From 2019 to 2024, gravity surveys were conducted at the Three Sisters volcanic cluster (TSVC), measuring 246 gravity sites using a spring relative gravimeter. We calculated the residual Bouguer anomaly and identified three main zones with negative anomalies, ranging from −4 to −8 mGal, located southwest and west of South Sister, within an area that has been uplifting for the past two decades. After inversion, we obtain a 3D density model of the subsurface and identify low-density bodies extending from the surface down to 3 km. We estimate a total of 15 km3 of crustal bodies with density close to 2 g/cm3 that could store up to ~5 km3 of water, forming an extensive hydrothermal system beneath the TSVC. We explore the possible combinations of melt compositions and temperatures that could create a bulk density close to our reference crustal density (2.5 g/cm3) using MELTS thermodynamic simulations. Our results indicate that a magmatic mush with as little as 15% partial melt of bulk rhyolitic composition or as much as 52%–57% partial melt of a bulk dacitic composition could be stored in a magmatic system under TSVC without generating a detectable gravity anomaly. Episodic magma injections at the base of the magmatic system, such as the 1998–2000 intrusion at ~6 km depth, would bring heat and gas to the hydrothermal system while maintaining a low melt fraction in the magmatic mush, as imaged at other Cascade volcanoes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB031886","usgsCitation":"Le Mevel, H., Andersen, N.L., Dechert, A.E., and Dufek, J., 2026, The magmatic-hydrothermal system of the Three Sisters volcanic cluster, Oregon, imaged from field gravity measurements: JGR Solid Earth, v. 131, no. 1, e2025JB031886, 16 p., https://doi.org/10.1029/2025JB031886.","productDescription":"e2025JB031886, 16 p.","ipdsId":"IP-178279","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":498736,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Three Sisters volcanic cluster","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.85498844236317,\n 44.16602505212751\n ],\n [\n -121.85498844236317,\n 44.00814911568179\n ],\n [\n -121.67001872468549,\n 44.00814911568179\n ],\n [\n -121.67001872468549,\n 44.16602505212751\n ],\n [\n -121.85498844236317,\n 44.16602505212751\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"131","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Le Mevel, Helene","contributorId":345674,"corporation":false,"usgs":false,"family":"Le Mevel","given":"Helene","affiliations":[{"id":82691,"text":"Carnegie Institution for Science, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":953897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Nathan Lee 0000-0002-4152-4914","orcid":"https://orcid.org/0000-0002-4152-4914","contributorId":345693,"corporation":false,"usgs":true,"family":"Andersen","given":"Nathan","email":"","middleInitial":"Lee","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":953898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dechert, Annika E.","contributorId":365193,"corporation":false,"usgs":false,"family":"Dechert","given":"Annika","middleInitial":"E.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":953899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufek, Josef","contributorId":365194,"corporation":false,"usgs":false,"family":"Dufek","given":"Josef","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":953900,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273737,"text":"70273737 - 2026 - Bird predation obscures detection of acoustic telemetry tags in fish","interactions":[],"lastModifiedDate":"2026-01-28T14:12:36.171101","indexId":"70273737","displayToPublicDate":"2026-01-13T10:58:23","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Bird predation obscures detection of acoustic telemetry tags in fish","docAbstract":"Increasing application of acoustic telemetry for determining survival, migration and habitat use of fishes highlights the need to improve interpretation of tracks that end abruptly: when is fishing mortality, predation, or some other cause to be inferred? Significant technological advances have led to the development of tags that “sense” predation and can be used to infer information about the type of predator that consumed the tagged fish. However, growing evidence suggests that bird predation is not effectively quantified by the technology. We hypothesized that reduction in sound transmission from acoustic tags in the gut of a bird combined with short bird diving intervals would eliminate detections of acoustic telemetry tags from the surface and severely reduce detection efficiency at depth. We test this hypothesis indirectly with two experiments using cormorant carcasses containing tagged fish in which carcasses were either tethered to a mooring for several hours or lowered through the water to simulate diving behavior. Detection of tagged prey fish in the gut of bird carcasses was severely reduced or negated completely, supporting our hypothesis. By comparison, as expected, tagged fish that were not in the gut of bird carcasses were detected at a higher frequency. Depth and distance to passive moored receivers also affected detection probability of tagged fish with more detections at depth and when closer to the receiver. Our results emphasized the importance of accounting for avian predation of tagged fish in studies of prey species in surface waters. Further, while recent development of predation sensing tags has illustrated a few examples of bird predation, our results demonstrate that determining that a tagged fish has been consumed by a diving bird will be difficult and will likely require alternative methods or technologies.
","language":"English","publisher":"Springer","doi":"10.1186/s40317-025-00441-1","usgsCitation":"Kraus, R., Roberts, J., Dufour, M.R., and Branden E. Kohler, 2026, Bird predation obscures detection of acoustic telemetry tags in fish: Animal Biotelemetry, v. 14, 2, 9 p., https://doi.org/10.1186/s40317-025-00441-1.","productDescription":"2, 9 p.","ipdsId":"IP-177144","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499319,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-025-00441-1","text":"Publisher Index Page"},{"id":499098,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2026-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":954487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":954489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Branden E. Kohler","contributorId":365630,"corporation":false,"usgs":false,"family":"Branden E. Kohler","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":954490,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273656,"text":"70273656 - 2026 - Plasticity in the reproductive biology of Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake following lake trout Salvelinus namaycush invasion","interactions":[],"lastModifiedDate":"2026-01-22T15:47:50.9445","indexId":"70273656","displayToPublicDate":"2026-01-13T09:43:23","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"Plasticity in the reproductive biology of Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake following lake trout Salvelinus namaycush invasion","docAbstract":"Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake are the focus of intensive conservation efforts due to the threat of predation by invasive lake trout Salvelinus namaycush. Suppression gillnetting has reduced the abundance of predatory lake trout, and the Yellowstone cutthroat trout population is recovering. Long-term monitoring indicates the size structure of the population shifted following lake trout invasion, suggesting that reproductive demographic rates of Yellowstone cutthroat trout may have changed. Length at 50% probability of maturity, as assessed using histological analysis of gonadal tissue, was 479 mm (95% confidence interval [CI] 467–490 mm) for females and 406 mm (95% CI 386–430 mm) for males, compared to 330 mm for males and females historically. Currently, age at 50% probability of maturity is 6.6 for females and 5.4 for males. The rate of skipped spawning was 3% for females and 38% for males. Mean absolute fecundity was 2897 ovarian follicles/individual at present compared to 1141 ovarian follicles/individual before lake trout invasion. Mean relative fecundity was 2157 ovarian follicles/kg. This research illustrates the plasticity in the reproductive strategies of fishes as a result of an invasive species. Understanding the reproductive biology of fish populations is vital for effective fisheries management, and these results are integral to a population model that can be used to develop new conservation benchmarks for Yellowstone cutthroat trout.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.70281","collaboration":"National Park Service","usgsCitation":"Briggs, M.A., Webb, M.A., Guy, C.S., and Koel, T.M., 2026, Plasticity in the reproductive biology of Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake following lake trout Salvelinus namaycush invasion: Journal of Fish Biology, https://doi.org/10.1111/jfb.70281.","ipdsId":"IP-179605","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfb.70281","text":"Publisher Index Page"},{"id":498841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.60702393614453,\n 44.5900031594889\n ],\n [\n -110.60702393614453,\n 44.26482350324392\n ],\n [\n -110.15041501501246,\n 44.26482350324392\n ],\n [\n -110.15041501501246,\n 44.5900031594889\n ],\n [\n -110.60702393614453,\n 44.5900031594889\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Michelle A.","contributorId":365353,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle","middleInitial":"A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":954197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Molly A.","contributorId":365354,"corporation":false,"usgs":false,"family":"Webb","given":"Molly","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":954199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koel, Todd M.","contributorId":365355,"corporation":false,"usgs":false,"family":"Koel","given":"Todd","middleInitial":"M.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":954200,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273487,"text":"70273487 - 2026 - Annual grass invasion is transforming the sagebrush biome’s songbird communities","interactions":[],"lastModifiedDate":"2026-03-11T16:45:32.310709","indexId":"70273487","displayToPublicDate":"2026-01-13T09:08:54","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Annual grass invasion is transforming the sagebrush biome’s songbird communities","docAbstract":"Novel stressors like climate change and biological invasions alter ecological communities, resulting in changes to ecosystem services and biodiversity (that is, ecological transformation). Most ecological transformation research focuses on plants, but animals are likely affected by and plausibly mediate the extent, impact, and pace of transformations. In western North America, where invasive annual grasses are transforming sagebrush-steppe ecosystems, we quantified how transformation in vegetation drives songbird community change. We hypothesized that transformation of vegetation communities via invasion alters wildlife communities by favoring generalists over specialists, albeit with extinction debts that may temporarily obscure transformations’ consequences. Although local-scale songbird diversity increased with grass invasion, we found that this shift was accompanied by ongoing reorganization of songbird communities at larger scales (across the sagebrush biome), driven by heterogeneous impacts of invasion among species and guilds. Through our biome-wide analysis, we were also able to identify high-priority regions for conservation of sensitive songbird species. Our research provides evidence that wildlife communities are transforming alongside vegetation communities and offers insight into the approaches required to quantify nascent community turnover.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.70024","usgsCitation":"Hobart, B.K., Moss, W.E., Cook, M.C., Nagy, R.C., and McKenzie, V.J., 2026, Annual grass invasion is transforming the sagebrush biome’s songbird communities: Frontiers in Ecology and the Environment, e70024, 8 p., https://doi.org/10.1002/fee.70024.","productDescription":"e70024, 8 p.","ipdsId":"IP-167644","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":500971,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70273487/images"},{"id":498923,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.70024","text":"Publisher Index Page"},{"id":498783,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70273487/70273487.XML"},{"id":498784,"rank":3,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70273487/full"},{"id":498780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.21700235279832,\n 49.461365022778125\n ],\n [\n -121.21700235279832,\n 36.16184720583651\n ],\n [\n -100.67035958615037,\n 36.16184720583651\n ],\n [\n -100.67035958615037,\n 49.461365022778125\n ],\n [\n -121.21700235279832,\n 49.461365022778125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hobart, Brendan K.","contributorId":338335,"corporation":false,"usgs":false,"family":"Hobart","given":"Brendan","middleInitial":"K.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":953910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moss, Wynne Emily 0000-0002-2813-1710","orcid":"https://orcid.org/0000-0002-2813-1710","contributorId":338331,"corporation":false,"usgs":true,"family":"Moss","given":"Wynne","email":"","middleInitial":"Emily","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":953911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Max C","contributorId":365201,"corporation":false,"usgs":false,"family":"Cook","given":"Max","middleInitial":"C","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":953912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagy, R. 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Building from a high-resolution conterminous United States (CONUS) hydrography network dataset, we quantified the spatial extent, density, and upstream catchment characteristics of headwater stream segments across the CONUS. We identified approximately 8.4 million kilometers of headwater streams, finding that 77% of the total stream network consists of headwaters, nearly double the total length represented in prior estimates. Stream density varied fivefold across regions, from < 1 km·km−2 in arid basins to > 5 km·km−2 in humid, forested areas. Over 73% of the CONUS landmass drains from headwater streams. The majority of headwater stream length occurred in forested and cultivated catchments across the CONUS, while substantial regional differences were evident for headwater stream distribution in other land cover classes (for example, wetlands, urban areas, shrublands, and herbaceous-dominated catchments). The dedicated and novel geospatial dataset, HELiOS (HEadwater streams and Low-Order Systems) is introduced for management and research use. The HELiOS dataset provides the first continental-scale, high-resolution characterization of headwater streams, offering new insights and opportunities for hydrologic modeling, ecological assessments, and environmental policy.
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Current knowledge gaps hinder recovery planning but are challenging to redress through direct observation of rare interactions in the field.
We used genetic metabarcoding to characterize the taxonomic composition of pollen collected by B. affinis workers in the Appalachian mountains of Virginia and West Virginia from 2021–2023. We developed a custom sequence database of the regional flora and compared results for two independent genetic loci, internal transcribed spacer 1 and internal transcribed spacer 2 (ITS1 and ITS2).
While ITS2 consistently detected more plant diversity, results from the two loci were broadly concordant with a few notable exceptions. The plant genera Hydrangea, Actaea, Rhododendron, Tilia, and (unexpectedly) Laportea were prominent in midsummer samples, with Rubus a consistent contributor in late spring and early summer. Pea flowers (family Fabaceae) were relatively infrequent but the genera Securigera and Trifolium were detected before the Hydrangea bloom and again in late summer afterwards. The diversity of forage plants was highest in late summer, driven primarily by various genera of Asteraceae. Comparing the current data with previous work indicates regional differentiation in forage plants between Appalachia and the upper Midwest, but also allows ‘consensus’ forage sources that are supported by multiple lines of evidence and shared between regions to be tabulated. These results should help managers focus survey efforts for this endangered species and plan habitat enhancements.
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freshwater bathymetry","docAbstract":"We provide an overview of an uncrewed aircraft system (UAS)-based software-defined radar (SDRadar) system for high-resolution geophysical observations. The radar transceiver is implemented on a Radio Frequency System-on-Chip (RFSoC) platform, along with an ultra-wideband Vivaldi antenna that has a starting operating frequency of 150 MHz, enabling the system to be used across different applications, including measurements of freshwater bathymetry. In addition to system design and subsystem performance assessments, this paper presents the results of field testing conducted along the Sacramento River near Glenn, California, USA. The radar-derived river depth measurements are compared with ground truth data collected from a crewed boat using an acoustic Doppler current profiler (ADCP). The results show good agreement, with a root mean square error (RMSE) of 0.079 m.
","language":"English","publisher":"IEEE Xplore","doi":"10.1109/TAP.2025.3642394","usgsCitation":"Eskandari, S., Melebari, A., Kinzel, P.J., Lotspeich, R.R., Eggleston, J., and Moghaddam, M., 2026, Development and field testing of a UAS-based-software-defined radar for measuring freshwater bathymetry: IEEE Transactions on Antennas and Propagation, 12 p., https://doi.org/10.1109/TAP.2025.3642394.","productDescription":"12 p.","ipdsId":"IP-175859","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":498712,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/tap.2025.3642394","text":"Publisher Index Page"},{"id":498805,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QQEJV7","text":"USGS data release","linkHelpText":"In situ measurements of water depth collected with acoustic Doppler current profilers and remotely sensed depths acquired with a software-defined radar deployed from an uncrewed aircraft system, Sacramento River, California, September 18-19, 2024"},{"id":498649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Glenn","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.01693399490816,\n 39.56351114246104\n ],\n [\n -122.01693399490816,\n 39.407688010111286\n ],\n [\n -121.97927648853752,\n 39.407688010111286\n ],\n [\n -121.97927648853752,\n 39.56351114246104\n ],\n [\n -122.01693399490816,\n 39.56351114246104\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eskandari, Sepehr 0000-0003-2831-6288","orcid":"https://orcid.org/0000-0003-2831-6288","contributorId":357310,"corporation":false,"usgs":false,"family":"Eskandari","given":"Sepehr","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":953837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melebari, Asem 0000-0001-6040-3977","orcid":"https://orcid.org/0000-0001-6040-3977","contributorId":357311,"corporation":false,"usgs":false,"family":"Melebari","given":"Asem","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":953838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":5044,"text":"National Research Program - 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Arlington","active":true,"usgs":false}],"preferred":false,"id":953818,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273800,"text":"70273800 - 2026 - An entropic explanation for Gutenberg-Richter scaling","interactions":[],"lastModifiedDate":"2026-02-02T20:26:15.963383","indexId":"70273800","displayToPublicDate":"2026-01-10T08:43:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"An entropic explanation for Gutenberg-Richter scaling","docAbstract":"We develop a simple explanation for Gutenberg-Richter (G-R) size scaling of earthquakes on a single fault. We discretize the fault and consider all possible contiguous ruptures at that level of discretization. In this static model, we assume that slip scales with rupture length, and that the rupture rates at each point along the fault are consistent with an a priori long-term slip rate. These simple assumptions define an (under-determined) non-negative least-squares inverse problem. Each solution to this inverse problem is a set of earthquake rates that matches the slip-rate constraint. We use a Markov Chain Monte Carlo (MCMC) algorithm to uniformly sample the solution space assuming constant slip rates along the fault. At finer discretizations, deviations from G-R behavior decrease, which is consistent with an entropic pressure towards G-R solutions. When the fault is discretized into 10 or more segments, random solutions found by the MCMC algorithm have G-R size scaling, even though there are trivial solutions that, for example, have earthquakes of only one size. This is because there are simply far more solutions that have G-R scaling; as the problem size increases, the strong degeneracy of GR solutions results in other solutions becoming improbably rare. Also, the entropically favored G-R distribution has a b-value of approximately 1, which agrees with measured b-values in real earthquake catalogs.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB032719","usgsCitation":"Page, M.T., and Field, E.H., 2026, An entropic explanation for Gutenberg-Richter scaling: JGR Solid Earth, v. 131, no. 1, e2025JB032719, 10 p., https://doi.org/10.1029/2025JB032719.","productDescription":"e2025JB032719, 10 p.","ipdsId":"IP-176974","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":954864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":954865,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273372,"text":"sir20255105 - 2026 - Evaluation of water quality in the Langford Valley–Irwin Groundwater Subbasin, Fort Irwin National Training Center, California, 1993–2019","interactions":[],"lastModifiedDate":"2026-04-13T22:47:36.833451","indexId":"sir20255105","displayToPublicDate":"2026-01-09T11:50:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5105","displayTitle":"Evaluation of Water Quality in the Langford Valley–Irwin Groundwater Subbasin, Fort Irwin National Training Center, California, 1993–2019","title":"Evaluation of water quality in the Langford Valley–Irwin Groundwater Subbasin, Fort Irwin National Training Center, California, 1993–2019","docAbstract":"The U.S. Army Fort Irwin National Training Center (NTC), 120 miles northeast of Los Angeles in the Mojave Desert of California, obtains its potable water supply from the Bicycle Valley and Langford Valley groundwater basins; Langford Valley groundwater basin is further subdivided into the Langford Well Lake and Irwin groundwater subbasins. The Irwin groundwater subbasin contains younger, unconsolidated deposits that have a saturated thickness of as much as 200 feet (ft) and a lower aquifer within older unconsolidated deposits as thick as 650 ft. Groundwater recharge under predevelopment conditions (before 1941) occurred primarily from infiltration of intermittent streamflow in small washes that cross the Irwin groundwater subbasin. Since that time, groundwater recharge has increased because of growth of the NTC in recent years and as a result of other processes, including (1) infiltration of treated wastewater into the aquifer through ponds near the NTC wastewater treatment facility (WWTF) and (2) infiltration of imported water and treated wastewater used for landscape irrigation at base housing and athletic fields.
Water samples were collected from 17 wells and analyzed for field parameters, chemical constituents, and isotope composition in the Irwin groundwater subbasin between 2014 and 2019. These data were supplemented with water-chemistry data collected during 1993–95 and at other times if available. Between 1993–95 and 2015–19, median dissolved solids and nitrate concentrations in water from wells in the Irwin groundwater subbasin increased from 620 to 1,030 milligrams per liter (mg/L) and from 2.8 to 4.5 mg/L as nitrogen, respectively. After 2014, dissolved solids and nitrate concentrations in water from wells near the NTC WWTF decreased as a result of changes in source water quality attributable to reverse osmosis of treated drinking water delivered within the Irwin groundwater subbasin and to increased levels of treatment at the NTC WWTF. Based on delta oxygen-18 and delta deuterium isotope data, increases in dissolved solids concentrations in water from most wells were consistent with evaporation prior to recharge and mobilization of soluble salts from the unsaturated zone. Arsenic and fluoride concentrations in water from wells decreased between 1993–95 and 2015–19 as the basin filled with treated wastewater, but 2015–19 concentrations generally exceeded the California State Water Resources Control Board maximum contaminant levels of 10 micrograms per liter for arsenic and 2 mg/L for fluoride. Most groundwater in the Irwin groundwater subbasin has unadjusted carbon-14 ages ranging from 18,400 to 12,350 years before present. However, water from well 10E3, located along the wash near the subbasin outflow in the southeastern part of the Irwin groundwater subbasin, contained measurable tritium, which is consistent with infiltration of intermittent streamflow and groundwater recharge from the wash after 1952. Chemical and isotopic data indicate that treated wastewater is present in water from most wells in the upper aquifer that underlies the Irwin groundwater subbasin. Wells were not sampled to adequately determine the extent of treated wastewater and changes in water quality within the lower aquifer that underlies the Irwin groundwater subbasin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255105","collaboration":"Prepared in cooperation with the U.S. Army Fort Irwin National Training Center","programNote":"Water Resources Mission Area—Water Availability and Use Science Program","usgsCitation":"Densmore, J.N., Izbicki, J.A., Dick, M.C., and Bond, S., 2026, Evaluation of water quality in the Langford Valley–Irwin Groundwater Subbasin, Fort Irwin National Training Center, California, 1993–2019: U.S. Geological Survey Scientific Investigations Report 2025–5105, 45 p., https://doi.org/10.3133/sir20255105.","productDescription":"Report: x, 45 p.; Data Release","numberOfPages":"45","onlineOnly":"Y","ipdsId":"IP-119450","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":498846,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119155.htm","linkFileType":{"id":5,"text":"html"}},{"id":498463,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HQ9C4W","text":"USGS data release","linkHelpText":"Water-quality data for treated drinking water and treated wastewater effluent at Fort Irwin National Training Center"},{"id":498462,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5105/images"},{"id":498458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5105/coverthb.jpg"},{"id":498459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5105/sir20255105.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5105 PDF"},{"id":498460,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255105/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5105 HTML"},{"id":498461,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5105/sir20255105.XML","description":"SIR 2025-5105 XML"}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin National Training Center, Langford Valley–Irwin Groundwater Subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.8892991637174,\n 35.417534498160876\n ],\n [\n -116.8892991637174,\n 35.081465765359056\n ],\n [\n -116.43900695086751,\n 35.081465765359056\n ],\n [\n -116.43900695086751,\n 35.417534498160876\n ],\n [\n -116.8892991637174,\n 35.417534498160876\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Building on a geology-based assessment of undiscovered, technically recoverable hydrocarbon resources within the Haynesville Formation, the U.S. Geological Survey estimated the water and proppant necessary for development of the remaining resources associated with the Haynesville Sabine Uplift Continuous Gas Assessment Unit. Additionally, projections have been made on the volume of wastewater expected as a byproduct of possible future development. This fact sheet presents an overview of the methodology, along with the inputs and results of the Haynesville water and proppant assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253053","usgsCitation":"Gardner, R., Flaum, J.A., Haines, S.S., Birdwell, J.E., Kinney, S.A., Varela, B., French, K.L., Pitman, J.K., Paxton, S.T., Mercier, T.J., Schenk, C.J., Leathers-Miller, H.M., and Shook, H.D., 2026, Assessment of water and proppant quantities associated with hydrocarbon production from the Haynesville Formation within the onshore United States and State waters of the Gulf Coast Basin, 2024: U.S. Geological Survey Fact Sheet 2025–3053, 4 p., https://doi.org/10.3133/fs20253053.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-171002","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499599,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119154.htm","linkFileType":{"id":5,"text":"html"}},{"id":498591,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253053/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3053"},{"id":498515,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3053/fs20253053.xml"},{"id":497505,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1UCE8FT","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Gulf Coast Mesozoic Province, Haynesville Formation Water and Proppant Assessment—Assessment Input Tables and Fact Sheet Data Tables"},{"id":498514,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3053/images"},{"id":497504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3053/fs20253053.pdf","text":"Report","size":"2.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3053"},{"id":497503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3053/coverthb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102,\n 33.838592660251564\n ],\n [\n -102,\n 27.450416297985527\n ],\n [\n -86,\n 27.450416297985527\n ],\n [\n -86,\n 33.838592660251564\n ],\n [\n -102,\n 33.838592660251564\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Karr (1981), which introduced the index of biotic (or biological) integrity (IBI) has been cited more often (>4,500 times) than any other paper in Fisheries. In this essay, we reflect on the historical context of this seminal publication and its broad, continuing impact on the management of natural resources, especially freshwater ecosystems.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/fshmag/vuaf120","usgsCitation":"Angermeier, P., Karr, J.R., Yoder, C.O., and Hughes, R.M., 2026, Igniting the transition from water quality to biological condition and ecological health: Fisheries, v. 51, no. 1, p. 28-33, https://doi.org/10.1093/fshmag/vuaf120.","productDescription":"6 p.","startPage":"28","endPage":"33","ipdsId":"IP-181809","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":498842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Angermeier, Paul L. 0000-0003-2864-170X","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":204519,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":954207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karr, James R.","contributorId":365365,"corporation":false,"usgs":false,"family":"Karr","given":"James","middleInitial":"R.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":954208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yoder, Chris O.","contributorId":365431,"corporation":false,"usgs":false,"family":"Yoder","given":"Chris","middleInitial":"O.","affiliations":[],"preferred":false,"id":954293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Robert M.","contributorId":113579,"corporation":false,"usgs":true,"family":"Hughes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":954209,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274099,"text":"70274099 - 2026 - ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest","interactions":[],"lastModifiedDate":"2026-02-25T15:35:31.584463","indexId":"70274099","displayToPublicDate":"2026-01-09T08:26:28","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10942,"text":"PNAS Nexus","active":true,"publicationSubtype":{"id":10}},"title":"ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest","docAbstract":"Sandy beaches act as buffers against various coastal hazards but are vulnerable to episodic (seasonal) and chronic (interannual) erosion. Understanding the variation of shoreline position, a key metric in coastal morphology, over a spectrum of time scales is therefore crucial in assessing hazard vulnerability. Long-standing research has investigated the role of El Niño-Southern Oscillation (ENSO), the dominant mode of climate variability in the Pacific Basin, in seasonal shoreline variability. Yet, ENSO’s chronic influence—and that of another Pacific climate mode, the Pacific Decadal Oscillation (PDO)—on shoreline anomalies remains poorly understood. Here, we examine the variability of sandy beaches in the US Pacific Northwest, a ∼750 km long coastal region on the US West Coast. We leverage 40 years (1984–2024) of shoreline data from publicly available Earth-observing (Landsat) satellite imagery at a high spatial resolution (>10,000 shore-normal transects at 50-m alongshore spacing) and employ Convergent Cross Mapping (CCM), a methodology for inferring causality in dynamical systems. We discover that strong El Niño years are signified by erosion (75.1% of transects), and strong La Niña years exhibit accretional behavior (73.4% of transects). Furthermore, we establish, for the first time, that both ENSO and PDO exert a statistically significant control on interannual shoreline variability, particularly on the alongshore component (in 95 and 100% of littoral cells, respectively), with water level fluctuations playing a critical role. This effort advances our understanding of the seasonal-to-interannual interactions between Pacific Basin climate variability and the PNW’s coastal morphodynamics, with implications for sediment management and coastal adaptation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/pnasnexus/pgaf404","usgsCitation":"Taherkhani, M., Vitousek, S., Graffin, M., Vos, K., Allan, J.C., Kaminsky, G.M., Ruggiero, P., 2026, ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest: PNAS Nexus, v. 5, no. 1, pgaf404, 15 p., https://doi.org/10.1093/pnasnexus/pgaf404.","productDescription":"pgaf404, 15 p.","ipdsId":"IP-176083","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":500608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/pnasnexus/pgaf404","text":"Publisher Index Page"},{"id":500510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.83369555506572,\n 48.57459950593827\n ],\n [\n -126.00388302759357,\n 39.14100845126933\n ],\n [\n -122.98418105660868,\n 39.14100845126933\n ],\n [\n -122.61669284602645,\n 48.33915875055985\n ],\n [\n -125.83369555506572,\n 48.57459950593827\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Taherkhani, Mohsen","contributorId":366984,"corporation":false,"usgs":false,"family":"Taherkhani","given":"Mohsen","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":956529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":956530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graffin, Marcan","contributorId":366985,"corporation":false,"usgs":false,"family":"Graffin","given":"Marcan","affiliations":[{"id":47711,"text":"University of Toulouse","active":true,"usgs":false}],"preferred":false,"id":956531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vos, Kilian","contributorId":366986,"corporation":false,"usgs":false,"family":"Vos","given":"Kilian","affiliations":[{"id":87519,"text":"OHB Digital Services","active":true,"usgs":false}],"preferred":false,"id":956532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allan, Jonathan C.","contributorId":118007,"corporation":false,"usgs":false,"family":"Allan","given":"Jonathan","email":"","middleInitial":"C.","affiliations":[{"id":7198,"text":"Oregon Department Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":956533,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaminsky, George M.","contributorId":366988,"corporation":false,"usgs":false,"family":"Kaminsky","given":"George","middleInitial":"M.","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":956534,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruggiero, Peter","contributorId":366989,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":956535,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273744,"text":"70273744 - 2026 - Performance evaluation and methods comparison of transcriptomic-based approaches for the characterization of wastewater treatment effluent","interactions":[],"lastModifiedDate":"2026-01-27T16:57:38.288647","indexId":"70273744","displayToPublicDate":"2026-01-08T10:47:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Performance evaluation and methods comparison of transcriptomic-based approaches for the characterization of wastewater treatment effluent","docAbstract":"Wastewater treatment effluents (WWTE) present complex risks to aquatic ecosystems that are difficult to characterize using traditional methods. This study systematically evaluated the consistency and performance of transcriptomic-based approaches over time with repeated sampling and with differing experimental approaches (selection of reference condition, grab vs. composite sampling, deployed vs. laboratory exposed). RNA-seq was performed on larval fathead minnow (FHM) exposed in the laboratory to moderately hard reconstituted water (MRHW) or individual grab samples collected from an upstream site and a WWTE in the morning and afternoon over two successive days, as well as FHM deployed concurrently with grab sampling at the same sites. Composite transcriptional profiles were generated by pooling count data from grab sample exposures. The choice of comparator significantly affected results. The use of the upstream site as the reference consistently yielded fewer differentially expressed genes (DEGs) and minimal overlap compared to DEG sets from the other comparisons. Using MRHW as a comparator, DEG sets showed high consistency across grab samples, with morning samples demonstrating larger, highly consistent gene expression sets (96 % overlap) compared to afternoon samples, revealing clear and consistent within-day expression patterns. With the MHRW comparator, DEG sets from grab sample composites and deployments also overlapped substantially, indicating that transcriptional profiles accurately reflect WWTE composition regardless of exposure method. Comparisons with non-targeted (NTA) and targeted analytical datasets confirmed that gene expression interpretations aligned with effluent composition while highlighting limitations of relying solely on targeted analyte sets for connecting expression to specific chemicals. Though highly dependent on experimental design, these results demonstrate that transcriptomic-based methods provide significant utility for characterizing the bioactivity of complex environmental mixtures, and when paired with NTA datasets, have the potential to deliver a comprehensive assessment of their environmental risk.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2025.127568","usgsCitation":"Biales, A., Hu, M.S., Bencic, D.C., See, M.J., Glassmeyer, S.T., Furlong, E., Stelman, J.M., Huang, W., Kolpin, D., Mills, M.A., Brunelle, L.D., Batt, A.L., and Purucker, S.T., 2026, Performance evaluation and methods comparison of transcriptomic-based approaches for the characterization of wastewater treatment effluent: Environmental Pollution, v. 392, 127568, 12 p., https://doi.org/10.1016/j.envpol.2025.127568.","productDescription":"127568, 12 p.","ipdsId":"IP-177758","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationDate":"2026-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Biales, Adam","contributorId":200074,"corporation":false,"usgs":false,"family":"Biales","given":"Adam","email":"","affiliations":[],"preferred":false,"id":954513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, M. S.","contributorId":365640,"corporation":false,"usgs":false,"family":"Hu","given":"M.","middleInitial":"S.","affiliations":[{"id":87172,"text":"USPEA","active":true,"usgs":false}],"preferred":false,"id":954514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bencic, D. C.","contributorId":365641,"corporation":false,"usgs":false,"family":"Bencic","given":"D.","middleInitial":"C.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":954515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"See, M. J.","contributorId":365642,"corporation":false,"usgs":false,"family":"See","given":"M.","middleInitial":"J.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":954516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glassmeyer, Susan T.","contributorId":184135,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":954517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Furlong, E.T.","contributorId":365643,"corporation":false,"usgs":false,"family":"Furlong","given":"E.T.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":954518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stelman, Julia M.","contributorId":365648,"corporation":false,"usgs":false,"family":"Stelman","given":"Julia","middleInitial":"M.","affiliations":[],"preferred":false,"id":954537,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, W.","contributorId":365644,"corporation":false,"usgs":false,"family":"Huang","given":"W.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":954519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954520,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mills, Marc A.","contributorId":228849,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","middleInitial":"A.","affiliations":[{"id":41517,"text":"U.S. Enviornmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":954521,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brunelle, L. D.","contributorId":365645,"corporation":false,"usgs":false,"family":"Brunelle","given":"L.","middleInitial":"D.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":954522,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Batt, Angela L.","contributorId":184134,"corporation":false,"usgs":false,"family":"Batt","given":"Angela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":954523,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Purucker, S. Thomas","contributorId":176291,"corporation":false,"usgs":false,"family":"Purucker","given":"S.","email":"","middleInitial":"Thomas","affiliations":[],"preferred":false,"id":954524,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70274286,"text":"70274286 - 2026 - Climate change has increased crop water consumption in Central Asia despite less water-intensive cropping","interactions":[],"lastModifiedDate":"2026-03-24T14:18:48.133425","indexId":"70274286","displayToPublicDate":"2026-01-08T09:11:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Climate change has increased crop water consumption in Central Asia despite less water-intensive cropping","docAbstract":"Climate change and land use change are crucial determinants of crop water consumption, particularly in drylands where water scarcity limits crop production. In Central Asia, the effects of land use and climate changes on crop water consumption remain unknown. We estimated the dynamics of crop water consumption by mapping annual actual evapotranspiration from Landsat imagery from 1987 to 2019 for all irrigated croplands in the Amu Darya Basin, the largest transboundary river in Central Asia. Total crop water consumption increased by 10%, while average consumption per unit area increased by 18%. Climate change was the main driver of the rising crop water consumption; land use changes towards less water-intensive cropping practices offset only 3% of this increase. Our findings underscore that crop production will become increasingly challenging amidst accelerating climatic changes and that changing cropping practices alone will be insufficient to curb the growing water scarcity without a global commitment to reducing emissions.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-025-03142-y","usgsCitation":"Peña-Guerrero, M.D., Senay, G., Umirbekov, A., Tarasova, L., Rufin, P., Pulatov, B., and Müller, D., 2026, Climate change has increased crop water consumption in Central Asia despite less water-intensive cropping: Communications Earth & Environment, v. 7, 122, 9 p., https://doi.org/10.1038/s43247-025-03142-y.","productDescription":"122, 9 p.","ipdsId":"IP-180332","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":501667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-025-03142-y","text":"Publisher Index Page"},{"id":501444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tajikistan, Turkmenistan, Uzbekistan","otherGeospatial":"Amu Darya basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 55.14649185414618,\n 42.425007460866794\n ],\n [\n 55.14649185414618,\n 37.25183592908982\n ],\n [\n 69.68848488936624,\n 37.25183592908982\n ],\n [\n 69.68848488936624,\n 42.425007460866794\n ],\n [\n 55.14649185414618,\n 42.425007460866794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2026-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Peña-Guerrero, M. 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The largest component of geologic emissions is thought to be microseepage, which is the diffuse flux of CH4 from soils across large areas of productive hydrocarbon basins. The accuracy of existing bottom-up estimates of microseepage is limited by low spatial coverage of published microseepage measurements. We present the first soil—atmosphere CH4 flux measurements from Michigan Basin, USA. Results from 335 measurements taken during summer and winter seasons across a large portion of the basin suggest microseepage is nonexistent in the sampled region. Even areas with predictive features for microseepage (e.g., underlying mature, organically rich source rocks, proven gas accumulations, faults, and lineaments) yield null or negative fluxes, suggesting that CH4 emissions from microseepage are negligible throughout our study region. A Monte Carlo method was used to place an upper limit on the regional-mean microseepage flux, in which synthetic patchy microseepage distributions were generated and tested against our observations to assess the impact of possible emission hot spots that were missed by our sampling strategy. Our analysis finds it is very unlikely that regional-mean emissions are as high as assumed in a previous global microseepage study. The observed lack of seepage may be explained by groundwater flow, active methanotrophy, glacial sediments, and bedded salt deposits, which could inhibit vertical gas migration and release to atmosphere.
","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.2025.00058","usgsCitation":"Hall, K.R., Weber, T.S., Stock, M.P., Buursink, M., Piao, H., Zhu, M., Walter-Anthony, K.M., and Petrenko, V.V., 2026, New measurements indicate that natural geologic methane emissions from microseepage in the Michigan Basin are likely negligible: Elementa: Science of the Anthropocene, v. 14, no. 1, 00058, 17 p., https://doi.org/10.1525/elementa.2025.00058.","productDescription":"00058, 17 p.","ipdsId":"IP-170390","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":499297,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.2025.00058","text":"Publisher Index Page"},{"id":499228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Huron, Lake Michigan, Michigan Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.20025852293985,\n 46.54984228068227\n ],\n [\n -88.20025852293985,\n 42.865081723412004\n ],\n [\n -81.7815573772342,\n 42.865081723412004\n ],\n [\n -81.7815573772342,\n 46.54984228068227\n ],\n [\n -88.20025852293985,\n 46.54984228068227\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Kathleen R.","contributorId":365776,"corporation":false,"usgs":false,"family":"Hall","given":"Kathleen","middleInitial":"R.","affiliations":[{"id":87217,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627","active":true,"usgs":false}],"preferred":false,"id":954773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Thomas S.","contributorId":198207,"corporation":false,"usgs":false,"family":"Weber","given":"Thomas","middleInitial":"S.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":954774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Marika P.","contributorId":365777,"corporation":false,"usgs":false,"family":"Stock","given":"Marika","middleInitial":"P.","affiliations":[{"id":87217,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627","active":true,"usgs":false}],"preferred":false,"id":954775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buursink, Marc L. 0000-0001-6491-386X","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":203357,"corporation":false,"usgs":true,"family":"Buursink","given":"Marc L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Piao, Haoran","contributorId":365778,"corporation":false,"usgs":false,"family":"Piao","given":"Haoran","affiliations":[{"id":87217,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627","active":true,"usgs":false}],"preferred":false,"id":954777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhu, Mingzhe","contributorId":365779,"corporation":false,"usgs":false,"family":"Zhu","given":"Mingzhe","affiliations":[{"id":87217,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627","active":true,"usgs":false}],"preferred":false,"id":954778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walter-Anthony, Katey M.","contributorId":365780,"corporation":false,"usgs":false,"family":"Walter-Anthony","given":"Katey","middleInitial":"M.","affiliations":[{"id":87218,"text":"University of Alaska Fairbanks, Fairbanks, AK 99775-5910","active":true,"usgs":false}],"preferred":false,"id":954779,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Petrenko, Vasilii V.","contributorId":365781,"corporation":false,"usgs":false,"family":"Petrenko","given":"Vasilii","middleInitial":"V.","affiliations":[{"id":87217,"text":"Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627","active":true,"usgs":false}],"preferred":false,"id":954780,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273675,"text":"70273675 - 2026 - 21st-century mangrove expansion along the southeastern United States","interactions":[],"lastModifiedDate":"2026-01-22T15:20:52.45908","indexId":"70273675","displayToPublicDate":"2026-01-07T09:15:57","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"21st-century mangrove expansion along the southeastern United States","docAbstract":"Warming winter temperatures are driving range expansion of tropical, cold-sensitive mangroves into temperate ecosystems. Along the Atlantic coast of North America, the mangrove range limit is particularly sensitive to climate variability and historical data demonstrate that the mangrove-salt marsh ecotone on this coast has shifted recurrently during recent centuries. However, a comprehensive understanding of how this mangrove-salt marsh ecotone may shift in the future remains lacking. Here, we combine ensemble forecasting of mangrove distribution for the next century with high-resolution oceanographic dispersal simulations, phenological observations, and historical hurricane data to project future mangrove-salt marsh dynamics at the rapidly changing range limit in northeastern Florida (USA). We show that warming winter temperatures will drive continued poleward expansion of mangroves along North America's Atlantic coast, potentially reaching South Carolina by 2100. With ongoing climate change, suitable mangrove habitat is projected to expand beyond the current range limit, and dispersal simulations suggest successful colonization of these sites from established mangrove populations. Additionally, patterns in hurricane directionality and intensity and field reports of propagule presence reveal that these high-energy events may significantly contribute to future mangrove range expansion by facilitating long-distance, storm-driven propagule dispersal. The encroachment of mangroves in salt marsh-dominated latitudes is expected to substantially modify wetland ecosystem function and structure, emphasizing how the identification of newly colonizable habitat can inform conservation strategies and site-specific decisions on mangrove management.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.70676","usgsCitation":"Enes Gramoso, L.I., Carrol, D., Cavanaugh, K.C., Bardou, R., Osland, M., and Van der Stocken, T., 2026, 21st-century mangrove expansion along the southeastern United States: Global Change Biology, v. 32, no. 1, e70676, 13 p., https://doi.org/10.1111/gcb.70676.","productDescription":"e70676, 13 p.","ipdsId":"IP-181151","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":498935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.70676","text":"Publisher Index Page"},{"id":498835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.22200639953145,\n 36.37952978542975\n ],\n [\n -77.72182101969094,\n 36.40470575265279\n ],\n [\n -81.91411568081017,\n 32.113748227893616\n ],\n [\n -81.74573448773677,\n 28.953603900196043\n ],\n [\n -80.85814647675448,\n 25.888305578021306\n ],\n [\n -83.46267982375748,\n 24.175772833973156\n ],\n [\n -79.91513400031955,\n 24.69759886854142\n ],\n [\n -79.81651773807448,\n 27.222321721452442\n ],\n [\n -81.06547026177786,\n 30.86676837523688\n ],\n [\n -76.06738341951453,\n 34.54040871806913\n ],\n [\n -75.22200639953145,\n 36.37952978542975\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Enes Gramoso, Lucia I.A.","contributorId":365421,"corporation":false,"usgs":false,"family":"Enes Gramoso","given":"Lucia","middleInitial":"I.A.","affiliations":[{"id":87134,"text":"Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":954277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carrol, Dustin","contributorId":365422,"corporation":false,"usgs":false,"family":"Carrol","given":"Dustin","affiliations":[{"id":87135,"text":"San José State University, Moss Landing, CA 95039","active":true,"usgs":false}],"preferred":false,"id":954278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cavanaugh, Kyle C.","contributorId":365423,"corporation":false,"usgs":false,"family":"Cavanaugh","given":"Kyle","middleInitial":"C.","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":954279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bardou, Remi","contributorId":274822,"corporation":false,"usgs":false,"family":"Bardou","given":"Remi","affiliations":[{"id":56654,"text":"Northeastern University Marine Science Center, 430 Nahant Rd, Nahant, Massachusetts, USA","active":true,"usgs":false}],"preferred":false,"id":954280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osland, Michael J. 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":206443,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":954281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van der Stocken, Tom","contributorId":365424,"corporation":false,"usgs":false,"family":"Van der Stocken","given":"Tom","affiliations":[{"id":87134,"text":"Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":954282,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273498,"text":"70273498 - 2026 - Status assessment of peregrine falcons in North America using integrated population models","interactions":[],"lastModifiedDate":"2026-01-20T14:59:43.055314","indexId":"70273498","displayToPublicDate":"2026-01-07T07:52:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Status assessment of peregrine falcons in North America using integrated population models","docAbstract":"Species status assessments require an understanding of underlying population dynamics and important drivers of species demography. Large-scale assessments can be difficult due to challenges collating data obtained through different methods and different sources at multiple scales. Integrated population models (IPMs) provide a unified framework to combine multiple data sources and jointly estimate population parameters over a large spatiotemporal scale. We developed separate IPMs to estimate abundance and demographic rates for a northern (NMP) and southern (SMP) management population of peregrine falcons (Falco peregrinus) in North America from 2008 through 2019 (SMP) and 2020 (NMP). An outbreak of highly pathogenic avian influenza (HPAI) starting in 2021 led us to extend our modeling effort to assess its impact on these management populations by updating both IPMs using index data of population size through 2024 in a predictive framework. Survival probabilities differed drastically between first-year and after-first-year individuals in both management populations. After-first-year survival was nearly identical between the NMP and SMP, but first-year survival was lower in the SMP. Mean productivity was significantly lower in the NMP compared to the SMP, whereas the probability of breeding was similar in both management populations. Estimated total abundance for the NMP was substantially larger than the SMP, representing most of the North American peregrine population. Population growth was positive for both management populations, albeit at a slower rate for the NMP. The NMP declined from 2017 to 2018 coinciding with a drop in 2018 estimated productivity. When we extended the IPMs with updated count data through 2024, the NMP slightly declined but estimated abundance remained above levels at the start of the time series analyzed. The SMP grew at a similar rate to that predicted during the period informed by demographic data. We did not detect a continental-scale change in population size or trajectory in either management population associated with the arrival of HPAI in 2021. Further monitoring can support determination of whether the declines in the NMP were temporary, can enhance understanding of the underlying mechanisms, and can be used to guide the conservation and management of the peregrine falcon population in North America.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e04024","usgsCitation":"Gould, M.J., Swem, T., Zimmerman, G.S., Millsap, B.A., Gedir, J.V., and Abadi, F., 2026, Status assessment of peregrine falcons in North America using integrated population models: Global Ecology and Conservation, v. 65, e04024, 12 p., https://doi.org/10.1016/j.gecco.2025.e04024.","productDescription":"e04024, 12 p.","ipdsId":"IP-180300","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":498918,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e04024","text":"Publisher Index Page"},{"id":498771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -17.645512177727937,\n 74.08269629392527\n ],\n [\n 4.050887934414121,\n 84.76371880139833\n ],\n [\n -167.95111365975603,\n 80.1265394049586\n ],\n [\n -169.85914511777705,\n 64.47840403364626\n ],\n [\n -157.58234088200044,\n 51.521173449696605\n ],\n [\n -136.03883649130242,\n 48.901619472112586\n ],\n [\n -108.50429591511289,\n 19.862808733419378\n ],\n [\n -97.3445071848272,\n 13.771551176727286\n ],\n [\n -75.36673211463953,\n 26.504032983593405\n ],\n [\n -43.55025606980736,\n 58.05109732496808\n ],\n [\n -17.645512177727937,\n 74.08269629392527\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gould, Michael J. 0000-0002-9703-4690","orcid":"https://orcid.org/0000-0002-9703-4690","contributorId":316810,"corporation":false,"usgs":true,"family":"Gould","given":"Michael","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swem, Ted","contributorId":200583,"corporation":false,"usgs":false,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":954019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, Guthrie S. 0000-0002-0965-2123","orcid":"https://orcid.org/0000-0002-0965-2123","contributorId":365268,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","middleInitial":"S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Millsap, Brian A. 0000-0003-3969-249X","orcid":"https://orcid.org/0000-0003-3969-249X","contributorId":365269,"corporation":false,"usgs":false,"family":"Millsap","given":"Brian","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":954021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gedir, Jay V.","contributorId":365270,"corporation":false,"usgs":false,"family":"Gedir","given":"Jay","middleInitial":"V.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":954022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abadi, Fitsum","contributorId":337711,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":954023,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272701,"text":"fs20253055 - 2026 - FluOil—A tool for estimating the transport and deposition of oil-particle aggregates in rivers","interactions":[],"lastModifiedDate":"2026-02-03T17:05:03.22053","indexId":"fs20253055","displayToPublicDate":"2026-01-07T07:29:50","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3055","displayTitle":"FluOil—A Tool for Estimating the Transport and Deposition of Oil-Particle Aggregates in Rivers","title":"FluOil—A tool for estimating the transport and deposition of oil-particle aggregates in rivers","docAbstract":"The FluOil tool was developed to help with planning and early response for oil spills in rivers where subsurface oil-sediment interactions result in the formation of oil-particle aggregates (OPA). The turbulence and variable velocity associated with water flowing within a natural stream channel creates the conditions needed for an oil slick to break up into small droplets and mix in the water column, collide with sediment or organic detritus, and form OPA. This process is similar to what occurs due to wave action along a shoreline. The FluOil tool estimates how fast OPA travel downstream in rivers as well as when and where they may deposit. The FluOil tool relies on pre-existing channel hydraulic data along with user-specified OPA characteristics of size, settling velocity and critical shear stress to compute OPA transport. It is important to know where OPA are transported and accumulated for understanding potential impacts on drinking water intakes, burial of sensitive habitat beds, potential toxicity to benthic organisms, and prolonged sheening from resuspension and breakup. OPA tend to accumulate with fine-grained (silt and clay) sediment deposits (“mud” or “muck”) in backwater areas, oxbows, side channels, pools, and other slow-moving reaches of rivers during low flows. Deposited OPA can be resuspended during high flows, driving continued environmental impact concerns that may extend beyond typical oil spill response timelines.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253055","collaboration":"Prepared in cooperation with the Inland Oil Spill Preparedness Program, U.S. Environmental Protection Agency, Lake Superior State University, and Natural Resources Canada","usgsCitation":"Fitzpatrick, F., Roland, C., Vaughan, A., Zhu, Z., Soong, D., and Sortor, R., 2026, FluOil—A tool for estimating the transport and deposition of oil-particle aggregates in rivers: U.S. Geological Survey Fact Sheet 2025–3055, 6 p., https://doi.org/10.3133/fs20253055.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-178930","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497094,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3055/fs20253055.pdf","text":"Report","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025–3055"},{"id":497093,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3055/coverthb.jpg"},{"id":497101,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99MJ6MD","text":"USGS data release","linkHelpText":"FluOil model and related datasets for Kalamazoo River, Michigan, oil spill—July 21 to October 31, 2010"},{"id":497100,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253055/full","text":"Report","description":"FS 2025–3055 HTML"},{"id":497099,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3055/images"},{"id":497098,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3055/fs20253055.XML","linkFileType":{"id":8,"text":"xml"}}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The FluOil tool helps oil spill planners and responders estimate how fast and far oiled sediment (called oil-particle aggregates [OPA]) can travel in rivers during an oil spill, and where it may settle out on the riverbed. The user interface makes it easy to run the tool for a range of river flow conditions and OPA characteristics.
","publicationDate":"2026-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209191,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roland, Collin 0000-0003-1004-0746","orcid":"https://orcid.org/0000-0003-1004-0746","contributorId":343660,"corporation":false,"usgs":true,"family":"Roland","given":"Collin","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vaughan, Angus 0000-0001-9900-4658","orcid":"https://orcid.org/0000-0001-9900-4658","contributorId":302333,"corporation":false,"usgs":true,"family":"Vaughan","given":"Angus","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":951368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhenduo","contributorId":340263,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhenduo","affiliations":[{"id":81528,"text":"Tsinghua University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":951369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soong, David 0000-0003-0404-2163","orcid":"https://orcid.org/0000-0003-0404-2163","contributorId":206523,"corporation":false,"usgs":true,"family":"Soong","given":"David","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sortor, Rachel 0000-0002-8778-4383","orcid":"https://orcid.org/0000-0002-8778-4383","contributorId":298591,"corporation":false,"usgs":true,"family":"Sortor","given":"Rachel","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951371,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273363,"text":"70273363 - 2026 - Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed","interactions":[],"lastModifiedDate":"2026-01-09T17:31:50.365144","indexId":"70273363","displayToPublicDate":"2026-01-06T11:26:38","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed","docAbstract":"Earthquake catalogs are essential data inputs for seismic hazard modeling. Because earthquake magnitudes are reported in a variety of types (e.g., local magnitudes and moment magnitudes), magnitude conversion relationships must be used to convert the different magnitude types present in a catalog to a uniform magnitude type to avoid biases in the hazard computation. However, these conversion relationships are often uncertain and have been shown to sometimes perform poorly. Here, we investigate the sensitivity of the gridded seismicity component of the National Seismic Hazard Model (NSHM) to the catalog conversion equations in the Eastern United States. In the 2023 NSHM, magnitudes of various types were converted to moment magnitudes using equations developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn), based on least‐squares (LS) regressions made using data from a catalog containing events up through 2008. We recompute these equations using events in the Advanced National Seismic System Comprehensive Earthquake Catalog with multiple magnitudes from 2000 to 2023. Although we prefer the use of orthogonal regressions for our datasets, LS regressions produce broadly similar results, with both approaches exhibiting large deviations from the CEUS‐SSCn conversions, especially at smaller magnitudes. We compare the spatial distribution of annual rates using three different models: (1) the 2023 NSHM conversions, (2) our updated conversions, and (3) no conversions. We find that the choice of conversions leads to substantial differences in the rate forecasts, which can greatly impact the seismic hazard model, particularly in regions with low‐seismicity rates such as the Eastern United States, where the hazard is dominated by gridded seismicity rather than a fault model.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250231","usgsCitation":"Llenos, A.L., Shelly, D.R., and Shumway, A., 2026, Magnitude conversion relations create substantial differences in seismic hazard models: Seismological Research Letters, https://doi.org/10.1785/0220250231.","ipdsId":"IP-179044","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":500652,"rank":3,"type":{"id":12,"text":"Errata"},"url":"https://doi.org/10.1785/0220260025","linkFileType":{"id":5,"text":"html"}},{"id":498508,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498688,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250231","text":"Publisher Index Page"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100,\n 50\n ],\n [\n -100,\n 25\n ],\n [\n -65,\n 25\n ],\n [\n -65,\n 50\n ],\n [\n -100,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":953425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":953426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shumway, Allison 0000-0003-1142-7141 ashumway@usgs.gov","orcid":"https://orcid.org/0000-0003-1142-7141","contributorId":147862,"corporation":false,"usgs":true,"family":"Shumway","given":"Allison","email":"ashumway@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":953427,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":70273838,"text":"70273838 - 2026 - Toxicity of 6PPD alternatives to salmonid cell lines","interactions":[],"lastModifiedDate":"2026-02-05T15:38:34.453429","indexId":"70273838","displayToPublicDate":"2026-01-06T09:24:15","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Toxicity of 6PPD alternatives to salmonid cell lines","docAbstract":"Stormwater runoff in urban areas introduces numerous anthropogenic chemicals into surrounding aquatic environments. One such chemical is 6PPD (N-(1,3-Dimethylbutyl)-N’-phenyl-p-phenylenediamine), the primary antidegradant responsible for protecting tire rubber from ozone-induced degradation and cracking. When exposed to ozone on the road surface 6PPD is transformed into the toxic transformation product 6PPD-quinone (6PPDQ). This compound is highly lethal to coho salmon ( Oncorhynchus kisutch), and 24 hour 50% lethal concentrations (LC50; 41-95 ng/L) are frequently detected in urban streams during stormwater runoff events1-5. The highest stream concentrations of 6PPDQ and most extensive coho salmon mortality occur in high-traffic urban areas, where tire wear particles accumulate due to the frequent braking and acceleration of cars6. In the Seattle area, some coho salmon-bearing streams can lose over 90% of returning females prior to spawning due to 6PPDQ-containing runoff7. Prespawn loss of this magnitude could result in the extinction of some urban spawning populations8. Importantly, the lethal effects of 6PPDQ have been observed in several other salmonid species, indicating that its impact may threaten fish health for urban aquatic environments globally9-11.
The ubiquity of 6PPD in automobile tires, high toxicity of the transformation product 6PPDQ, and prevalence of 6PPD and 6PPDQ in environmental matrices has spurred investigations into alternative rubber antiozonants to replace 6PPD that retain tire performance while reducing ecological harm. A technical memorandum provided to the legislature by the Washington State Department of Ecology summarized a list of potential 6PPD alternatives requiring further study, including several structurally similar p-phenylenediamines (PPDs)12. However, the structural similarity of other PPDs to 6PPD and their known production of quinone transformation products13 raises concerns that they may elicit similar toxic effects as 6PPDQ. Currently, investigations into the toxicity of proposed PPD alternatives or their ozonated transformation products in coho salmon are limited, representing a significant data gap in evaluating whether they offer improved environmental safety over 6PPD.
This project investigated the toxicity of proposed alternative rubber antiozonants in vitro using immortalized cell lines derived from three salmonid species with known differences in sensitivity to 6PPDQ (coho salmon, Chinook salmon (O. tshawytscha), rainbow trout (O. mykiss))1. These immortalized cell lines replicate toxic responses observed in in vivo studies, while enabling higher-throughput testing and reducing the need for animal use and other resource-intensive procedures. The antiozonants and their transformation products selected for testing were chosen based on multiple criteria, including their inclusion in the Ecology technical memorandum, structural substitutions (e.g., branched/cyclic alkyl vs aryl substitutions), commercial availability, and input from the Washington State Department of Ecology and other industry experts.
","language":"English","publisher":"Washington Department of Ecology","usgsCitation":"Greer, J.B., Dalsky, E.M., Bachand, P.T., and Hansen, J.D., 2026, Toxicity of 6PPD alternatives to salmonid cell lines, 13 p.","productDescription":"13 p.","ipdsId":"IP-183177","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499582,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.ezview.wa.gov/site/alias__1962/37732/research_and_proposed_alternatives_to_6ppd.aspx"}],"noUsgsAuthors":false,"publicationDate":"2026-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Greer, Justin Blaine 0000-0001-6660-9976","orcid":"https://orcid.org/0000-0001-6660-9976","contributorId":265183,"corporation":false,"usgs":true,"family":"Greer","given":"Justin","email":"","middleInitial":"Blaine","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":955178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalsky, Ellie Maureen 0000-0001-8299-7198","orcid":"https://orcid.org/0000-0001-8299-7198","contributorId":265182,"corporation":false,"usgs":true,"family":"Dalsky","given":"Ellie","email":"","middleInitial":"Maureen","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":955179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bachand, Paxton Turner 0009-0002-4196-9005","orcid":"https://orcid.org/0009-0002-4196-9005","contributorId":366032,"corporation":false,"usgs":true,"family":"Bachand","given":"Paxton","middleInitial":"Turner","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":955180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, John D. 0000-0002-3006-2734","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":220725,"corporation":false,"usgs":true,"family":"Hansen","given":"John","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":955181,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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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and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70271720","publicationYear":"2025","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"predicate":"SUPERSEDED_BY","object":{"id":70273497,"text":"70273497 - 2026 - Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","indexId":"70273497","publicationYear":"2026","noYear":false,"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations"},"id":1}],"lastModifiedDate":"2026-01-20T15:17:42.806547","indexId":"70273497","displayToPublicDate":"2026-01-06T08:09:21","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning generated streamflow drought forecasts for the conterminous United States (CONUS): developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations","docAbstract":"Forecasts of streamflow drought, when streamflow declines below typical levels, are notably less available than for floods or meteorological drought, despite widespread impacts. We apply machine learning (ML) models to forecast streamflow drought 1–13 weeks ahead at 3,219 streamgages across the conterminous United States. We applied two ML methods (Long short-term memory neural networks; Light Gradient-Boosting Machine) and two benchmark models (persistence; Autoregressive Integrated Moving Average) to predict weekly streamflow percentiles with independent models for each forecast horizon. ML models outperformed benchmarks in predicting continuous streamflow percentiles below 30%. ML models generally performed worse than persistence models for discrete classification (moderate, severe, extreme) but exceeded the benchmark models for drought onset/termination. Performance was better for less intense droughts and shorter horizons, with predictive power for 1–4 weeks for severe droughts (10% threshold). This work highlights challenges and opportunities to advance hydrological drought forecasting and supports a new experimental forecasting tool.
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