At the Bascom Laser Diffraction Sedimentology Laboratory, which is located in the Florence Bascom Geoscience Center at U.S. Geological Survey (USGS) headquarters in Reston, Virginia, scientists use physical sedimentology and particle characterization techniques to conduct detailed sediment characterization. Scientists address research problems in collaboration with other USGS science centers, State geological surveys, commercial industry, universities, and other partners. Laboratory capabilities include laser diffractometry for quantitative particle-size analysis, portable x-ray fluorescence (XRF) analysis for determining elemental abundances in rock or sediment samples, petrographic analysis of geologic media, and mechanical sieve analysis. These methods are used to analyze soil and sediment core material from terrestrial, marine, and lacustrine environments, surface sediments from coastal regions, and calcareous materials. Work done by the laboratory supports geologic mapping, resource assessments, land change studies, and geohazard analyses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253051","usgsCitation":"Colip, Grant D., 2026, Bascom Laser Diffraction Sedimentology Laboratory, Reston, Virginia: U.S. Geological Survey Fact Sheet 2025–3051, 4 p., https://doi.org/10.3133/fs20253051.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180629","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":499522,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3051/coverthb.jpg"},{"id":499523,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3051/fs20253051.pdf","size":"1.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3051 PDF"},{"id":499524,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253051/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3051 HTML"},{"id":499525,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3051/fs20253051.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3051 XML"},{"id":499526,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3051/images/"}],"contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Fault geometry exerts a first-order control on geothermal systems by governing stress localization, fracture development, and permeability, yet in complex fault networks or broader shear zones, the relative influence of individual geometric features is often difficult to resolve. In the northern California Coast Ranges, The Geysers geothermal field is commonly interpreted to occur within a releasing stepover, although no single, clearly defined stepover is identified in published studies. To investigate the structural controls on The Geysers and the broader Clear Lake region, a two-dimensional elastic boundary element model is developed to evaluate spatial patterns of dilational strain associated with progressively more complete fault geometries. Model results show that dilation in the region is not controlled by a single structure but instead reflects the combined effects of multiple interacting fault elements. Three primary controls are identified: (1) opposing bends in the regional strike-slip fault system, including a releasing bend along the Maacama fault; (2) the southern fault tip of the Collayomi fault, which generates a prominent dilational lobe beneath the southern Geysers; and (3) a releasing stepover between the Collayomi fault and the Geyser Peak–Mercuryville–Big Sulphur Creek fault system, inferred to collectively behave as a right-lateral shear zone bounding the western margin of The Geysers. Predicted dilational strain magnitudes are sufficient to localize permeability between faults. These results highlight that incorporating complete fault networks and bedrock geological mapping can enhance geothermal assessments and provide a transferable framework for evaluating structurally controlled permeability in tectonically active regions.
","conferenceTitle":"51st Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 9-11, 2026","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford","usgsCitation":"Melosh, B.L., 2026, Stepovers and beyond: Structural control of The Geysers geothermal system and the broader Clear Lake region, 51st Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 9-11, 2026, 10 p.","productDescription":"10 p.","ipdsId":"IP-185865","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501816,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=38346"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake region, Geysers geothermal system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.08882992251972,\n 39.16306777840023\n ],\n [\n -123.08882992251972,\n 38.698271344676584\n ],\n [\n -122.51130712624908,\n 38.698271344676584\n ],\n [\n -122.51130712624908,\n 39.16306777840023\n ],\n [\n -123.08882992251972,\n 39.16306777840023\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2026-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Melosh, Benjamin L. 0000-0002-8017-7193","orcid":"https://orcid.org/0000-0002-8017-7193","contributorId":217215,"corporation":false,"usgs":true,"family":"Melosh","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":958309,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273880,"text":"70273880 - 2026 - The petrogenesis of Þingmúli volcano, East Fjords, Iceland","interactions":[],"lastModifiedDate":"2026-04-06T15:51:12.426713","indexId":"70273880","displayToPublicDate":"2026-02-09T07:57:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The petrogenesis of Þingmúli volcano, East Fjords, Iceland","docAbstract":"In this work we revisit Þingmúli volcano (Þ = Th), a classic locality known as an example of a complete tholeiitic differentiation. Þingmúli is a ~ 9.5 Ma extinct central volcano located in the East Fjords of Iceland, in which the whole compositional spectrum from basalt to rhyolites have erupted. These volcanic products have been previously considered as petrogenetically related by an ideal fractionation trend, regardless any temporal relationship or volumetric considerations.
Here we report new whole-rock geochemistry, mineral chemistry, isotope analyses, estimation of residence times of the different eruptive deposits, and an update of the original petrogenetic model. Our results highlight that an enriched source, likely spinel lherzolites, generated transitional-alkaline basaltic melts after 15–20% of partial melting at depths of 40–45 km. Many of these basaltic melts erupted at various stages of the volcano's history, while others remained longer in the volcanic plumbing system. These evolved by fractional crystallisation into basaltic andesite magmas with a residence time of ~5 years based on the crystal size distribution of the plagioclase population. Isotopic differences between the basalts/basaltic andesites (87Sr/86Sr ~ 0.7034; 143Nd/144Nd ~ 0.51315) and the erupted rhyolites (87Sr/86Sr ~ 0.7037; 143Nd/144Nd ~ 0.51304) indicate that the latter are not petrogenetically related to the former. Therefore, instead of a fractional crystallisation mechanism to generate the rhyolites, we propose the partial melting of ignimbrite layers located beneath the volcano. The broad range of trace element concentrations in andesites and dacites and their different isotopic values compared to the basalts strongly suggest that these magmas have been generated by magma mixing between basaltic and rhyolitic melts, similar to modern day Icelandic volcanoes such as Hekla. These results highlight the need to revisit previously studied Icelandic classic localities and reassess their traditionally proposed petrogenetic models.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2026.108561","usgsCitation":"Hughes, A., Cortès, J.A., McGarvie, D., Moscati, R.J., and Olive, V., 2026, The petrogenesis of Þingmúli volcano, East Fjords, Iceland: Journal of Volcanology and Geothermal Research, v. 472, 108561, 64 p., https://doi.org/10.1016/j.jvolgeores.2026.108561.","productDescription":"108561, 64 p.","ipdsId":"IP-182556","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":499746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502210,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13NQWAA","linkFileType":{"id":5,"text":"html"}}],"country":"Iceland","otherGeospatial":"Þingmúli volcano, East Fjords","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -23.540028058288044,\n 66.59258513859314\n ],\n [\n -25.126290149179766,\n 65.22506991722106\n ],\n [\n -22.087340842076145,\n 63.19806647357345\n ],\n [\n -13.158892284515474,\n 63.28606024776602\n ],\n [\n -13.158892284515474,\n 66.7304685435675\n ],\n [\n -23.540028058288044,\n 66.59258513859314\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"472","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hughes, Amanda L. 0000-0003-2481-444X","orcid":"https://orcid.org/0000-0003-2481-444X","contributorId":346354,"corporation":false,"usgs":false,"family":"Hughes","given":"Amanda L.","affiliations":[{"id":82839,"text":"Edge Hill University, UK","active":true,"usgs":false}],"preferred":false,"id":955407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cortès, Joaquín A. 0000-0003-0062-6954","orcid":"https://orcid.org/0000-0003-0062-6954","contributorId":366198,"corporation":false,"usgs":false,"family":"Cortès","given":"Joaquín","middleInitial":"A.","affiliations":[{"id":87379,"text":"Edge Hill Univ","active":true,"usgs":false}],"preferred":false,"id":955408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGarvie, Dave","contributorId":366200,"corporation":false,"usgs":false,"family":"McGarvie","given":"Dave","affiliations":[{"id":87380,"text":"Lancaster Univ","active":true,"usgs":false}],"preferred":false,"id":955409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":955410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olive, Valerie 0000-0002-3905-2946","orcid":"https://orcid.org/0000-0002-3905-2946","contributorId":366201,"corporation":false,"usgs":false,"family":"Olive","given":"Valerie","affiliations":[{"id":87381,"text":"Univ of Glasgow","active":true,"usgs":false}],"preferred":false,"id":955411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273822,"text":"70273822 - 2026 - Ten new insights in climate science 2025","interactions":[],"lastModifiedDate":"2026-02-04T15:13:28.226776","indexId":"70273822","displayToPublicDate":"2026-02-08T07:49:38","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21212,"text":"Global Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Ten new insights in climate science 2025","docAbstract":"Interdisciplinary understanding is vital for delivering sound climate policy advice. However, navigating the ever-growing and increasingly diverse scholarly literature on climate change is challenging for any individual researcher. This annual synthesis highlights and explains recent advances across a variety of fields of climate change research. This year, the 10 insights focus on: (1) the record-warmth of 2023/2024 and the elevated Earth energy imbalance; (2) acceleration of ocean warming and intensifying marine heatwaves; (3) northern land carbon sinks under strain; (4) reinforcing feedback between biodiversity loss and climate change; (5) accelerated depletion of groundwater; (6) global dengue incidence; (7) global income losses and labour productivity declines; (8) strategic scaling of CDR; (9) integrity challenges in carbon credit markets and emerging responses; and (10) effective policy mixes for emissions reductions. The insights have been written to be accessible to researchers from different fields, serving as entry-points to specific topics, as well as providing an overview of the evolving landscape of climate change research. In the final section, the insights are used to develop overarching policy-relevant messages. This paper provides the basis for a science-policy report that was shared with all Party delegations ahead of COP30 in Belém, Brazil.","language":"English","publisher":"Cambridge University Press","doi":"10.1017/sus.2025.10043","usgsCitation":"Ospina, D., Mirazo, P., Allan, R.P., Basnett, S., Bastos, A., Bhattarai, N., Broadgate, W., Broekhoff, D.J., Bustamante, M., Chen, D., Choi, Y., Cox, P., Domeignoz-Horta, L.A., Ebi, K., Friedlingstein, P., Frölicher, T.L., Fuss, S., Goessling, H.F., Gruber, N., He, Q., Hebden, S.R., Hedrich, N., Heilemann, A., Hirota, M., Hodnebrog, Ø., Hugelius, G., Izquierdo-Tort, S., Juhola, S., Kasuga, F., Ke, P., Kelley, D.I., Kilkiș, Ş., Kotz, M., Kumarasinghe, N., Lamb, W.F., Lee, S., Liu, J., Maesano, C.N., Martin, M.A., Mazzochini, G.G., Merchant, C.J., Mori, A.S., Morris, J., Persson, Å., Pörtner, H., Probst, B.S., Ramage, J., Razanatsoa, E., Redman, A., Rockström, J., Rodrigues, R., Ruehr, S., Ryan, S.J., Schleussner, C., Schlosser, P., Scott, W.A., Semenza, J.C., Seybold, H., Shindell, D.T., Sioen, G.B., Smith, K.E., Sokona, Y., Stechemesser, A.H., Stocker, T.F., Su, S.H., Thiam, D., Trencher, G., Virkkala, A., Warszawski, L., Weiskopf, S.R., Wu, H., and Zhu, S., 2026, Ten new insights in climate science 2025: Global Sustainability, v. 9, e6, 37 p., https://doi.org/10.1017/sus.2025.10043.","productDescription":"e6, 37 p.","ipdsId":"IP-179484","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":499625,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/sus.2025.10043","text":"Publisher Index Page"},{"id":499500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2026-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ospina, Daniel","contributorId":365884,"corporation":false,"usgs":false,"family":"Ospina","given":"Daniel","affiliations":[{"id":87244,"text":"Future Earth Secretariat","active":true,"usgs":false}],"preferred":false,"id":954957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirazo, Paula","contributorId":365885,"corporation":false,"usgs":false,"family":"Mirazo","given":"Paula","affiliations":[],"preferred":false,"id":954958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allan, Richard P.","contributorId":365886,"corporation":false,"usgs":false,"family":"Allan","given":"Richard","middleInitial":"P.","affiliations":[{"id":87245,"text":"Department of Meteorology/National Centre for Earth Observation, University of Readingu","active":true,"usgs":false}],"preferred":false,"id":954959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Basnett, Smriti","contributorId":365887,"corporation":false,"usgs":false,"family":"Basnett","given":"Smriti","affiliations":[{"id":87246,"text":"1. 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Effective communication is critical for promoting coexistence, yet on-the-ground conservation messaging seldom links to behavior change theories. We conducted 23 semistructured interviews with practitioners to examine the approaches they used to communicate with private landowners about beaver coexistence in Oregon (USA). Although we did not set out to interview practitioners about their messages targeting capability, opportunity, and motivation (elements of the COM-B model of behavior), we used the COM-B model to synthesize the primary dimensions of practitioners’ complex, real-world communication about human–wildlife coexistence. We found that practitioners used multiple communication channels to listen for and respond to landowners’ capability, opportunity, and motivation. They tailored messages to affirm and enhance knowledge and skills, identify and address site-specific and social contexts, and align beaver impacts with landowner goals. Our findings suggest the COM-B model can go beyond guiding audience analysis and behavioral intervention design to help practitioners tailor real-time communication with landowners about coexistence behavior. The model, based on our use of COM-B to analyze existing communication, could be used to provide practitioners with techniques for making sense of their existing communication efforts, for identifying gaps, and for dynamically tailoring their communication.
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\"}}]}","volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Brian D.","contributorId":339269,"corporation":false,"usgs":false,"family":"Erickson","given":"Brian","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":956184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956185,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70275540,"text":"70275540 - 2026 - Chronic wasting disease (CWD) knowledge, risk perception, and management acceptance are influenced by media engagement and trust among deer hunters in Massachusetts","interactions":[],"lastModifiedDate":"2026-05-04T16:31:30.912073","indexId":"70275540","displayToPublicDate":"2026-02-07T09:21:05","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Chronic wasting disease (CWD) knowledge, risk perception, and management acceptance are influenced by media engagement and trust among deer hunters in Massachusetts","docAbstract":"Prior to wildlife disease emergence, public outreach campaigns can improve disease-related knowledge and increase the likelihood that stakeholders accept potential management actions. One wildlife disease of particular interest is chronic wasting disease (CWD), which is spreading across the United States but has not been detected in Massachusetts. We conducted a survey of deer hunters (n = 7,419) in Massachusetts to: (1) explore media channel usage and source trust, and (2) assess the relationship among CWD knowledge, risk perception, management acceptability, and state wildlife agency trust. We found that channel usage and source trust varied by socio-demographic factors. We also found that engagement with popular channels and trust in accurate sources were positively correlated with CWD knowledge. CWD risk perception mediated the relationship between knowledge and management acceptance, and trust was positively associated with management acceptance. Collectively, our results indicate a mixed-media campaign by state wildlife agencies could improve CWD management acceptance.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10871209.2025.2589886","usgsCitation":"McEachran, M., Hoven, B.M., Feehan, M., and DiRenzo, G.V., 2026, Chronic wasting disease (CWD) knowledge, risk perception, and management acceptance are influenced by media engagement and trust among deer hunters in Massachusetts: Human Dimensions of Wildlife, https://doi.org/10.1080/10871209.2025.2589886.","ipdsId":"IP-156850","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":504180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10871209.2025.2589886","text":"Publisher Index Page"},{"id":503950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.2571070611136,\n 42.76780770024638\n ],\n [\n -73.54406975005473,\n 42.05346733008463\n ],\n [\n -71.41595395377722,\n 42.016471073632175\n ],\n [\n -71.09006086742083,\n 41.508469701988034\n ],\n [\n -70.79943751691263,\n 41.263710237026146\n ],\n [\n -69.96748465016458,\n 41.129859096876636\n ],\n [\n -69.71431782412303,\n 41.55217473089283\n ],\n [\n -70.48530007759994,\n 42.87610528654483\n ],\n [\n -71.03065266749265,\n 42.870080386740064\n ],\n [\n -71.21310496793963,\n 42.800893123216866\n ],\n [\n -71.19873720838875,\n 42.683582499756895\n ],\n [\n -73.2571070611136,\n 42.76780770024638\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"McEachran, Margaret C. 0000-0002-8390-451X","orcid":"https://orcid.org/0000-0002-8390-451X","contributorId":346535,"corporation":false,"usgs":true,"family":"McEachran","given":"Margaret C.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":960836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoven, Brian M.","contributorId":346541,"corporation":false,"usgs":false,"family":"Hoven","given":"Brian","middleInitial":"M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":960971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feehan, Martin J. R","contributorId":351842,"corporation":false,"usgs":false,"family":"Feehan","given":"Martin J. R","affiliations":[{"id":47540,"text":"Massachusetts Division of Fisheries & Wildlife","active":true,"usgs":false}],"preferred":false,"id":960838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":960839,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273904,"text":"70273904 - 2026 - Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin","interactions":[],"lastModifiedDate":"2026-02-13T15:44:06.039327","indexId":"70273904","displayToPublicDate":"2026-02-07T08:37:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin","docAbstract":"Use of per- and polyfluoroalkyl substances (PFAS) in the petroleum industry could be a cause for concern due to the large volumes of produced water (PW) generated during oil and gas extraction, the reuse of these wastes in water-stressed regions, and adverse health outcomes related to PFAS exposures. However, PW PFAS characterization is nearly absent in the literature, and hydraulic fracturing (HF) chemical disclosures often omit the identities of additives as proprietary. Here we evaluate PFAS in PW samples from three petroleum wells in the Denver Basin during their first year of production. Total concentrations of targeted PFAS (Σ40PFAS) were < 35 ng/L in PW samples, with short-chain PFAS like perfluorobutanoic acid persisting throughout the sampled duration. Analysis of freshwater inputs for hydraulic fracturing (Σ40PFAS ~ 113 ng/L) and mixed fracture fluid (Σ40PFAS ~ 69 ng/L) indicated much of the targeted PFAS content was derived from the input water, and not from HF additives, however samples subjected to oxidation indicated the presence of PFAS precursors that would not be detected by targeted analysis. This study highlights that while PFAS content is low in the studied PWs, the potential for redistribution of PFAS in the environment may be a consideration for reuse applications.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-33394-9","usgsCitation":"Varonka, M., Jubb, A., McDevitt, B., Shelton, J.L., Barnhart, E.P., Akob, D., and Cozzarelli, I.M., 2026, Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin: Scientific Reports, v. 16, 5743, 8 p., https://doi.org/10.1038/s41598-025-33394-9.","productDescription":"5743, 8 p.","ipdsId":"IP-173284","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":500246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-33394-9","text":"Publisher Index Page"},{"id":500087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Nebraska, Wyoming","otherGeospatial":"Denver Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.7394986500792,\n 41.98806529832831\n ],\n [\n -105.7394986500792,\n 39.252214457834185\n ],\n [\n -103.39682614563382,\n 39.252214457834185\n ],\n [\n -103.39682614563382,\n 41.98806529832831\n ],\n [\n -105.7394986500792,\n 41.98806529832831\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2026-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Varonka, Matthew S. 0000-0003-3620-5262","orcid":"https://orcid.org/0000-0003-3620-5262","contributorId":203231,"corporation":false,"usgs":true,"family":"Varonka","given":"Matthew S.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDevitt, Bonnie 0000-0001-8390-0028","orcid":"https://orcid.org/0000-0001-8390-0028","contributorId":291246,"corporation":false,"usgs":true,"family":"McDevitt","given":"Bonnie","email":"","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":955716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelton, Jenna L. 0000-0002-1377-0675","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":366369,"corporation":false,"usgs":false,"family":"Shelton","given":"Jenna","middleInitial":"L.","affiliations":[{"id":87467,"text":"Illinois State Water Survey, Prairie Research Institute, Champaign, IL, USA 61821","active":true,"usgs":false}],"preferred":false,"id":955717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":955719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":955720,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273684,"text":"mcs2026 - 2026 - Mineral commodity summaries 2026","interactions":[],"lastModifiedDate":"2026-05-27T13:45:57.860435","indexId":"mcs2026","displayToPublicDate":"2026-02-06T11:55:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026","displayTitle":"Mineral Commodity Summaries 2026","title":"Mineral commodity summaries 2026","docAbstract":"Each mineral commodity chapter of the 2026 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2025 mineral production data for the world. More than 90 individual minerals and materials are covered by two-page synopses.
Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D.
The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the 2026 MCS are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mcs2026","isbn":"978-1-4113-4643-7","usgsCitation":"U.S. Geological Survey, 2026, Mineral commodity summaries 2026 (ver. 1.3, May 2026): U.S. Geological Survey, 222 p., https://doi.org/10.3133/mcs2026.","productDescription":"Report: 222 p.; Data Release; Data Visualization","numberOfPages":"222","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-185894","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":499639,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://apps.usgs.gov/critical-minerals/mineral-commodities-2026.html","text":"Data visualization"},{"id":498869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/periodicals/mcs2026/coverthb2.jpg"},{"id":499534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/periodicals/mcs2026/mcs2026.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"MCS 2026 PDF"},{"id":499535,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/mineral-commodity-summaries","text":"Mineral Commodity Summaries Prior to 2026"},{"id":500785,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/periodicals/mcs2026/versionHist.txt","size":"1.86 KB","linkFileType":{"id":2,"text":"txt"}},{"id":499654,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119204.htm","linkFileType":{"id":5,"text":"html"}},{"id":499537,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WKQ63T","text":"USGS data release","linkHelpText":"Data release for mineral commodity summaries 2026"},{"id":499536,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/commodity-statistics-and-information","text":"Commodity Statistics and Information"}],"edition":"Version 1.0: February 2026; Version 1.1: March 2026; Version 1.2: April 2026; Version 1.3: May 2026","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"Using Alaskan lake sediment oxygen isotope records (δ18O), which trace the δ18O of precipitation, we establish that abrupt atmospheric shifts occurred during the last deglacial period in the North Pacific-Arctic. The robust lake δ18O chronologies confidently correlate Younger-Dryas (YD) atmospheric adjustments in Alaska with Greenland ice-core records and their seasonal sensitivity are consistent with cooling during winter. In contrast, abrupt δ18O decreases during the late Holocene observed in our records, of similar magnitude as the YD, are best explained by atmospheric modes involving long-distance transport of sub-tropical Pacific moisture. Our sediment cores are among the most reliably dated records yet produced in the circum-Arctic and show that similar decreases in δ18O of winter precipitation during the YD and late Holocene were driven by different atmospheric teleconnections. These results underscore major roles for seasonality and atmospheric patterns in the conceptual understanding of global scale climate oscillations, both past and future.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-026-68841-2","usgsCitation":"Anderson, L., Finney, B.P., and Baxter, W.B., 2026, Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals: Nature Communications, v. 17, 2287, 11 p., https://doi.org/10.1038/s41467-026-68841-2.","productDescription":"2287, 11 p.","ipdsId":"IP-173518","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":502072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-026-68841-2","text":"Publisher Index Page"},{"id":501859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.5838715688011,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 61.71714669073339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -54.47050647646307,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 76.12487765561002\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":368960,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":368961,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","middleInitial":"P.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":958186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, W. Brad","contributorId":368962,"corporation":false,"usgs":false,"family":"Baxter","given":"W.","middleInitial":"Brad","affiliations":[{"id":87683,"text":"U.S. Army Corps of Engineers, Cold Regions Research and Engineering Lab","active":true,"usgs":false}],"preferred":false,"id":958187,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273856,"text":"70273856 - 2026 - Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering","interactions":[],"lastModifiedDate":"2026-02-09T15:15:20.251915","indexId":"70273856","displayToPublicDate":"2026-02-06T09:07:55","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23294,"text":"Wind Energy","active":true,"publicationSubtype":{"id":10}},"title":"Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering","docAbstract":"A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.
","language":"English","publisher":"Wiley","doi":"10.1002/we.70099","usgsCitation":"Rand, J., Kramer, L., Hoen, B., Diffendorfer, J., and Garrity, C., 2026, Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering: Wind Energy, v. 29, no. 3, e70099, 13 p., https://doi.org/10.1002/we.70099.","productDescription":"e70099, 13 p.","ipdsId":"IP-182443","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/we.70099","text":"Publisher Index Page"},{"id":499676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Rand, Joseph","contributorId":290223,"corporation":false,"usgs":false,"family":"Rand","given":"Joseph","affiliations":[{"id":41633,"text":"DOE Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":955277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kramer, Louisa 0000-0002-6776-9768","orcid":"https://orcid.org/0000-0002-6776-9768","contributorId":204878,"corporation":false,"usgs":true,"family":"Kramer","given":"Louisa","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoen, Ben 0000-0002-9512-5572","orcid":"https://orcid.org/0000-0002-9512-5572","contributorId":204879,"corporation":false,"usgs":false,"family":"Hoen","given":"Ben","email":"","affiliations":[{"id":37001,"text":"DOE Lawrence Berkeley National Labs","active":true,"usgs":false}],"preferred":false,"id":955279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":223504,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrity, Christopher 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":220994,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955281,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273858,"text":"70273858 - 2026 - Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations","interactions":[],"lastModifiedDate":"2026-02-09T15:28:29.171335","indexId":"70273858","displayToPublicDate":"2026-02-06T08:20:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23297,"text":"Data Science in Science","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations","docAbstract":"Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.
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Besides competition for resources, carp may also have disadvantageous nutrition for predators. One biochemical aspect to consider in carp is production of the enzyme thiaminase that cleaves thiamine (vitamin B1), making it unavailable to most vertebrates. The function of thiaminase within prey fishes is unclear, but roughly half of all fishes tested have measurable thiaminase activity. Predators consuming large volumes of prey with high thiaminase activity can develop thiamine deficiency, ultimately leading to offspring mortality. Three invasive carp (black carp, grass carp, and bighead carp) have no published thiaminase data. We tested juvenile (<160 mm standard length) black carp (n = 38), bighead carp (n = 7), grass carp (n = 50), and silver carp (n = 50) for thiaminase activity. All four species had measurable activity; however, grass carp had statistically higher thiaminase activity (p < 0.001; median = 61 nmol/g/min) than the other three species. Silver carp had the second highest thiaminase activity (14 nmol/g/min). Bighead (2.7 nmol/g/min) and black (2.2 nmol/g/min) carp had the lowest thiaminase activity; activities were often near detection limits. Predators with diets heavily composed of grass carp or silver carp may experience thiamine deficiency, though seasonal variation in carp size and other food source availability may determine potential effects of invasive carp predation in Great Lakes food webs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2026.102751","usgsCitation":"Rowland, F.E., Byrd, C.G., and Kroboth, P., 2026, Thiaminase I activity is high in grass and silver carp, but negligible in bighead and black carp: Journal of Great Lakes Research, v. 52, no. 1, 102751, 8 p., https://doi.org/10.1016/j.jglr.2026.102751.","productDescription":"102751, 8 p.","ipdsId":"IP-183322","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":501233,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274235/images"},{"id":501232,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274235/70274235.XML"},{"id":501231,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274235/full"},{"id":501229,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rowland, Freya Elizabeth 0000-0002-1041-5301","orcid":"https://orcid.org/0000-0002-1041-5301","contributorId":302395,"corporation":false,"usgs":true,"family":"Rowland","given":"Freya","email":"","middleInitial":"Elizabeth","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Curtis G. 0000-0002-5124-5652","orcid":"https://orcid.org/0000-0002-5124-5652","contributorId":210798,"corporation":false,"usgs":true,"family":"Byrd","given":"Curtis","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276519,"text":"70276519 - 2026 - Occupancy rates of river otters (Lontra canadensis) in the St. Louis River Area of Concern","interactions":[],"lastModifiedDate":"2026-06-10T15:19:10.257613","indexId":"70276519","displayToPublicDate":"2026-02-05T12:26:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":24810,"text":"IUCN/SSC Otter Specialist Group Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Occupancy rates of river otters (Lontra canadensis) in the St. Louis River Area of Concern","title":"Occupancy rates of river otters (Lontra canadensis) in the St. Louis River Area of Concern","docAbstract":"The St. Louis River Area of Concern (AOC), an estuarine system along the northeastern Minnesota-Wisconsin border, experienced significant ecological disturbances and degradation from unregulated industrial development during the 19th and 20th centuries. Recent restoration and remediation efforts in the AOC have led to substantial improvements in water quality, habitat, and fisheries populations. However, the status of wildlife populations following restoration efforts in the AOC remain largely unknown. We used remote cameras to estimate occupancy rates of river otters Lontra canadensis in the AOC and at two reference areas that had not been subjected to historical degradation. Because river otters occupy a high trophic level within these systems, we hypothesized that they would be an effective indicator species of overall habitat quality and recovery. Using data collected from June 2015 to February 2016, we developed single-season occupancy models for both summer and winter seasons. We found no differences in occupancy between the AOC and the reference sites, suggesting that river otter populations within the AOC were comparable to those in unaffected areas. Our results indicate that habitat restoration and remediation efforts in the St. Louis River estuary have been successful in promoting healthy wildlife populations.
","language":"English","publisher":"IUCN/SSC Otter Specialist Group","usgsCitation":"Evans, B.E., Tucker, M.C., Van Deelen, T.R., and Crimmins, S.M., 2026, Occupancy rates of river otters (Lontra canadensis) in the St. Louis River Area of Concern: IUCN/SSC Otter Specialist Group Bulletin, v. 43, no. 1, p. 24-34.","productDescription":"11 p.","startPage":"24","endPage":"34","ipdsId":"IP-152860","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":505271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":505201,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iucnosgbull.org/Volume43/Vol43_Iss1_Index.html"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Boulder Lake, St. Croix River, St. Louis River Area of Concern","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.94600196159826,\n 46.77005207817896\n ],\n [\n -92.37221823661014,\n 46.77005207817896\n ],\n [\n -92.37221823661014,\n 46.026349615068455\n ],\n [\n -91.94600196159826,\n 46.026349615068455\n ],\n [\n -91.94600196159826,\n 46.77005207817896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Bryn E.","contributorId":371903,"corporation":false,"usgs":false,"family":"Evans","given":"Bryn","middleInitial":"E.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":962565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Madeleine C.","contributorId":371904,"corporation":false,"usgs":false,"family":"Tucker","given":"Madeleine","middleInitial":"C.","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":962566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Deelen, Timothy R.","contributorId":371905,"corporation":false,"usgs":false,"family":"Van Deelen","given":"Timothy","middleInitial":"R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":962567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":962568,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275576,"text":"70275576 - 2026 - Weather, water, and precipitation","interactions":[],"lastModifiedDate":"2026-05-04T15:43:51.730851","indexId":"70275576","displayToPublicDate":"2026-02-05T10:40:54","publicationYear":"2026","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"Weather, water, and precipitation","docAbstract":"No abstract available.
","largerWorkTitle":"Mountain sheep in North America: Biology, ecology, conservation, and management","language":"English","publisher":"CRC Press","usgsCitation":"Cain, J.W., and van de Kerk, M., 2026, Weather, water, and precipitation, chap. 12 of Mountain sheep in North America: Biology, ecology, conservation, and management.","ipdsId":"IP-174390","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":503940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Krausman, Paul R.","contributorId":356094,"corporation":false,"usgs":false,"family":"Krausman","given":"Paul R.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":960968,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jex, William","contributorId":371079,"corporation":false,"usgs":false,"family":"Jex","given":"William","affiliations":[],"preferred":false,"id":960969,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":960926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van de Kerk, Madelon","contributorId":371051,"corporation":false,"usgs":false,"family":"van de Kerk","given":"Madelon","affiliations":[{"id":38118,"text":"Western Colorado University","active":true,"usgs":false}],"preferred":false,"id":960927,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273385,"text":"sir20255104 - 2026 - Estimating the magnitude and frequency of floods at ungaged locations on urban streams in Tennessee and parts of Alabama, Georgia, Mississippi, North Carolina, and South Carolina, using data through the 2022 water year","interactions":[],"lastModifiedDate":"2026-02-05T22:06:06.078649","indexId":"sir20255104","displayToPublicDate":"2026-02-05T08:41:23","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":"2025-5104","displayTitle":"Estimating the Magnitude and Frequency of Floods at Ungaged Locations on Urban Streams in Tennessee and Parts of Alabama, Georgia, Mississippi, North Carolina, and South Carolina, Using Data Through the 2022 Water Year","title":"Estimating the magnitude and frequency of floods at ungaged locations on urban streams in Tennessee and parts of Alabama, Georgia, Mississippi, North Carolina, and South Carolina, using data through the 2022 water year","docAbstract":"In 2024, the U.S. Geological Survey, in cooperation with the Tennessee Department of Transportation, updated the methods for predicting the magnitude and frequency of floods at ungaged locations on streams in urban areas in Tennessee. The study area included 136 streamgages in urban areas in Tennessee, Mississippi, Alabama, Georgia, South Carolina, and North Carolina that had at least 10 percent developed imperviousness in their basins as indicated by data from the 2011 National Land Cover Database. Regression equations were developed to predict streamflows corresponding to the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs) and were incorporated into the StreamStats application. In generalized least-squares regression, the base-10 logarithm of drainage area, the percentages of the streamgage basins in developed land use, and the percentages of the streamgage basins in the Piedmont and Ridge and Valley Level 3 ecoregions were statistically significant in explaining the variability in annual peak streamflows in the study area. Drainage areas ranged from 0.164 to 93.4 square miles, the percentage of the streamgage basins in developed land use ranged from 26 to 100 percent, and the percentage of the streamgage basins in Piedmont and Ridge and Valley Level 3 ecoregions ranged from 0 to 100 percent. Pseudo R-squared values for the regression equations ranged from 0.86, or 86 percent, for the 50- and 20-percent AEPs (2- and 5-year floods) to 0.71, or 71 percent, for the 0.2-percent AEP (500-year flood). The average variance of prediction (in log base-10 units) ranged from 0.023 for the 20- and 10-percent AEPs to 0.05 for the 0.2-percent AEP. The average variance of prediction can be reported as a percentage of the predicted value, known as the standard error of prediction, which ranged from 35.8 percent for the 20-percent AEP (5-year flood) to 55.4 percent for the 0.2-percent AEP (500-year flood). Methods are presented for estimating annual peak streamflows for gaged locations, ungaged locations on gaged streams, and locations on ungaged streams.
Contact Us- USGS Publications Warehouse
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
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Digital flood-inundation maps for a 2.7-mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water-surface profiles were computed for the stream reach by using a one-dimensional, steady-state, step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00-foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water-surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile.
The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood-mitigation strategies and to define flood-hazard areas to help protect life and property, to coordinate flood-response activities such as evacuations and road closures, and to aid post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255112","usgsCitation":"Ostheimer, C.J., Torres-Garcia, L.M., and Gomez-Fragoso, J.M., 2026, Flood-inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026: U.S. Geological Survey Scientific Investigations Report 2025–5112, 16 p., https://doi.org/10.3133/sir20255112.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179822","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":499274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5112/coverthb.jpg"},{"id":499277,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255112/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5112 HTML"},{"id":499276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5112/sir20255112.pdf","size":"3.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5112 PDF"},{"id":499609,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119202.htm","linkFileType":{"id":5,"text":"html"}},{"id":499280,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1IZ6D5V","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for Río Grande De Loíza in Caguas, Puerto Rico"},{"id":499279,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5112/images/"},{"id":499278,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5112/sir20255112.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5112 XML"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.09390482728071,\n 18.33190261334512\n ],\n [\n -66.09390482728071,\n 18.134783495693256\n ],\n [\n -65.97456945279221,\n 18.134783495693256\n ],\n [\n -65.97456945279221,\n 18.33190261334512\n ],\n [\n -66.09390482728071,\n 18.33190261334512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229-1737
Invasive species within North America, particularly wild pigs (Sus scrofa), pose a serious threat to native ecosystems through both direct and indirect impacts. Wild pigs are a large-bodied omnivorous species native to Eurasia and introduced to North America. Using DNA metabarcoding of fecal samples, we investigated the diet of wild pigs at a bottomland hardwood forest ecosystem within Felsenthal National Wildlife Refuge in southern Arkansas. We found that the wild pig diet was diverse and included at least 74 plant families and 106 genera, dominated by plant matter with Fagaceae (oaks and hickories), Poaceae (grasses), and Asteraceae (asters, sunflowers, and daisies) comprising over 50% of total dietary detections. Hard mast was a primary food source in fall and winter, while herbaceous vegetation peaked in spring. We documented DNA from 23 species of vertebrates in wild pig fecal samples, including mammals, birds, fish, frogs, and turtles. Vertebrate matter was most frequently detected in autumn. Vertebrate consumption constituted ~17% of wild pig diet by relative read abundance. Our results highlighted the potential long-term ecological consequences of wild pig foraging behaviors, particularly competition for critical food resources with native wildlife and impact on forest regeneration through the consumption of mast. Understanding dietary dynamics is crucial for managing wild pig populations and mitigating impacts on vulnerable ecosystems and wildlife.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.70019","usgsCitation":"Wilson, K., Chiavacci, S.J., Roberts, C.P., and DeGregorio, B.A., 2026, Seasonal variation in wild pig (Sus scrofa) diet revealed by DNA metabarcoding: Wildlife Society Bulletin, v. 50, no. 1, e70019, 22 p., https://doi.org/10.1002/wsb.70019.","productDescription":"e70019, 22 p.","ipdsId":"IP-176314","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.70019","text":"Publisher Index Page"},{"id":501862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Felsenthal National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.25663096909476,\n 33.2889631983969\n ],\n [\n -92.25663096909476,\n 33.05047632468441\n ],\n [\n -92.0547025523673,\n 33.05047632468441\n ],\n [\n -92.0547025523673,\n 33.2889631983969\n ],\n [\n -92.25663096909476,\n 33.2889631983969\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Kenneth","contributorId":341075,"corporation":false,"usgs":false,"family":"Wilson","given":"Kenneth","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":958330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiavacci, Scott J. 0000-0003-3579-8377","orcid":"https://orcid.org/0000-0003-3579-8377","contributorId":206161,"corporation":false,"usgs":true,"family":"Chiavacci","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":958333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":958331,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274663,"text":"70274663 - 2026 - Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland","interactions":[],"lastModifiedDate":"2026-04-03T15:15:07.218513","indexId":"70274663","displayToPublicDate":"2026-02-04T10:03:52","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":"Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland","docAbstract":"The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JB032100","usgsCitation":"Fabbrizzi, A., Maloney, J.M., Derosier, B.J., and Keith, B., 2026, Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland: JGR Solid Earth, v. 131, no. 2, e2025JB032100, 30 p., https://doi.org/10.1029/2025JB032100.","productDescription":"e2025JB032100, 30 p.","ipdsId":"IP-178847","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jb032100","text":"Publisher Index Page"},{"id":502163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cortes Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.25,\n 32.575\n ],\n [\n -119.25,\n 32.575\n ],\n [\n -119.25,\n 31.75\n ],\n [\n -118.25,\n 31.75\n ],\n [\n -118.25,\n 32.575\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"131","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fabbrizzi, Andrea 0000-0003-3166-1015","orcid":"https://orcid.org/0000-0003-3166-1015","contributorId":369216,"corporation":false,"usgs":false,"family":"Fabbrizzi","given":"Andrea","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":958617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Jillian M. 0000-0001-8223-4676","orcid":"https://orcid.org/0000-0001-8223-4676","contributorId":261208,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":958618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Derosier, Boe Jay 0000-0003-1517-4129","orcid":"https://orcid.org/0000-0003-1517-4129","contributorId":369217,"corporation":false,"usgs":true,"family":"Derosier","given":"Boe","middleInitial":"Jay","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Bradley","contributorId":369218,"corporation":false,"usgs":false,"family":"Keith","given":"Bradley","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":958620,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273876,"text":"70273876 - 2026 - Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave","interactions":[],"lastModifiedDate":"2026-02-11T15:25:43.001543","indexId":"70273876","displayToPublicDate":"2026-02-04T09:17:59","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave","docAbstract":"Chinook salmon population declines span their geographic range with climate hypothesized as a major driver. Concerns of warming freshwater temperatures in their northern range gained urgency during 2019 when a heatwave coincided with premature mortality. This study examined heat stress during the 2019 heatwave compared to subsequent years and described water temperatures in western Alaska to understand the degree to which freshwater temperatures may be a stressor. Heat stress was prevalent among Chinook salmon captured in the 2019 heatwave (Kuskokwim tributaries: 90% in Kwethluk and 63% Takotna river), and variable in subsequent years (∼8% to 60% across Kuskokwim tributaries and Norton Sound rivers). A review of water temperature data indicated that potentially stressful temperatures (≥18 °C) were most common and prolonged in the Yukon River, moderately common and prolonged in the Kuskokwim River, and relatively rare in the Norton Sound region. Water temperatures in 2019 broke several records for overall maximum and frequency of temperatures ≥ 18 °C. Migration water temperatures and heat stress in northern Pacific salmon habitats vary more widely than previously recognized (up to 25 °C).
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0109","usgsCitation":"von Biela, V.R., Regish, A.M., McCormick, S.D., Spaeder, J., Whitworth, K., Leon, J., Gillikin, D., Liller, Z., Ivanoff, R., Bell, J., Larson, S.D., Carey, M.P., and Zimmerman, C.E., 2026, Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave: Canadian Journal of Fisheries and Aquatic Sciences, https://doi.org/10.1139/cjfas-2025-0109.","ipdsId":"IP-171279","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":499750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"western Alaska","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":955346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science 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Kevin","contributorId":366142,"corporation":false,"usgs":false,"family":"Whitworth","given":"Kevin","affiliations":[{"id":87364,"text":"Kuskokwim River Inter-Tribal Fish Commission","active":true,"usgs":false}],"preferred":false,"id":955350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leon, Justin","contributorId":366143,"corporation":false,"usgs":false,"family":"Leon","given":"Justin","affiliations":[{"id":87364,"text":"Kuskokwim River Inter-Tribal Fish Commission","active":true,"usgs":false}],"preferred":false,"id":955351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gillikin, Daniel","contributorId":366144,"corporation":false,"usgs":false,"family":"Gillikin","given":"Daniel","affiliations":[{"id":87365,"text":"Native Village of Napaimute","active":true,"usgs":false}],"preferred":false,"id":955352,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liller, Zachary","contributorId":290701,"corporation":false,"usgs":false,"family":"Liller","given":"Zachary","email":"","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":955353,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ivanoff, Renae","contributorId":264889,"corporation":false,"usgs":false,"family":"Ivanoff","given":"Renae","affiliations":[{"id":54574,"text":"norton sound","active":true,"usgs":false}],"preferred":false,"id":955354,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bell, Jenefer","contributorId":366145,"corporation":false,"usgs":false,"family":"Bell","given":"Jenefer","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":955355,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Larson, Sean D.","contributorId":366146,"corporation":false,"usgs":false,"family":"Larson","given":"Sean","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":955356,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":955357,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":955358,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70273695,"text":"sir20255098 - 2026 - Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23","interactions":[],"lastModifiedDate":"2026-02-11T18:58:23.302299","indexId":"sir20255098","displayToPublicDate":"2026-02-04T09:07:41","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":"2025-5098","displayTitle":"Water-Budget Simulations for Selected Watersheds in Cameron County, Texas, 2022–23","title":"Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Brownsville, Texas, configured and calibrated a set of hydrologic models for a 217-square-mile study area in Cameron County in south Texas during 2022–23. The models were used for estimating runoff and quantities of water diverted from the Rio Grande/Rio Bravo del Norte (hereinafter referred to as the “Rio Grande”) to maintain water-surface elevations in the canals and resacas (former distributary channels cut off from the main channel of the Rio Grande). Resacas provide habitat to aquatic species and help reduce the effects of flooding.
Because of the large size of the study area and diversity of hydrologic conditions, the study area was divided into 11 watersheds, and separate hydrologic models were developed for 9 of the watersheds. Six of the nine modeled watersheds are drained mostly by canals (canal watersheds), and three of the modeled watersheds drain to resacas (resaca watersheds). The Hydrological Simulation Program—FORTRAN was selected for modeling the study area watersheds because it is flexible in simulating a wide variety of watershed conditions.
The models were calibrated with streamflow data collected during 2022–23. The calibrated models were used to simulate water budgets (streamflow, evapotranspiration, water-storage volumes, and water diversions and withdrawals) during 2022–23. Model simulations showed that the resaca watersheds required more diversions from the Rio Grande and released less runoff than did the canal watersheds. Management practices maintaining resaca water levels constrained their runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255098","issn":"2328-0328","collaboration":"Prepared in cooperation with the City of Brownsville, Texas","usgsCitation":"Ockerman, D.J., and Choi, N., 2026, Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23: U.S. Geological Survey Scientific Investigations Report 2025–5098, 37 p., https://doi.org/10.3133/sir20255098.","productDescription":"Report: viii, 37 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-167896","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":499763,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255098/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5098 HTML"},{"id":499608,"rank":6,"type":{"id":36,"text":"NGMDB Index 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Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"Understanding the local to regional history of extreme events such as debris flows and floods provides context to plan for and mitigate these hazards to life, property, and infrastructure. The Klamath Mountains of northwestern California have experienced both debris flows and devastating wildfires. Whiskeytown National Recreation Area (WHIS) is at the heart of this range and has a wealth of debris flow–related landforms. Gaining an understanding of prehistoric flows and their relationship with fire or other potential triggers can help mitigate future problems. Optically stimulated luminescence and radiocarbon analyses from sediment and entrained organics in undisturbed facies, including beneath partially buried boulders, establishes a chronology of paleo-events in WHIS. The levee deposits indicate a repetition of debris flows during the latest Holocene, every 125–150 years, since 850 yr. Larger flows occurred, with a record elucidated from debris-flow deposits along Clear Creek, with Middle Holocene ages, ca. 2600 to 5500 yr, most of which have sufficient concentrations of charcoal to indicate origins as postfire debris flows. Deposits at higher elevations show events from the latest Pleistocene ca. 13,000 yr. This geochronology indicates that these are not singular events but are relatively common and inherent to the geomorphic processes shaping this landscape.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2025.10064","usgsCitation":"Wood, J., Mahan, S.A., East, A.E., Bilderback, E., Krolczyk, E.T., Rasmussen, B.A., Zyatitsky, K.S., and Hallas, L.(., 2026, Geochronologic data reveal Late Pleistocene to Holocene debris-flow history and wildfire association within Whiskeytown National Recreation Area, Klamath Mountains, northern California: Quaternary Research, 21 p., https://doi.org/10.1017/qua.2025.10064.","productDescription":"21 p.","ipdsId":"IP-176240","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499931,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/qua.2025.10064","text":"Publisher Index Page"},{"id":499584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Klamath Mountains, Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.63689471598963,\n 40.6731703155468\n ],\n [\n -122.63689471598963,\n 40.56431461436682\n ],\n [\n -122.47862213398994,\n 40.56431461436682\n ],\n [\n -122.47862213398994,\n 40.6731703155468\n ],\n [\n -122.63689471598963,\n 40.6731703155468\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, John R. \"Jack\" 0000-0002-0270-6328","orcid":"https://orcid.org/0000-0002-0270-6328","contributorId":359808,"corporation":false,"usgs":false,"family":"Wood","given":"John R. \"Jack\"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":955111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":219600,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":955113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bilderback, Eric Leland 0000-0002-2027-5699","orcid":"https://orcid.org/0000-0002-2027-5699","contributorId":349936,"corporation":false,"usgs":true,"family":"Bilderback","given":"Eric Leland","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"preferred":true,"id":955114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krolczyk, Emma Taylor 0000-0002-7163-4348","orcid":"https://orcid.org/0000-0002-7163-4348","contributorId":291354,"corporation":false,"usgs":true,"family":"Krolczyk","given":"Emma","email":"","middleInitial":"Taylor","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955115,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rasmussen, Brian A.","contributorId":365987,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Brian","middleInitial":"A.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":955116,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zyatitsky, Karina S.","contributorId":365988,"corporation":false,"usgs":false,"family":"Zyatitsky","given":"Karina","middleInitial":"S.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":955117,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hallas, Leticia (Contractor) 0009-0004-4071-2456","orcid":"https://orcid.org/0009-0004-4071-2456","contributorId":359806,"corporation":false,"usgs":true,"family":"Hallas","given":"Leticia","middleInitial":"(Contractor)","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":955118,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273882,"text":"70273882 - 2026 - Ensemble methods for history matching and uncertainty quantification with a watershed model","interactions":[],"lastModifiedDate":"2026-02-11T15:28:04.157861","indexId":"70273882","displayToPublicDate":"2026-02-04T08:23:01","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble methods for history matching and uncertainty quantification with a watershed model","docAbstract":"History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and qualitatively compare the results and performance to the stepwise history matching approach. In the latter approach, subsets of parameters and observations were sequentially calibrated to a diverse range of observations to mitigate non-uniqueness and local minima. In iES, localization simulates the same causal connections between parameters and observations without the need (and computational cost) of sequential history matching steps. iES uses a weighted sum-of-squared-errors objective function which allows differential weighting of multiple data sources. Formal adoption of range observation also pushes results to within ranges of observation values rather than discrete values. Overall, the ensemble approach performs similarly to the stepwise approach. Both approaches performed poorly for the cutout representing a snowmelt-dominated watershed, indicating a structural issue in the process representation of the model. The main advantage of iES is quantification of uncertainty in both the history matching and the predictions of interest.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.70086","usgsCitation":"Fienen, M., Long, A.J., Markovich, K.H., Haj, A.E., and Barker, M., 2026, Ensemble methods for history matching and uncertainty quantification with a watershed model: Journal of the American Water Resources Association, v. 62, no. 1, e70086, 18 p., https://doi.org/10.1111/1752-1688.70086.","productDescription":"e70086, 18 p.","ipdsId":"IP-181945","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n 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world","interactions":[],"lastModifiedDate":"2026-03-23T14:47:40.529718","indexId":"70273852","displayToPublicDate":"2026-02-04T08:07:16","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23291,"text":"FEBS Letters","active":true,"publicationSubtype":{"id":10}},"title":"A fresh perspective - Advancing fish immunotoxicology in a complex world","docAbstract":"Understanding how environmental changes affect the health of organisms and ecosystems is complex, but recent interdisciplinary advances and the recognition of immune function as a dynamic mediator offer exciting progress. Environmental immunotoxicology in teleost fishes is evolving beyond cataloguing stressors towards a mechanistic, integrative framework that leverages omics, in vivo tracking and cross-disciplinary modelling. However, knowledge gaps in immune mechanisms, toxicokinetics and multi-stressor interactions remain. The present work highlights these gaps, advocating for immune function as both a mechanistic lens and an integrative health indicator. Such a framework can improve predictive risk assessments, management strategies and our understanding of contaminant effects on resilience, disease susceptibility and population viability. While challenges remain, the field is poised for significant growth through collaborative innovation and advancing technology.
","language":"English","publisher":"FEBS Press","doi":"10.1002/1873-3468.70296","usgsCitation":"Smith, C.R., Burattin, L., Iglesias, N.R., Sullivan, R., Rice, C.D., Segner, H., and Tort, L., 2026, A fresh perspective - Advancing fish immunotoxicology in a complex world: FEBS Letters, v. 600, no. 5, p. 572-590, https://doi.org/10.1002/1873-3468.70296.","productDescription":"19 p.","startPage":"572","endPage":"590","ipdsId":"IP-180147","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499675,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499935,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/1873-3468.70296","text":"Publisher Index Page"}],"volume":"600","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":true,"id":955256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burattin, Laura","contributorId":366092,"corporation":false,"usgs":false,"family":"Burattin","given":"Laura","affiliations":[{"id":66158,"text":"University of Namur","active":true,"usgs":false}],"preferred":false,"id":955257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iglesias, Nuria Ruiz","contributorId":366093,"corporation":false,"usgs":false,"family":"Iglesias","given":"Nuria","middleInitial":"Ruiz","affiliations":[{"id":87357,"text":"Autonomous University of Barcelona","active":true,"usgs":false}],"preferred":false,"id":955258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Roisin","contributorId":366094,"corporation":false,"usgs":false,"family":"Sullivan","given":"Roisin","affiliations":[{"id":84564,"text":"The University of Sydney","active":true,"usgs":false}],"preferred":false,"id":955259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Charles D.","contributorId":366095,"corporation":false,"usgs":false,"family":"Rice","given":"Charles","middleInitial":"D.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":955260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Segner, Helmut","contributorId":366096,"corporation":false,"usgs":false,"family":"Segner","given":"Helmut","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":955261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tort, Lluis","contributorId":169142,"corporation":false,"usgs":false,"family":"Tort","given":"Lluis","email":"","affiliations":[],"preferred":false,"id":955262,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}