0.42 to 0.76). We selected a single gridded air temperature dataset to compare two novel predictive stream temperature models, both of which had good accuracy (root mean squared error [RMSE] of 1.19 and 0.95°C). Stream temperature indicators calculated from modeled daily data, maximum temperatures during adult migration and cumulative temperatures during juvenile rearing, had high spatial correlation across tributaries within the Yukon and Kuskokwim River basins and showed significant warming over the past 40 years. Streamflow indicators calculated from modeled daily data, maximum flow during spawning and median flow during rearing, had few trends and were largely uncorrelated within the Yukon River basin and moderately correlated within the Kuskokwim River basin. Overall, we found that generic measures of model performance varied considerably, and it was important to consider the models best suited to our case study. For both streamflow and stream temperature, multiple high-performing models allowed estimation of ecologically relevant conditions affecting Chinook salmon. The approach we used to estimate local-scale habitat conditions has value to identify synchronous conditions that may influence multiple salmon populations under a changing subarctic climate.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70399","usgsCitation":"Shaftel, R., Feddern, M.L., McAfee, S.A., Schoen, E.R., Cunningham, C., von Biela, V.R., Paul, J., Cheng, Y., Newman, A., Perdue, M., Schwenk, J., von Finster, A., Falke, J.A., 2026, Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins: Ecosphere, v. 17, no. 1, e70399, 25 p., https://doi.org/10.1002/ecs2.70399.","productDescription":"e70399, 25 p.","ipdsId":"IP-170801","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500622,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70399","text":"Publisher Index Page"},{"id":500403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kuskokwim River basin, Yukon River 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USA","interactions":[],"lastModifiedDate":"2026-04-06T15:43:42.592143","indexId":"70273459","displayToPublicDate":"2026-01-06T08:06:52","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Tectonic implications of transitional melting regimes from petrological, geochronological, and compositional characterization of the ophiolitic Seventymile terrane, Alaska, USA","docAbstract":"New geochemical, U-Pb geochronology, and Sr-Nd-Hf isotope data provide evidence for the tectonic evolution of the Seventymile terrane in interior Alaska, USA. Ultramafic and mafic rocks of the Seventymile terrane are thought to represent components of a dismembered ophiolite and provide unique constraints on regional terrane evolution and accretion. The Seventymile ophiolite represents fragments of the Devonian to Permian Slide Mountain Ocean (SMO) that separated allochthonous and parautochthonous continental fragments of western North America. It now occurs as multiple thrust sheets containing Permian mafic and ultramafic rocks overlying and/or possibly imbricated with amphibolite-facies supracrustal rocks of allochthonous Yukon-Tanana terrane and parautochthonous North America. Seventymile klippen contain variably serpentinized peridotite, primarily harzburgite, low-grade meta-mafic rocks, and minor oceanic sedimentary rocks (argillite, chert, limestone, and metasandstone). Mafic rocks include gabbro to diabase, typically as dikes, veinlets, or rare massive stocks intruding peridotite. Mafic rocks also include greenstones of the Seventymile assemblage in klippen structurally underlying, and in shear zone contact with, ultramafic klippen.
New trace element and radiogenic isotope data from mafic magmatic rocks associated with the Seventymile ultramafic bodies show evidence for a weakly subduction-modified mantle source, like the mantle source of normal mid-ocean-ridge basalt (N-MORB) or back-arc basin basalt (BABB). Seventymile assemblage greenstones are more heterogeneous. They range from N-MORB to enriched mid-ocean-ridge basalt (E-MORB) and ocean-island basalt (OIB), with a subset of samples indicative of continental arc affinity. These geochemistry results indicate that distinct tectonic environments are represented by at least two, and possibly three, lithological and structural units comprising the Seventymile terrane. Hf-Nd isotope systematics are consistent with a depleted MORB mantle (DMM)−like component that overlaps with Pacific MORB. Primary zircon is rare, but new in situ U-Pb data for gabbro and greenstone indicate ca. 274−272 Ma peak zircon and titanite crystallization. Scattered younger zircons define a ca. 255 Ma zircon peak and correspond to secondary crystallization associated with baddeleyite reaction of high-Si fluids during low-grade metamorphism. If Seventymile suites are contemporaneous, obduction associated with the closure of the SMO resulted in the stacking of ophiolitic packages representing distinct tectonomagmatic settings across the transition from pericontinental, to epicontinental, to distal ocean back-arc. Intrusions hosted in klippe of ultramafic rocks, plus the least subduction-modified greenstones underlying them, geologically and compositionally resemble Slide Mountain rocks of the Campbell Range formation in eastern Yukon and may provide a new piercing point across the Tintina fault.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1130/GES02837.1","usgsCitation":"Todd, E., Caine, J., Bizimis, M., Kylander-Clark, A.R., Hammond, R.R., and Wypych, A., 2026, Tectonic implications of transitional melting regimes from petrological, geochronological, and compositional characterization of the ophiolitic Seventymile terrane, Alaska, USA: Geosphere, v. 22, no. 2, p. 296-339, https://doi.org/10.1130/GES02837.1.","productDescription":"44 p.","startPage":"296","endPage":"339","ipdsId":"IP-170876","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498608,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498699,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02837.1","text":"Publisher Index Page"}],"country":"Canada, United States","state":"Alaska, British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.54814578278632,\n 64.49262655255515\n ],\n [\n -151.54814578278632,\n 59.59805672240421\n ],\n [\n -133.60437046462778,\n 59.59805672240421\n ],\n [\n -133.60437046462778,\n 64.49262655255515\n ],\n [\n -151.54814578278632,\n 64.49262655255515\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-06","publicationStatus":"PW","contributors":{"authors":[{"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":953782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":953783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bizimis, Michael","contributorId":192879,"corporation":false,"usgs":false,"family":"Bizimis","given":"Michael","email":"","affiliations":[],"preferred":false,"id":953784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kylander-Clark, Andrew R.C. 0000-0002-4034-644X","orcid":"https://orcid.org/0000-0002-4034-644X","contributorId":302380,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","middleInitial":"R.C.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":953785,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammond, Robert Reece","contributorId":365154,"corporation":false,"usgs":false,"family":"Hammond","given":"Robert","middleInitial":"Reece","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":953786,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wypych, Alicja","contributorId":216040,"corporation":false,"usgs":false,"family":"Wypych","given":"Alicja","email":"","affiliations":[{"id":39354,"text":"State of Alaska Department of Natural Resources DGGS Fairbanks","active":true,"usgs":false}],"preferred":false,"id":953787,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273351,"text":"70273351 - 2026 - Toward an efficient framework for remote sensing of river bathymetry: Comparing sensors and algorithms on an inaccessible proglacial river in Alaska","interactions":[],"lastModifiedDate":"2026-01-09T17:12:25.941374","indexId":"70273351","displayToPublicDate":"2025-12-27T11:01:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Toward an efficient framework for remote sensing of river bathymetry: Comparing sensors and algorithms on an inaccessible proglacial river in Alaska","docAbstract":"Remote sensing can provide reliable information on river depths and this approach might be particularly valuable in areas that are difficult to survey via conventional field methods. In this study, we assessed the potential to map the bathymetry of an inaccessible proglacial river in Alaska from both aerial orthophotos and a multispectral satellite image. In addition, we evaluated a variety of depth retrieval algorithms with different input data requirements, including some methods that require field measurements of water depth for calibration and other techniques that can be applied even when such field data are not available. These approaches might enable more efficient use of remote sensing methods by resource management agencies. Our results suggest that bathymetric mapping along the turquoise-colored river we examined was not only feasible but highly accurate ( R2 up to 0.94) for both types of image data. Algorithms that use paired observations of depth and reflectance to train depth retrieval models were the most accurate, with errors on the order of 15%–20% and little or no bias. Alternative techniques based on hydraulic and statistical concepts also led to strong agreement between predicted and observed depths but were more susceptible to systematic biases toward under- or over-estimation of depth. In contrast to clear-flowing streams, bathymetric mapping in this environment was enabled by a direct relationship between the depth and brightness of the water due to scattering by suspended sediment. In selecting an appropriate depth retrieval method, a compromise might need to be reached between the level of field effort invested and the accuracy of the resulting image-derived bathymetry. Standalone software for implementing these techniques is freely available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2025.110140","usgsCitation":"Legleiter, C.J., Leonard, C.M., Burger, P.A., Pletcher, A.G., and Kinzel, P.J., 2026, Toward an efficient framework for remote sensing of river bathymetry: Comparing sensors and algorithms on an inaccessible proglacial river in Alaska: Geomorphology, v. 495, 110140, 24 p., https://doi.org/10.1016/j.geomorph.2025.110140.","productDescription":"110140, 24 p.","ipdsId":"IP-179757","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":498513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United states","state":"Alaska","otherGeospatial":"Mulchatna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.00824680332022,\n 60.789825438561536\n ],\n [\n -154.09788058802903,\n 60.789825438561536\n ],\n [\n -154.09788058802903,\n 60.770469283939605\n ],\n [\n -154.00824680332022,\n 60.770469283939605\n ],\n [\n -154.00824680332022,\n 60.789825438561536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"495","noUsgsAuthors":false,"publicationDate":"2025-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":953420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Christina M. 0000-0002-5096-8103","orcid":"https://orcid.org/0000-0002-5096-8103","contributorId":360578,"corporation":false,"usgs":false,"family":"Leonard","given":"Christina","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":953421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burger, Paul A. 0009-0005-7135-8290","orcid":"https://orcid.org/0009-0005-7135-8290","contributorId":360579,"corporation":false,"usgs":false,"family":"Burger","given":"Paul","middleInitial":"A.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":953422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pletcher, Addison G. 0009-0002-3775-0852","orcid":"https://orcid.org/0009-0002-3775-0852","contributorId":360580,"corporation":false,"usgs":false,"family":"Pletcher","given":"Addison","middleInitial":"G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":953423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":953424,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273084,"text":"70273084 - 2026 - A time-space model of graphite mineral systems","interactions":[],"lastModifiedDate":"2026-03-23T14:05:12.786795","indexId":"70273084","displayToPublicDate":"2025-12-12T09:03:53","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"A time-space model of graphite mineral systems","docAbstract":"Increasing demand for graphite in energy storage systems warrants review of graphite ore genesis in a mineral systems framework. Orogenic graphite encompasses the metamorphic and orogenic mineral systems that produce flake graphite and hydrothermal vein (lump and chip) graphite deposits, respectively. A common feature of orogenic graphite deposits is an association with upper amphibolite- to granulite-facies metasedimentary rocks in continent-continent or continent-island arc collisional orogens. Orogenic flake graphite deposits form primarily through graphitization of organic carbon during regional metamorphism, but strain localization and partial melting of pelitic protoliths are likely important processes for graphite grade and quality enrichment. Orogenic vein graphite deposits precipitate from hydrothermal fluids, possibly derived from metamorphism or anatexis at depth. Decarbonation reactions in mixed calcareous-carbonaceous metasedimentary sequences are the most likely carbon sources for the veins. In contrast, intrusion-related graphite includes magmatic-hydrothermal and metamorphic mineral systems that form primarily in continental arc settings via the interaction of magmas with carbonaceous sedimentary packages. Magmatic-hydrothermal flake graphite deposits are hosted in plutonic and volcanic rocks, and result from the exsolution of CO2-CH4-rich fluids from melts contaminated by such packages. Contact metamorphism of carbonaceous sedimentary rocks by plutons produces some microcrystalline (amorphous) graphite deposits, including many in China. Compilation of geologic data from known graphite deposits globally suggests that pulses of carbon deposition in the Paleoproterozoic, Mesoproterozoic, and Neoproterozoic provided source carbon material. Subsequent supercontinent orogenesis at ca. 2,100 to 1,700 Ma (Columbia), ca. 1,300 to 1,000 Ma (Rodinia), and ca. 650 to 500 Ma (Gondwana) resulted in the genesis of orogenic flake and vein graphite deposits, where favorable geologic components overlapped with organic ± carbonate carbon-rich strata. Cryogenian deposition of graphite protoliths and Cryogenian – Cambrian metamorphic mineralization account for nearly 75% of all known resources globally and coincide with profound carbon isotope excursions and climate variability, implying a link with the global carbon budget. Comparatively few graphite deposits are associated with Pangea-forming orogens, attributed to less exhumation and/or denudation. High-temperature metasedimentary belts containing organic carbon-rich protoliths are most favorable for hosting orogenic flake graphite deposits, whereas sequences that also contain carbonate protoliths are favorable for orogenic graphite veins. Continent-scale orogenic belts may host both deposit types along with vanadium deposits. Use of a time-space mineral systems framework for graphite deposits can improve exploration models needed to ensure future supply of this critical mineral and provide insights into Earth’s long-term carbon cycle.
","language":"English","publisher":"Springer","doi":"10.1007/s00126-025-01412-5","usgsCitation":"Case, G.N., 2026, A time-space model of graphite mineral systems: Mineralium Deposita, v. 61, p. 783-810, https://doi.org/10.1007/s00126-025-01412-5.","productDescription":"28 p.","startPage":"783","endPage":"810","ipdsId":"IP-177742","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":497464,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":497697,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00126-025-01412-5","text":"Publisher Index Page"}],"volume":"61","noUsgsAuthors":false,"publicationDate":"2025-12-12","publicationStatus":"PW","contributors":{"authors":[{"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":952260,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70275030,"text":"70275030 - 2026 - Land cover, elevation, and precipitation predict distribution and hotspots of three bird species of concern in boreal Alaska","interactions":[],"lastModifiedDate":"2026-04-13T14:53:18.323215","indexId":"70275030","displayToPublicDate":"2025-11-21T09:44:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Land cover, elevation, and precipitation predict distribution and hotspots of three bird species of concern in boreal Alaska","docAbstract":"The boreal forest biome is an important breeding area for migratory birds and is undergoing rapid changes, including drying of wetlands, changes to vegetation composition, and human development. Many boreal bird populations are declining, but information is often lacking on how these species associate with habitat characteristics and thus how they may respond to changing conditions. We used a large point-count dataset to describe habitat associations and hotspots for three boreal species of concern in Alaska, USA: Tringa flavipes (Lesser Yellowlegs), Contopus cooperi (Olive-sided Flycatcher), and Euphagus carolinus (Rusty Blackbird). We used an N-mixture model to evaluate covariates of abundance and two components of detection (availability and perceptibility). We then used the estimated relationships with covariates to predict density of each species across the Northwestern Interior Forest (Bird Conservation Region 4) in Alaska, including identifying hotspots where density was predicted to be in the top 10% of all locations. T. flavipes and E. carolinus were associated with wetlands and mean values of June precipitation; T. flavipes were also associated with low elevation and recent fire; and C. cooperi was associated with needleleaf forest and moderate elevation. Hotspots for T. flavipes and E. carolinus usually overlapped, while hotspots for C. cooperi almost never overlapped with those of the other two species. Following ground-truthing, these predicted distributions could be used to indicate areas of high importance for species of conservation concern and thus inform management decisions and mitigation measures. Our results could also help identify areas that are likely to be important for these species in the future, given the rapid changes now occurring across the boreal biome in response to climate warming and drying.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf072","usgsCitation":"Weiser, E.L., Christie, K., Burns, C.T., Hagelin, J.C., Matsuoka, S.M., Johnson, J.A., and Handel, C.M., 2026, Land cover, elevation, and precipitation predict distribution and hotspots of three bird species of concern in boreal Alaska: Ornithological Applications, v. 128, no. 1, p. 1-14, https://doi.org/10.1093/ornithapp/duaf072.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-173816","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":504063,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1A9HM4R","text":"USGS data release","linkHelpText":"R scripts to run model of bird density and habitat associations"},{"id":502996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duaf072","text":"Publisher Index Page"},{"id":502742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.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 -151.1832172747073,\n 59.13365735004231\n ],\n [\n -147.31692125943155,\n 59.58285918598074\n ],\n [\n -144.5504762366018,\n 59.98787477154784\n ],\n [\n -140.98899437078293,\n 60.56824776252196\n ],\n [\n -140.97836768707944,\n 68.7876537335149\n ],\n [\n -163.90405087591324,\n 67.79343524918025\n ],\n [\n -162.87185288557635,\n 66.98967164182704\n ],\n [\n -159.64110532284926,\n 66.37323884592763\n ],\n [\n -160.51454911606677,\n 65.3848210134932\n ],\n [\n -163.66272432299337,\n 64.88616256748963\n ],\n [\n -162.92957746110244,\n 64.45699993046611\n ],\n [\n -160.98494728134088,\n 64.64573400264587\n ],\n [\n -161.77397727382123,\n 62.99858790802136\n 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Threatened","active":true,"usgs":false}],"preferred":false,"id":959265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Casey T.","contributorId":244656,"corporation":false,"usgs":false,"family":"Burns","given":"Casey","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":959266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagelin, Julie C 0000-0002-0434-6936","orcid":"https://orcid.org/0000-0002-0434-6936","contributorId":270470,"corporation":false,"usgs":false,"family":"Hagelin","given":"Julie","email":"","middleInitial":"C","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":959267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":959268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, James A. 0000-0002-2312-0633","orcid":"https://orcid.org/0000-0002-2312-0633","contributorId":299054,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":959269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":959270,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273453,"text":"70273453 - 2026 - The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","interactions":[],"lastModifiedDate":"2026-02-09T16:24:50.573071","indexId":"70273453","displayToPublicDate":"2025-11-20T09:50:26","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","title":"The 1912 Ms 7.2 earthquake in the Denali region of central Alaska","docAbstract":"The 2002 Mw 7.9 earthquake in central Alaska ruptured 340 km on three faults—Susitna Glacier thrust fault, Denali fault, Totschunda fault—crossing both the Richardson Highway and the Alaska Pipeline. Its occurrence prompted renewed interest in historical large earthquakes that possibly originated on the Denali fault. One of these earthquakes was a Ms 7.2 event on July 7, 1912, which we revisit with two approaches: (1) probabilistic relocation of the epicenter using globally recorded arrival times, and (2) compilation and reassessment of shaking intensity reports to estimate a macroseismic epicenter. Our preferred instrumental epicenter is west of the Parks Highway and in agreement with the maximum‐reported shaking, which was from the Parker–Browne expedition of Denali. We also relocated a Ms 6.4 aftershock, whose epicenter is 11 km from the mainshock. Candidate faults for the 1912 earthquake include the Denali fault, the McLeod Creek thrust fault, and the Kantishna Hills thrust fault. Future analysis of active faults, paleoseismic results, 1912 instrumental data, and 1912 felt reports may help in interpreting the fault and mechanism of the 1912 earthquake.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250150","usgsCitation":"Tape, C., Aquino-Lopez, M., Bemis, S., Haeussler, P., and Ginnaty, J., 2026, The 1912 Ms 7.2 earthquake in the Denali region of central Alaska: Bulletin of the Seismological Society of America, v. 116, no. 1, p. 322-354, https://doi.org/10.1785/0120250150.","productDescription":"33 p.","startPage":"322","endPage":"354","ipdsId":"IP-182077","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":498617,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498703,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0120250150","text":"Publisher Index Page"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.43690719365998,\n 66.58359872082357\n ],\n [\n -169.43690719365998,\n 53.57022459464301\n ],\n [\n -130.19988331357695,\n 53.57022459464301\n ],\n [\n -130.19988331357695,\n 66.58359872082357\n ],\n [\n -169.43690719365998,\n 66.58359872082357\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"116","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":953755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aquino-Lopez, Marco","contributorId":331553,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","affiliations":[],"preferred":false,"id":953756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bemis, Sean","contributorId":175460,"corporation":false,"usgs":false,"family":"Bemis","given":"Sean","affiliations":[{"id":27572,"text":"UK","active":true,"usgs":false}],"preferred":false,"id":953757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":953758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginnaty, Jessalyn","contributorId":365145,"corporation":false,"usgs":false,"family":"Ginnaty","given":"Jessalyn","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":953759,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273811,"text":"70273811 - 2026 - High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting","interactions":[],"lastModifiedDate":"2026-02-04T14:24:54.694859","indexId":"70273811","displayToPublicDate":"2025-11-04T08:30:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7571,"text":"Bulletin of Seismological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting","docAbstract":"The Minto Flats fault zone (MFFZ) in central Alaska is a left‐lateral strike‐slip fault system situated between the continental‐scale right‐lateral Denali and Kaltag‐Tintina faults. The MFFZ has the potential to generate magnitude 7 earthquakes, and it hosted a magnitude 6 earthquake in 1995. It has also produced exotic events, such as very‐low‐frequency earthquakes and nucleation signals. We use network‐matched filtering and relative earthquake relocation techniques to derive a detailed catalog of earthquake locations for the MFFZ. The catalog spans from August 2014 to December 2019, a time period including 13 temporary seismic stations in the region. Our results provide the most complete catalog for the MFFZ and include deeper events, clusters of shallow seismicity, and a complex and segmented fault structure not observed in the original regional catalog. We document right‐lateral strike‐slip faulting, conjugate to the main northeast‐striking left‐lateral faults of the MFFZ. Below Nenana basin, the relocated seismicity reveals northwest‐dipping left‐lateral faults, supporting the inference that deep crustal active faulting is associated with recent basin deformation.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250177","usgsCitation":"Sims, N.E., Tape, C., Ruppert, N., and West, M.E., 2026, High-precision earthquake catalog for Minto Flats fault zone, central Alaska, reveals complex and conjugate faulting: Bulletin of Seismological Society of America, v. 116, no. 1, p. 375-396, https://doi.org/10.1785/0120250177.","productDescription":"22 p.","startPage":"375","endPage":"396","ipdsId":"IP-182902","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Minto Flats fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.5,\n 65.2\n ],\n [\n -150,\n 65.2\n ],\n [\n -150,\n 64.2\n ],\n [\n -146.5,\n 64.2\n ],\n [\n -146.5,\n 65.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"116","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Sims, Nealey E.","contributorId":365831,"corporation":false,"usgs":false,"family":"Sims","given":"Nealey","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":954904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":954905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Natalia A. 0000-0003-0589-1159","orcid":"https://orcid.org/0000-0003-0589-1159","contributorId":351514,"corporation":false,"usgs":true,"family":"Ruppert","given":"Natalia A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":954906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"West, Michael E.","contributorId":365832,"corporation":false,"usgs":false,"family":"West","given":"Michael","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":954907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271917,"text":"70271917 - 2026 - Cumulative effects analysis to inform public land management in the United States: Key characteristics and legal challenges","interactions":[],"lastModifiedDate":"2025-09-24T15:03:03.061932","indexId":"70271917","displayToPublicDate":"2025-09-22T09:53:42","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1544,"text":"Environmental Impact Assessment Review","active":true,"publicationSubtype":{"id":10}},"title":"Cumulative effects analysis to inform public land management in the United States: Key characteristics and legal challenges","docAbstract":"Considering potential cumulative effects of proposed actions is fundamental to environmental impact analysis. However, cumulative effects analyses historically are not robust, especially for site-specific decisions. We sought to identify opportunities to strengthen cumulative effects analysis in a large United States public land management agency, the Bureau of Land Management (BLM). We asked 1) how cumulative effects analyses were legally challenged, 2) how site-specific cumulative effects analyses aligned with policy and compared to the broader-scale analyses to which they tiered, and 3) whether characteristics of cumulative effects analyses varied with category of proposed action, type of resource, or agency office. We used thematic analysis to assess litigation and appeals case documents finalized from 2010 to 2020 and a set of document analysis questions to assess National Environmental Policy Act (NEPA) analyses for BLM decisions completed prior to 2020 in Alaska and Colorado. We found that legal challenges related to cumulative effects focused on absence of cumulative effects analysis. In NEPA analyses, cumulative effects were frequently considered, but elements recommended in policy, such as citations, methods, and scope, were rarely included. These elements were present more often in the broader analyses to which site-specific analyses tiered. Many elements of cumulative effects analyses varied by proposed action and BLM office, and analyses of potential cumulative effects on air quality were consistently more detailed than for other resources. Our results suggest that many problems that historically plagued cumulative effects analysis persist. Advances in methods, training, and guidance could strengthen the defensibility of NEPA analyses.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.eiar.2025.108158","usgsCitation":"Rutherford, T.K., Hammond, T.O., Foster, A., Gilbert, M.A., Haby, T.S., Lehrter, R.J., Meineke, J., Samuel, E.M., and Carter, S.K., 2026, Cumulative effects analysis to inform public land management in the United States: Key characteristics and legal challenges: Environmental Impact Assessment Review, v. 117, 108158, 12 p., https://doi.org/10.1016/j.eiar.2025.108158.","productDescription":"108158, 12 p.","ipdsId":"IP-172121","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":496152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.eiar.2025.108158","text":"Publisher Index Page"},{"id":496008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Colorado","geographicExtents":"{\n \"type\": 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]\n}","volume":"117","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rutherford, Tait K. 0000-0003-4314-1519","orcid":"https://orcid.org/0000-0003-4314-1519","contributorId":331173,"corporation":false,"usgs":true,"family":"Rutherford","given":"Tait","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":949366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammond, Tim O.","contributorId":361749,"corporation":false,"usgs":false,"family":"Hammond","given":"Tim","middleInitial":"O.","affiliations":[{"id":86344,"text":"BLM Eastern Interior Field Office","active":true,"usgs":false}],"preferred":false,"id":949367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, Alison C. 0000-0002-6659-2120","orcid":"https://orcid.org/0000-0002-6659-2120","contributorId":331240,"corporation":false,"usgs":false,"family":"Foster","given":"Alison C.","affiliations":[{"id":79166,"text":"USGS, currently US Forest Service","active":true,"usgs":false}],"preferred":false,"id":949368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilbert, Megan A.","contributorId":361750,"corporation":false,"usgs":false,"family":"Gilbert","given":"Megan","middleInitial":"A.","affiliations":[{"id":79145,"text":"BLM Headquarters","active":true,"usgs":false}],"preferred":false,"id":949369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haby, Travis S. 0000-0003-2204-9967","orcid":"https://orcid.org/0000-0003-2204-9967","contributorId":138831,"corporation":false,"usgs":false,"family":"Haby","given":"Travis","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":949370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehrter, Richard J. 0000-0002-5760-9269","orcid":"https://orcid.org/0000-0002-5760-9269","contributorId":331176,"corporation":false,"usgs":false,"family":"Lehrter","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":79144,"text":"BLM National Operations Center (Contractor)","active":true,"usgs":false}],"preferred":false,"id":949371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meineke, Jennifer K. 0000-0002-7136-5854","orcid":"https://orcid.org/0000-0002-7136-5854","contributorId":331238,"corporation":false,"usgs":false,"family":"Meineke","given":"Jennifer K.","affiliations":[{"id":79165,"text":"USGS, currently with Colorado State University","active":true,"usgs":false}],"preferred":false,"id":949372,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Samuel, Ella M. 0000-0001-5085-7369","orcid":"https://orcid.org/0000-0001-5085-7369","contributorId":300515,"corporation":false,"usgs":true,"family":"Samuel","given":"Ella","email":"","middleInitial":"M.","affiliations":[{"id":65185,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":949373,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":949374,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273804,"text":"70273804 - 2026 - Reducing bias in shorebird nest survival rates across a large Arctic landscape","interactions":[],"lastModifiedDate":"2026-02-03T14:12:23.263322","indexId":"70273804","displayToPublicDate":"2025-09-06T15:21:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Reducing bias in shorebird nest survival rates across a large Arctic landscape","docAbstract":"Reproductive success is a key demographic parameter that can have profound impacts on a species' population trend. Indeed, poor reproductive success has been suggested as a contributing factor to the declines observed in many species of birds, including Arctic-breeding shorebirds. However, the available information on Arctic-breeding shorebird nest survival is restricted to a limited number of non-random locations where proximity to human settlements and traditional invasive monitoring techniques may artificially alter nest predation rates and, thus, bias results. To accurately assess reproductive success, unbiased estimates are needed. In this study, we monitored 96 shorebird nests (six species) at 41 randomly selected sites across a large Arctic landscape (1219 km2 area of the Arctic National Wildlife Refuge) using minimally invasive techniques (i.e. single nest visits, temperature loggers and cameras) in 2019 and 2022. Overall, daily survival was 0.975 (95% CI: 0.955–0.987), which translates to a 53% (95% CI: 32–72%) probability of a shorebird nest surviving the median (25 days) incubation period for the studied species. Camera footage indicated Arctic Foxes Vulpes lagopus were the primary nest predator (85% of identified predation events), but Parasitic Jaegers Stercorarius parasiticus and Sandhill Cranes Grus canadensis also contributed to nest loss. In both years, greater nest failure occurred in the northwest and northcentral regions of our study area, potentially the result of greater shorebird abundance and density-dependent predation rates. Nest survival rates obtained in this study were the same as those obtained in a previous large geographical study that monitored shorebird nests across numerous small, non-randomly selected, high-density shorebird field sites that employed intensive human monitoring techniques. However, site-specific and annual differences in predator and shorebird species and densities make direct comparisons to previous studies difficult. Continued monitoring using methods that minimize bias and are consistent across time are needed to accurately measure true changes in nest survival rates that may occur under a changing climate and with increased human development.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13441","usgsCitation":"Saalfeld, S.T., Weiser, E.L., Brown, S.C., Latty, C., Schulte, S., and Lanctot, R.B., 2026, Reducing bias in shorebird nest survival rates across a large Arctic landscape: Ibis, v. 168, no. 1, p. 25-41, https://doi.org/10.1111/ibi.13441.","productDescription":"17 p.","startPage":"25","endPage":"41","ipdsId":"IP-172288","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":499619,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.13441","text":"Publisher Index Page"},{"id":499416,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.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 -146.73408758739058,\n 70.27291487299507\n ],\n [\n -146.73408758739058,\n 69.58605177408464\n ],\n [\n -142.60339842266058,\n 69.58605177408464\n ],\n [\n -142.60339842266058,\n 70.27291487299507\n ],\n [\n -146.73408758739058,\n 70.27291487299507\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"168","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Saalfeld, Sarah T. 0000-0002-6837-9729","orcid":"https://orcid.org/0000-0002-6837-9729","contributorId":365825,"corporation":false,"usgs":false,"family":"Saalfeld","given":"Sarah","middleInitial":"T.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":954882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":954883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C. 0000-0002-0421-1660","orcid":"https://orcid.org/0000-0002-0421-1660","contributorId":208214,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":37764,"text":"Shorebird Recovery Program","active":true,"usgs":false}],"preferred":false,"id":954884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latty, Christopher","contributorId":341229,"corporation":false,"usgs":false,"family":"Latty","given":"Christopher","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulte, Shiloh","contributorId":354797,"corporation":false,"usgs":false,"family":"Schulte","given":"Shiloh","affiliations":[{"id":84665,"text":"Manomet Conservation Sciences","active":true,"usgs":false}],"preferred":false,"id":954886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lanctot, R. 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The igneous suite was emplaced within Upper Triassic sedimentary rocks along the southern margin of Western Wrangellia, the western-most fragment of the Wrangellia composite terrane. The igneous rocks range from mafic (50.6% SiO2) to felsic (78.3% SiO2), characteristically have less than 1.55% K2O, and generally have low trace element abundances. The tonalitic and trondhjemitic magmas were largely sourced in mafic-rich lower crust and incompletely assimilated quartz and other mineral xenocrysts are common. Fractionation involving plagioclase and amphibole is indicated for some magmas and composite intrusions and igneous xenoliths indicate magma mixing was possible. Paleozoic and Precambrian inherited zircons and initial 87Sr/86Sr (0.704103–0.705609) and 143Nd/144Nd (0.512396–0.512777) ratios indicate that the Western Wrangellia crustal sources are heterogeneous and contain sialic components. The latest Triassic magmatism reflects processes that preceded Early Jurassic subduction along the Wrangellia composite terrane and Pacific Ocean plate boundary. These processes involved heating and melting of mantle lithosphere and lower crust as mantle instabilities accompanied the breaking of the plate boundary linkages. The Late Triassic transition to subduction along the Wrangellia composite terrane margin coincided with the transition to subduction cessation in the Late Triassic arcs of the western Intermontane terranes of Canada. The shift to subduction along the outboard Wrangellia composite terrane margin marks the beginning of the Pacific Ocean–Cordillera plate interactions that came to dominate the tectonic evolution of the northern Cordillera from the Early Jurassic to today.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjes-2024-0009","usgsCitation":"Hudson, T.L., Wilson, F.H., and O’Sullivan, P., 2026, Upper Triassic igneous rocks of the southern Kenai Peninsula, Alaska – Prelude to Early Jurassic subduction along the western Wrangellia composite terrane margin: Canadian Journal of Fisheries and Aquatic Sciences, v. 61, no. 9, p. 941-965, https://doi.org/10.1139/cjes-2024-0009.","productDescription":"15 p.","startPage":"941","endPage":"965","ipdsId":"IP-161254","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":504067,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FDZG9X","text":"USGS data release","linkHelpText":"U-Pb Isotope Geochronology Data and Geochemical Analyses of Selected Rocks from the Seldovia Quadrangle, Southcentral Alaska"},{"id":502749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"southern Kenai Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.63613952005835,\n 62.54680811224148\n ],\n [\n -158.0836644356667,\n 62.54680811224148\n ],\n [\n -158.0836644356667,\n 55.29522427923976\n ],\n [\n -146.63613952005835,\n 55.29522427923976\n ],\n [\n -146.63613952005835,\n 62.54680811224148\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Travis L. 0000-0003-1588-2280","orcid":"https://orcid.org/0000-0003-1588-2280","contributorId":329722,"corporation":false,"usgs":false,"family":"Hudson","given":"Travis","email":"","middleInitial":"L.","affiliations":[{"id":78701,"text":"Applied Geology, Inc.","active":true,"usgs":false}],"preferred":false,"id":959256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Frederic H. 0000-0003-1761-6437 fwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1761-6437","contributorId":67174,"corporation":false,"usgs":true,"family":"Wilson","given":"Frederic","email":"fwilson@usgs.gov","middleInitial":"H.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":959257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":959258,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273761,"text":"70273761 - 2025 - A laboratory-based spectrometer intercomparison for the measurement of snow spectra","interactions":[],"lastModifiedDate":"2026-01-28T15:54:55.650048","indexId":"70273761","displayToPublicDate":"2025-12-22T08:48:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1264,"text":"Cold Regions Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"A laboratory-based spectrometer intercomparison for the measurement of snow spectra","docAbstract":"Seasonal snow is an integral component of global hydrological systems, global energy budget and Earth's climate. As an important part of many Earth systems, seasonal snow is also an essential source of water for many human populations and ecosystems around the world. As such, the measurement of seasonal snow and characterization of uncertainty in those measurements is crucial. To elucidate potential uncertainty attributable to commonly used field spectrometers (and to a lesser extent imaging spectrometers) and associated reference panels, this work presents results from an intercalibration experiment conducted synchronously with the NASA 2023 Snow Experiment (SnowEx) Albedo campaign near Fairbanks, Alaska USA. Three sets of experiments were carried out under controlled laboratory conditions to characterize the radiometric and spectral wavelength consistency of the instruments as well as the white reference panels used to calculate reflectance from field measurements. Although there was generally good agreement between the instruments, panels, and the references, there were also some notable differences. One instrument showed an average − 74 % change from the reference for radiance, and multiple instruments exceeded the suggested 0.5 nm threshold for spectral wavelength scale. The Discussion section highlights how some of these findings and their implications could improve future field campaigns and general use/maintenance of these high-precision scientific instruments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coldregions.2025.104800","usgsCitation":"Roberts-Pierel, B.M., Crawford, C., Brown, S.W., Kokaly, R.F., Gleason, K.E., Nolin, A.W., Bair, E.H., Wilder, B.A., Surunis, A.J., Skiles, S.K., Meyer, J., Fitts, A.E., Johnston, J.M., Hunsaker, A.G., Steufer, M., and Løke, T., 2025, A laboratory-based spectrometer intercomparison for the measurement of snow spectra: Cold Regions Science and Technology, v. 245, 104800, 16 p., https://doi.org/10.1016/j.coldregions.2025.104800.","productDescription":"104800, 16 p.","ipdsId":"IP-182042","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499970,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pdxscholar.library.pdx.edu/esm_fac/430","text":"External Repository"},{"id":499172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.93176636317207,\n 64.88847731461294\n ],\n [\n -147.93176636317207,\n 64.76084697844067\n ],\n [\n -147.5919038491945,\n 64.76084697844067\n ],\n [\n -147.5919038491945,\n 64.88847731461294\n ],\n [\n -147.93176636317207,\n 64.88847731461294\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts-Pierel, Benjamin M. 0000-0002-1486-7903","orcid":"https://orcid.org/0000-0002-1486-7903","contributorId":365679,"corporation":false,"usgs":false,"family":"Roberts-Pierel","given":"Benjamin","middleInitial":"M.","affiliations":[{"id":87187,"text":"Earth Space Technology Service","active":true,"usgs":false}],"preferred":false,"id":954604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":954605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Steven W.","contributorId":365680,"corporation":false,"usgs":false,"family":"Brown","given":"Steven","middleInitial":"W.","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":954606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":954607,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gleason, Kelly E.","contributorId":365681,"corporation":false,"usgs":false,"family":"Gleason","given":"Kelly","middleInitial":"E.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":954608,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nolin, Anne W.","contributorId":365682,"corporation":false,"usgs":false,"family":"Nolin","given":"Anne","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":954609,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bair, Edward H.","contributorId":365683,"corporation":false,"usgs":false,"family":"Bair","given":"Edward","middleInitial":"H.","affiliations":[{"id":87188,"text":"Leidos, Inc.","active":true,"usgs":false}],"preferred":false,"id":954610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilder, Brenton A.","contributorId":365684,"corporation":false,"usgs":false,"family":"Wilder","given":"Brenton","middleInitial":"A.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":954611,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Surunis, Anton J.","contributorId":365685,"corporation":false,"usgs":false,"family":"Surunis","given":"Anton","middleInitial":"J.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":954612,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Skiles, S. 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Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas:
The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Monitoring the extent of surface water features (hydrography), accurately storing them in databases, and representing them on topographic maps are essential for various applications such as navigation and policy-making for legislative boundaries and permitting. In this context, hydrographic data includes features that generally have water present or image data showing signs that water is forming a terrain channel, and which would be included in 1:24,000 or larger scale topographic maps. In addition, reliable hydrographic data play a critical role to help manage environmental risks such as droughts, floods, fires, and landslides, as well as monitoring biological resources and pollutants. Inaccuracies in hydrography data can lead to modelling inaccuracies, resulting in economic, social, and environmental risks. However, generating sufficiently accurate high-resolution (HR) hydrography and terrain data for these purposes remains a substantial challenge primarily because of complex surface water dynamics and data handling limitations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Abstracts of the International Cartographic Association","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Cartographic Association","doi":"10.5194/ica-abs-10-275-2025","usgsCitation":"Stanislawski, L., Qin, R., Liu, J., Shavers, E.J., Wang, S., Jaroenchai, N., and Thiem, P.T., 2025, Multi-temporal surface water mapping with high-resolution elevation and image data through weakly supervised deep learning, in Abstracts of the International Cartographic Association, v. 7, no. 10, 275, 3 p., https://doi.org/10.5194/ica-abs-10-275-2025.","productDescription":"275, 3 p.","ipdsId":"IP-179538","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":498917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ica-abs-10-275-2025","text":"Publisher Index Page"},{"id":498745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"7","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qin, Rongjun","contributorId":333939,"corporation":false,"usgs":false,"family":"Qin","given":"Rongjun","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":947788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jung-Kuan 0000-0001-8461-8200","orcid":"https://orcid.org/0000-0001-8461-8200","contributorId":333940,"corporation":false,"usgs":true,"family":"Liu","given":"Jung-Kuan","email":"","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":947791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":947792,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":947793,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70275053,"text":"70275053 - 2025 - Hair growth rate estimation in North American ursids","interactions":[],"lastModifiedDate":"2026-04-13T16:00:00.480605","indexId":"70275053","displayToPublicDate":"2025-12-11T08:51:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Hair growth rate estimation in North American ursids","docAbstract":"The feeding ecology of wildlife populations has important implications for individual health, population productivity and distribution patterns. For ursids (bears), food resources and feeding behaviour primarily affect population dynamics via effects on cub production and survival. Much of what is known about the feeding ecology of bears is based on analyses of tissues collected from capture-based research efforts, harvested animals or non-invasive approaches. However, inference about diet from hair has been limited by a lack of quantitative data on the timing of the moult and hair growth rates. We conducted a study to develop and test two methods of quantifying hair growth rates of three species in the family Ursidae (n = 1 polar bear, Ursus maritimus; n = 3 black bears, Ursus americanus; n = 3 grizzly bears, Ursus arctos horribilis). We implemented visual and biochemical approaches, proven safe for humans and other mammals, in a zoo setting. These methods relied on voluntary bear behaviours trained using positive reinforcement. The two methods were: (i) applying a small patch of hair dye (or bleach) on the rump or foreleg, and (ii) feeding an isotopically labelled amino acid (glycine) capsule that ‘marks’ time at a particular location as it is incorporated within the hair. We collected hair at regular intervals (every 1–2 weeks) for five months from body locations on the bear consistent with commonly sampled collection points in wild-caught bears. We found that both methods effectively identified periods of hair growth and detected individual and seasonal variation in hair growth rates. Average guard hair growth rates ranged between 0.10 and 1.05 mm day−1 across the three species. This study provides the first step for developing a foundation for incorporating seasonality in wild-collected bear hair samples by assessing growth over an annual cycle.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coaf075","usgsCitation":"Stern, J.H., Rode, K.D., Stricker, C.A., Ploof, S., Roberts, C.L., Edinger, C., Humbyrd, M., Wagner, N., Owen, M.A., Whiteman, J.P., Bechshoft, T., White, B., and Laidre, K.L., 2025, Hair growth rate estimation in North American ursids: Conservation Physiology, v. 13, no. 1, coaf075, 14 p., https://doi.org/10.1093/conphys/coaf075.","productDescription":"coaf075, 14 p.","ipdsId":"IP-170567","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":503003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaf075","text":"Publisher Index Page"},{"id":502752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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However, not including end-users, especially decision-makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision-making. While the ESM community increasingly values broad community engagement, end-users may not initially perceive models as useful for local planning. Co-designing models with end-users fosters two-way learning: users better understand models and their outputs, while modelers gain insights into fine-scale local processes like monitoring practices and management priorities. Higher-level co-design can lead to more customized, priority-driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co-design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision-makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high-resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land-atmosphere models. In the Mid-Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four-level framework: (a) Co-design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co-develop New Model Functions. We aim to help researchers consider and compare co-design across diverse modeling projects systematically and coherently.
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2025 - Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds","interactions":[],"lastModifiedDate":"2025-12-09T14:17:39.30669","indexId":"70272740","displayToPublicDate":"2025-12-04T07:52:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds","docAbstract":"Animal-borne trackers are commonly used to study bird movements, including in long-distance migrants such as shorebirds. Selecting a tracker and attachment method can be daunting, and methodological advancements often have been made by trial and error and conveyed by word of mouth. We synthesized tracking outcomes across 2745 dorsally mounted trackers on 37 shorebird species around the world. We evaluated how attachment method, power source, data retrieval method, relative tracker mass, and biological traits affected success, where success was defined as whether or not each tag deployment reached its expected tracking duration (i.e. all aspects succeeded for the intended duration of the study: attachment, tracking, data acquisition, and bird survival). We conducted separate analyses for tag deployments with remote data retrieval (‘remote-upload tag deployments') and those that archived data and had to be recovered (‘archival tag deployments'). Among remote-upload tag deployments, those that were a lighter mass relative to the bird, were beyond their first year of production, transmitted data via satellite, or were attached with a leg-loop harness were most often successful at reaching their expected tracking duration. Archival tag deployments were most successful when applied at breeding areas, or when applied to males in any season. Remote-upload tag deployments with solar power, satellite data retrieval, or leg-loop harnesses continued tracking for longer than those with battery power, other types of data retrieval, or glue attachments. However, the majority of tag deployments failed to reach their expected tracking duration (71% of remote-upload, 83% of archival), which could have been due to tracker failure, attachment failure, or bird mortality. Our findings highlight that many tag deployments may fail to meet the goals of a study if tracking duration is crucial. Using our results, we provide guidelines for selecting a tracker and attachment to improve success at meeting study goals.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/jav.03487","usgsCitation":"Weiser, E.L., Lanctot, R., Ruthrauff, D.R., Saalfeld, S.T., Tibbitts, L., Abad-Gómez, J., Aldabe, J., de Almeida, J.B., Alves, J., Anderson, G., Battley, P.F., Belting, H., Bêty, J., Bianchini, K., Bishop, M.A., Bom, R.A., Bowgen, K., Brown, G.S., Brown, S.C., Bugoni, L., Burton, N., Bybee, D.R., Carneiro, C., Castresana, G., Chan, Y., Choi, C., Christie, K., Clark, N., Conklin, J.R., Cruz-López, M., Dinsmore, S., Dodd, S., Douglas, D., Eberhart-Hertel, L., English, W.B., Ewing, H., Faria, F.A., Franks, S.E., Fuller, R., Gill, R., Giroux, M., Gratto-Trevor, C.L., Green, D., Green, R.E., Green, R., Gunnarsson, T., Gutiérrez, J.S., Harrison, A., Hartman, C.A., Hassell, C., Hoepfner, S., Hooijmeijer, J.C., Johnson, J., Johnson, O.W., Kempenaers, B., Klaassen, M., Kok, E., Krietsch, J., Küpper, C., Kwarteng, A., Kwon, E., Lamarre, J., Latty, C., Lecomte, N., Loonstra, A., Ma, Z., Mander, L., Marlow, C., Marra, P., Masero, J.A., McDuffie, L.A., McGuire, R., Melter, J., Melville, D.S., Méndez, V., Michels, T., Morrissey, C., Mu, T., Newstead, D., Page, G., Pierce, A.K., Piersma, T., Repenning, M., Robinson, B.H., Rocha, A., Rogers, D.I., Scarpignato, A., Schulte, S., Scragg, E., Senner, N.R., Smith, P., Taylor, A.R., Taylor, R.C., Þórisson, B., Valcu, M., Verhoeven, M.A., Ware, L., Warnock, N., Weber, M., Wright, L., and Wunder, M.B., 2025, Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds: Journal of Avian Biology, v. 2025, no. 6, e03487, 20 p., https://doi.org/10.1002/jav.03487.","productDescription":"e03487, 20 p.","ipdsId":"IP-176997","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":497394,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jav.03487","text":"Publisher 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sediment delivery to the Arctic Ocean. On Alaska's Arctic coastal plain, rivers begin flowing during snowmelt in late spring while extensive river ice persists in channels, such that hydraulics are altered and water is kept cool. The effects of river ice on permafrost bank erosion are poorly understood, primarily due to a dearth of field observations and a lack of river ice in existing models.
To address this knowledge gap, we developed a numerical model to simulate the melt of substrate interstitial ice and bank collapse along individual permafrost river banks. We parameterize the model with field observations from riverbanks in three different channels on the Canning River delta, which are disparately impacted by river ice during snowmelt. We explore the bank erosion produced without river ice in the model and with modern river ice model scenarios that we drive with different stages and water temperature boundary conditions. We also compare predicted erosion rates to observations from satellite imagery to validate this approach.
In the model, banks are idealized as vertical profiles that rise 1–2 m above the river bed and are comprised of silt- to sand-sized sediment with dense roots in the active layer. Underneath, we generalize bank ice content underneath the active layer to represent ice-rich permafrost on the river corridor boundaries. The model predicts that these ice-rich river banks can erode by 2–6 m/yr. Scenarios without ice underpredict erosion in the distributary channels. Scenarios with varying river ice for different deltaic channels produce erosion rates similar to observations.
Our results suggest that the prolonged melt of thick river ice in a delta nonlinearly impacts permafrost bank erosion by blocking river discharge to certain branches, heightening stage across the distributary network and locally limiting river water warming. Given expected changes in air temperature and hydrology, future estimates of Arctic river bank erosion could be improved by considering river ice.
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