{"pageNumber":"12","pageRowStart":"275","pageSize":"25","recordCount":41014,"records":[{"id":70275139,"text":"70275139 - 2026 - Net widening of Southern California beaches","interactions":[],"lastModifiedDate":"2026-04-16T15:31:48.712088","indexId":"70275139","displayToPublicDate":"2026-01-29T10:26:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Net widening of Southern California beaches","docAbstract":"<p><span>Human impacts from dams reduce river sediment fluxes and are primary causes of coastal erosion worldwide. Here we provide new satellite-derived shoreline observation techniques to examine beach area trends across the diverse coastal settings of California. Contrary to global trends, these data reveal that the most heavily urbanized and dammed region of southern California experienced net beach growth of over 2 million m</span><sup>2</sup><span>&nbsp;during 1984-2024. While several beaches experienced severe erosion, overall widening is explained by sufficient sediment supply and concentrated widening from longshore transport captured at coastal structures and in littoral convergence zones. These results indicate that adequate sediment sources exist in this human-modified landscape to mitigate coastal erosion, but that this sediment is not effectively distributed to vulnerable beaches. This highlights the critical role that longshore sediment transport plays in long-term beach trends and illuminates management opportunities for coastal sustainability at the regional scale.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-026-68880-9","usgsCitation":"Warrick, J.A., Vos, K., Buscombe, D.D., Ritchie, A., Vitousek, S., Hachey, T., and Sanders, B., 2026, Net widening of Southern California beaches: Nature Communications, v. 17, 1705, 15 p., https://doi.org/10.1038/s41467-026-68880-9.","productDescription":"1705, 15 p.","ipdsId":"IP-179766","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-026-68880-9","text":"Publisher Index Page"},{"id":502939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.2626309,\n              32.5606682\n            ],\n            [\n              -116.8630481,\n              32.5783916\n            ],\n            [\n              -117.4238661,\n              33.5185381\n            ],\n            [\n              -118.4052976,\n              34.1706348\n            ],\n            [\n              -119.3937376,\n              34.4774706\n            ],\n            [\n              -120.5293941,\n              34.6102787\n            ],\n            [\n              -120.4242407,\n              34.3849575\n            ],\n            [\n              -119.7232182,\n              34.3618132\n            ],\n            [\n              -119.3376558,\n              34.1880274\n            ],\n            [\n              -119.1694104,\n              34.0603564\n            ],\n            [\n              -118.7768378,\n              33.938309\n            ],\n            [\n              -118.5314799,\n              33.9208593\n            ],\n            [\n              -118.440347,\n              33.6936888\n            ],\n            [\n              -118.2160198,\n              33.6295061\n            ],\n            [\n              -118.0267437,\n              33.6119934\n            ],\n            [\n              -117.5500484,\n              33.2258157\n            ],\n            [\n              -117.2626309,\n              32.5606682\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2026-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":959618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vos, Kilian 0000-0002-9518-1582","orcid":"https://orcid.org/0000-0002-9518-1582","contributorId":229435,"corporation":false,"usgs":false,"family":"Vos","given":"Kilian","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":959619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":959620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":959621,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":959622,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hachey, Teresa","contributorId":370064,"corporation":false,"usgs":false,"family":"Hachey","given":"Teresa","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":959623,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanders, Brett 0000-0002-1592-5204","orcid":"https://orcid.org/0000-0002-1592-5204","contributorId":370065,"corporation":false,"usgs":false,"family":"Sanders","given":"Brett","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":959624,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70275587,"text":"70275587 - 2026 - Differentiating persistent and intermittent euxinia from the molecular derivatives of green sulfur bacteria carotenoids","interactions":[],"lastModifiedDate":"2026-05-04T15:04:51.502489","indexId":"70275587","displayToPublicDate":"2026-01-28T09:57:01","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12558,"text":"Geochemica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating persistent and intermittent euxinia from the molecular derivatives of green sulfur bacteria carotenoids","docAbstract":"<p><span>Green sulfur bacteria biomarkers that indicate euxinia within the photic zone sometimes co-occur with evidence of contradictory depositional redox conditions, such as oxygen-requiring fossils or bioturbation. Intermittent euxinia may explain this apparent contradiction, and recent studies of modern environments show that green sulfur bacteria dwell in transiently euxinic settings. As a result, new approaches are needed to distinguish green sulfur bacteria biomarkers indicative of persistent versus intermittent euxina in ancient sedimentary samples, which this study addresses by investigating how the distribution of isorenieratene derivatives relates to depositional redox conditions. To accomplish this objective, this study focuses on two drill cores through the Upper Cretaceous Mowry Shale and the Eagle Ford Group. These drill cores are comparably thermally immature according to vitrinite reflectance data, and these formations in these cores capture a spectrum of depositional redox conditions according to multiple organic and inorganic proxies, including newly acquired iron speciation and kerogen organic sulfur data. The results presented here reveal that higher molecular weight diagenetic products of isorenieratene are preferentially preserved under persistent euxinia compared to intermittently euxinic intervals that contain isorenieratene derivatives that are shifted to lower molecular weights. Further, the total inventory of aromatic carotenoid diagenetic products contains features that can be used to identify green sulfur bacteria biomarkers from reworked petrogenic sources. Accordingly, the diagenetic fate of isorenieratene and the distribution of its diagenetic products distinguish persistent versus intermittent euxinia, which can be used to sharpen our evaluation of euxinia in the geologic record.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2025.12.033","usgsCitation":"French, K.L., Hackley, P.C., and Sperling, E.A., 2026, Differentiating persistent and intermittent euxinia from the molecular derivatives of green sulfur bacteria carotenoids: Geochemica et Cosmochimica Acta, v. 415, p. 130-145, https://doi.org/10.1016/j.gca.2025.12.033.","productDescription":"16 p.","startPage":"130","endPage":"145","ipdsId":"IP-179628","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":504170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2025.12.033","text":"Publisher Index Page"},{"id":503932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"415","noUsgsAuthors":false,"publicationDate":"2026-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":false,"id":960952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":960953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sperling, Erik A.","contributorId":371074,"corporation":false,"usgs":false,"family":"Sperling","given":"Erik","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":960954,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70275707,"text":"70275707 - 2026 - Thinking outside the rocks: Subsurface water storage, topography, and land cover are key modulators of large-scale riverine dissolved silicon dynamics","interactions":[],"lastModifiedDate":"2026-05-13T14:17:01.525783","indexId":"70275707","displayToPublicDate":"2026-01-28T09:12:22","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Thinking outside the rocks: Subsurface water storage, topography, and land cover are key modulators of large-scale riverine dissolved silicon dynamics","docAbstract":"<p><span>Riverine dissolved silicon (DSi) dynamics reflect integrated geologic, hydrologic, climatic, and ecological controls. We compiled annual DSi data for 337 rivers across four continents and trained interpretable machine-learning models to predict concentrations and yields from 28 watershed variables. Both models reproduced testing data (</span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;0.85 for concentration and 0.96 for yield) and withheld-site validation (</span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;0.91 and 0.93). Lithology, especially volcanic rock fraction, strongly controlled DSi while subsurface storage, topography, and land cover further shaped DSi dynamics. DSi concentrations and yields exhibited nonlinear responses to basin slope, recession-curve slope, proportion of open-water cover, and nutrient availability. Concentrations showed sharper threshold responses to hydrologic and biotic variables, whereas yields varied more gradually with climate and lithology. These results provide a framework for forecasting DSi under land cover and climate change and for embedding realistic, nonlinear processes in mechanistic models.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL118853","usgsCitation":"Bush, S.A., Johnson, K., Jankowski, K.J., Carey, J.C., Sethna, L.R., Lyon, N., and Sullivan, P.L., 2026, Thinking outside the rocks: Subsurface water storage, topography, and land cover are key modulators of large-scale riverine dissolved silicon dynamics: Geophysical Research Letters, v. 53, no. 2, e2025GL118853, 12 p., https://doi.org/10.1029/2025GL118853.","productDescription":"e2025GL118853, 12 p.","ipdsId":"IP-182450","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":504371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl118853","text":"Publisher Index Page"},{"id":504299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bush, Sidney A. 0000-0002-8359-7927","orcid":"https://orcid.org/0000-0002-8359-7927","contributorId":265930,"corporation":false,"usgs":false,"family":"Bush","given":"Sidney","email":"","middleInitial":"A.","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":961459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Keira 0000-0003-0671-3901","orcid":"https://orcid.org/0000-0003-0671-3901","contributorId":330720,"corporation":false,"usgs":false,"family":"Johnson","given":"Keira","email":"","affiliations":[{"id":78986,"text":"College of Earth, Ocean, and Atmospheric Science, Oregon State University, Corvallis, Oregon, 97331","active":true,"usgs":false}],"preferred":false,"id":961460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":961461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carey, Joanna C. 0000-0003-2365-9185","orcid":"https://orcid.org/0000-0003-2365-9185","contributorId":363158,"corporation":false,"usgs":false,"family":"Carey","given":"Joanna","middleInitial":"C.","affiliations":[{"id":86633,"text":"Babson College","active":true,"usgs":false}],"preferred":false,"id":961462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sethna, Lienne R. 0000-0003-1156-172X","orcid":"https://orcid.org/0000-0003-1156-172X","contributorId":330721,"corporation":false,"usgs":false,"family":"Sethna","given":"Lienne","email":"","middleInitial":"R.","affiliations":[{"id":78987,"text":"St. Croix Watershed Research Station, Marine on St. Croix, Minnesota 55047","active":true,"usgs":false}],"preferred":false,"id":961463,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyon, Nicholas 0000-0003-3905-1078","orcid":"https://orcid.org/0000-0003-3905-1078","contributorId":332697,"corporation":false,"usgs":false,"family":"Lyon","given":"Nicholas","email":"","affiliations":[{"id":79584,"text":"1021 Anacapa St, Santa Barbara, CA 93101","active":true,"usgs":false}],"preferred":false,"id":961464,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sullivan, Pamela L. 0000-0001-8780-8501","orcid":"https://orcid.org/0000-0001-8780-8501","contributorId":330723,"corporation":false,"usgs":false,"family":"Sullivan","given":"Pamela","email":"","middleInitial":"L.","affiliations":[{"id":78986,"text":"College of Earth, Ocean, and Atmospheric Science, Oregon State University, Corvallis, Oregon, 97331","active":true,"usgs":false}],"preferred":false,"id":961465,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273753,"text":"pp1890N - 2026 - Toward a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau","interactions":[{"subject":{"id":70273753,"text":"pp1890N - 2026 - Toward a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau","indexId":"pp1890N","publicationYear":"2026","noYear":false,"chapter":"N","displayTitle":"Toward a Four-Dimensional Petrogenetic Model of a Distributed Volcanic Field on the Southern Edge of the Colorado Plateau","title":"Toward a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau"},"predicate":"IS_PART_OF","object":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"id":1}],"isPartOf":{"id":70259456,"text":"pp1890 - 2024 - Distributed volcanism—Characteristics, processes, and hazards","indexId":"pp1890","publicationYear":"2024","noYear":false,"title":"Distributed volcanism—Characteristics, processes, and hazards"},"lastModifiedDate":"2026-02-05T21:57:24.382918","indexId":"pp1890N","displayToPublicDate":"2026-01-27T15:30:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1890","chapter":"N","displayTitle":"Toward a Four-Dimensional Petrogenetic Model of a Distributed Volcanic Field on the Southern Edge of the Colorado Plateau","title":"Toward a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau","docAbstract":"<p>A detailed characterization of the &gt;3,000 square kilometer (km<sup>2</sup>) Springerville volcanic field, located on the southern tip of the Colorado Plateau in Arizona, United States, with its more than 501 volcanic units and widely distributed &gt;420 cinder cones and lava flows, provides constraints toward an integrated petrogenetic model for the field. Large-volume effusive tholeiitic eruptions at 2–1.5 mega-annum (Ma) transitioned to more numerous, smaller volume alkali olivine basalt (AOB) events at 1.5–1.0 Ma, with increasing abundances of evolved alkalic rocks (EARs), and a final 1.0–0.3 Ma period dominated by smaller volume, more explosive alkalic eruptions.</p><p>Early large-scale melting in a relatively enriched lithospheric mantle (EM) source generated large-volume effusive tholeiitic magmas. Depths of tholeiite magma generation average about 90 kilometers (km) across the field, but depths for individual units decreased southward, consistent with lithospheric thinning toward the Colorado Plateau margin. Early and middle-stage transitional basalts, alkali olivine basalts (AOBs), and basanites originate from a progressively deeper (&gt;100 km) region in a prevalent mantle (PREMA)-like asthenospheric source produced by increasingly smaller degrees of melting, as low as about 2 percent. The chemical signature of the basanites is consistent with small degrees of melting in a carbonated, asthenospheric source to depths of about 140 km. As heat waned, the last phase of volcanism was dominated by more explosive EARs derived at shallower lithospheric pressures but that have isotopic and trace element similarities to the deeper asthenospheric magmas. This suggests mixing between deeper basanitic and shallower tholeiitic magmas. With waning heat, eruptions became more localized along alignments, likely related to boundaries between blocks of Proterozoic crust with differing properties that affected magma ascent.</p><p>The petrogenetic patterns are consistent with a variety of processes. Basin and Range Province extension, melting, and heat-induced weakening progressively eroded the Colorado Plateau’s thicker lithosphere, giving rise to relatively high degrees of partial melting from shallower (&lt;90 km) sources that produced the early large volumes of effusive tholeiitic magma. Possible lithosphere delamination and removal, and a resulting steep boundary step with the asthenosphere, may have given rise to mantle edge convection, resulting in the mixing of basanitic and tholeiitic magmas. With plate motion, shear-driven upwelling likely gave an eastward component to convection, affecting relative amounts of melting at the field’s western boundary and corresponding with volcanism moving eastward during times of peak vent production by eruption of alkalic lavas, giving rise to more explosive and lower volume eruptions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1890N","usgsCitation":"Mnich, M.E., and Condit, C.D., 2026, Toward a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau, chap. 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 \"}}]}","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/volcano-science-center\" data-mce-href=\"https://www.usgs.gov/centers/volcano-science-center\">Volcano Science Center</a><br>U.S. Geological Survey<br>1300 SE Cardinal Court Bldg. 10<br>Vancouver, WA 98683</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2026-01-27","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Mnich, Marissa E.","contributorId":365649,"corporation":false,"usgs":false,"family":"Mnich","given":"Marissa","middleInitial":"E.","affiliations":[{"id":36475,"text":"Sonoma State University","active":true,"usgs":false}],"preferred":false,"id":954539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condit, Christopher D.","contributorId":365650,"corporation":false,"usgs":false,"family":"Condit","given":"Christopher","middleInitial":"D.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":954540,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274233,"text":"70274233 - 2026 - Harvest of long-tailed ducks from an important hunting location on Lake Michigan","interactions":[],"lastModifiedDate":"2026-03-17T19:04:12.850311","indexId":"70274233","displayToPublicDate":"2026-01-27T13:56:25","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Harvest of long-tailed ducks from an important hunting location on Lake Michigan","docAbstract":"<p><span>Annual waterfowl harvest in North America is estimated through a collaborative and strategic process, with federal harvest surveys the primary method of estimation. Sea duck hunters participating in federal harvest surveys represent a small proportion of the overall waterfowl hunting population, limiting the utility of harvest estimates for sea ducks. The long-tailed duck (</span><i>Clangula hyemalis</i><span>) is one such species. To partially address the paucity of long-tailed duck harvest survey information, we conducted in-person hunter surveys from 1 November through 4 December 2016 at a boat launch in Two Rivers, Wisconsin, USA (Lake Michigan), an important area for long-tailed duck harvest within the state. Hunters were present on 15 of 21 survey days, and we surveyed occupants of 62 individual hunting boats on 127 occasions. Long-tailed ducks were the most common (97%) of the 1,431 sea ducks reported harvested by hunters. Hunter harvest of long-tailed ducks averaged 3.8 (95% CI = 3.4, 4.1; range = 0–6) long-tailed ducks/hunter/day. We used count models to evaluate the effects of environmental variables on hunter participation and harvest of long-tailed ducks. Wave height was the most influential predictor variable for hunter participation; an information criterion-based best model (wave height + temperature) indicated that hunter participation decreased by 91.9% (95% CI = 79.3–97.1%) for each 1-m increase in wave height. Long-tailed duck harvest was positively associated with air temperature; the relationship indicated a 9.5% (95% CI = 6.2–12.9%) increase in long-tailed duck harvest with each degree increase in temperature. Our results contribute to the understanding of waterfowl hunter participation, hunter preferences, and harvest on Lake Michigan and can inform managers as they assess regulatory frameworks for sea duck hunting.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70182","usgsCitation":"Fara, L., Beatty, W.S., Gray, B.R., Kenow, K.P., and Eichholz, M.W., 2026, Harvest of long-tailed ducks from an important hunting location on Lake Michigan: Journal of Wildlife Management, v. 90, no. 3, e70182, https://doi.org/10.1002/jwmg.70182.","productDescription":"e70182","ipdsId":"IP-171382","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Two Rivers","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.58814421174469,\n              44.16475294219143\n            ],\n            [\n              -87.58814421174469,\n              44.13885420061274\n            ],\n            [\n              -87.55382762153202,\n              44.13885420061274\n            ],\n            [\n              -87.55382762153202,\n              44.16475294219143\n            ],\n            [\n              -87.58814421174469,\n              44.16475294219143\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Fara, Luke J.","contributorId":194768,"corporation":false,"usgs":false,"family":"Fara","given":"Luke J.","affiliations":[],"preferred":false,"id":957104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beatty, William S. 0000-0003-0013-3113 wbeatty@usgs.gov","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":173946,"corporation":false,"usgs":true,"family":"Beatty","given":"William","email":"wbeatty@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":957107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eichholz, Michael W.","contributorId":171365,"corporation":false,"usgs":false,"family":"Eichholz","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":26877,"text":"Southern Illinois University, Carbondale, IL","active":true,"usgs":false}],"preferred":false,"id":957108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273781,"text":"70273781 - 2026 - Latest Pleistocene to 19th-century earthquakes on bending-moment reverse faults of the Seattle fault zone, Washington","interactions":[],"lastModifiedDate":"2026-01-29T15:05:22.089312","indexId":"70273781","displayToPublicDate":"2026-01-27T07:59:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Latest Pleistocene to 19th-century earthquakes on bending-moment reverse faults of the Seattle fault zone, Washington","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Fault-related folds and their associated secondary faults play a critical yet often underrecognized role in accommodating strain and generating earthquakes in active fold-and-thrust belts. In the Seattle fault zone (SFZ), Washington, USA, we present new paleoseismic, geomorphic, and geophysical evidence for late Pleistocene and Holocene earthquakes on shallow, south-dipping secondary faults—the Lytle Beach and Vasa Park faults—that lie within the hanging wall of the greater SFZ and are on trend with the primary, blind Blakely Harbor fault. Our data show that these structures have ruptured independently, producing localized uplift and deformation at the surface, with the most recent event (RH2) likely occurring in the early nineteenth century. While a temporal overlap between the late Pleistocene RH1 and VP1 earthquakes raises the possibility of a ≥35 km rupture along the Blakely Harbor fault, structural and temporal evidence instead supports independent rupture on individual faults related to folding. We interpret these faults as bending-moment reverse faults that formed within a synclinal hinge zone of the main fault, reflecting mechanical and kinematic influences of the broader fault system. Combined with prior studies, our findings indicate that faulting related to folding dominates the mode of strain release within the SFZ since the late Pleistocene with more frequent earthquake recurrence (∼350 yr) over the past ∼2500 yr.</span></span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B38333.1","usgsCitation":"Angster, S.J., Sherrod, B.L., Pearl, J., Staisch, L.M., Johns, W., and Blakely, R.J., 2026, Latest Pleistocene to 19th-century earthquakes on bending-moment reverse faults of the Seattle fault zone, Washington: GSA Bulletin, 20 p., https://doi.org/10.1130/B38333.1.","productDescription":"20 p.","ipdsId":"IP-169328","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499226,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.25111195305615,\n              48.899230690241126\n            ],\n            [\n              -125.25111195305615,\n              47.269725066793995\n            ],\n            [\n              -121.72996974638943,\n              47.269725066793995\n            ],\n            [\n              -121.72996974638943,\n              48.899230690241126\n            ],\n            [\n              -125.25111195305615,\n              48.899230690241126\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Angster, Stephen J. 0000-0001-9250-8415","orcid":"https://orcid.org/0000-0001-9250-8415","contributorId":225610,"corporation":false,"usgs":true,"family":"Angster","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":954767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":954768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearl, Jessie K. 0000-0002-1556-2159","orcid":"https://orcid.org/0000-0002-1556-2159","contributorId":336799,"corporation":false,"usgs":false,"family":"Pearl","given":"Jessie K.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":954769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":954770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johns, Wes 0000-0003-0476-6364","orcid":"https://orcid.org/0000-0003-0476-6364","contributorId":365774,"corporation":false,"usgs":false,"family":"Johns","given":"Wes","affiliations":[{"id":80905,"text":"Lettis Consultants International, Inc.","active":true,"usgs":false}],"preferred":false,"id":954771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":954772,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273873,"text":"70273873 - 2026 - Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","interactions":[],"lastModifiedDate":"2026-03-23T14:50:21.582142","indexId":"70273873","displayToPublicDate":"2026-01-25T09:06:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python","docAbstract":"<p><span>Regulatory agencies in humid temperate environments rely on timely evaluations of streamflow depletion and drawdown to protect aquatic ecosystems and existing water users. Numerical models offer detailed insights, but their complexity and time demands often preclude their practical use in rapid decision-making. We present pycap-dss, an open-source Python package that implements a suite of analytical solutions for estimating streamflow depletion and drawdown. The tool supports superposition of multiple wells and time-varying pumping, enabling cumulative impact assessments in situations with multiple wells and streams. The software is modular and extensible, allowing users to interchange solutions or add new analytical methods. A YAML-based configuration supports batch processing of multiple wells, and an optional AnalysisProject class facilitates integration with regulatory workflows. Rigorous unit and regression testing ensures computational reliability, and continuous integration supports ongoing development. We demonstrate deterministic examples of drawdown where multiple solutions are readily compared and streamflow depletion with multiple wells in the Central Sands region of Wisconsin. We also show the value of Monte Carlo analyses of streamflow depletion in the same Central Sands example, leveraging computational efficiency to evaluate the uncertainty of individual and cumulative streamflow depletion calculations from over 200 high-capacity wells.</span></p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.70046","usgsCitation":"Fienen, M., Pruitt, A., and Reeves, H.W., 2026, Teach me how to pycap: A high-capacity well decision support tool using analytical solutions in Python: Groundwater, v. 64, no. 2, p. 223-234, https://doi.org/10.1111/gwat.70046.","productDescription":"12 p.","startPage":"223","endPage":"234","ipdsId":"IP-183720","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499946,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.70046","text":"Publisher Index Page"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Tomorrow River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.67725263192825,\n              44.6879674210181\n            ],\n            [\n              -89.67725263192825,\n              44.15565808301017\n            ],\n            [\n              -89.16563204911922,\n              44.15565808301017\n            ],\n            [\n              -89.16563204911922,\n              44.6879674210181\n            ],\n            [\n              -89.67725263192825,\n              44.6879674210181\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruitt, Aaron","contributorId":214451,"corporation":false,"usgs":false,"family":"Pruitt","given":"Aaron","affiliations":[],"preferred":false,"id":955344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273948,"text":"70273948 - 2026 - Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions","interactions":[],"lastModifiedDate":"2026-03-02T17:49:22.623453","indexId":"70273948","displayToPublicDate":"2026-01-24T09:23:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions","docAbstract":"<p><span>Our understanding of the impacts of climate change, sea-level rise (SLR), and freshwater management on the magnitude and variability of carbon fluxes in tidal forested wetlands remains limited. In this study, we applied a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool—DeNitrification-DeComposition (WCAT-DNDC) model to explore responses of carbon fluxes in tidal swamp forests to climate change-induced alterations in hydrologic conditions and to predict impacts of planned reintroduction of river flows. We selected twelve sites in three habitats (throughput, relict, degraded) inside the Lake Maurepas swamp forests (Louisiana, USA) to represent various hydrological and salinity regimes. Environmental scenarios included dry, average, and wet conditions, SLR (low and high), and a Mississippi River (MR) diversion. Simulation results showed that the responses of net ecosystem exchange (NEE), net primary productivity (NPP), ecosystem respiration (ER), methane (CH</span><sub>4</sub><span>) and nitrous oxide (N</span><sub>2</sub><span>O) emissions in the Lake Maurepas swamp forests varied substantially among sites. However, the overall net carbon uptake capacity of the Lake Maurepas swamp forests was high (NEE: −&nbsp;1143 to −&nbsp;1650&nbsp;g C m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>), suggesting that Lake Maurepas swamp forests are large carbon sinks. The high net carbon uptake capacity could be significantly affected by climate change induced drought, flooding, and SLR with the bi-directional changes (increase or decrease) depending on the direction and magnitude of the hydrologic regime changes. The response of the net carbon uptake capacity to MR diversion is also bi-directional and site-specific, but enhancement of the capacity of NEE of up to −&nbsp;1957&nbsp;g C m</span><sup>2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;is possible, implying that MR diversion into the swamp forests could be beneficial in the context of carbon cycling and carbon sequestration.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s11273-026-10111-5","usgsCitation":"Wang, H., Krauss, K.W., Shaffer, G.P., Patton, B., Kroes, D., Noe, G.E., Dai, Z., Dettwiller, L., and Trettin, C.C., 2026, Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions: Wetlands Ecology and Management, v. 34, no. 1, 11, 27 p., https://doi.org/10.1007/s11273-026-10111-5.","productDescription":"11, 27 p.","ipdsId":"IP-180681","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":500188,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500214,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70273948/full"},{"id":500215,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70273948/70273948.XML"},{"id":500683,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70273948/images"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lake Maurepas swamp forests","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.21451630425345,\n              30.450162758345343\n            ],\n            [\n              -90.90340771654913,\n              30.450162758345343\n            ],\n            [\n              -90.90340771654913,\n              29.978620193311116\n            ],\n            [\n              -90.21451630425345,\n              29.978620193311116\n            ],\n            [\n              -90.21451630425345,\n              30.450162758345343\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":222377,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":955890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W.","contributorId":366426,"corporation":false,"usgs":false,"family":"Krauss","given":"Ken","middleInitial":"W.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":955891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaffer, Gary P.","contributorId":366427,"corporation":false,"usgs":false,"family":"Shaffer","given":"Gary","middleInitial":"P.","affiliations":[{"id":28058,"text":"Southeastern Louisiana University","active":true,"usgs":false}],"preferred":false,"id":955892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patton, Brett 0000-0002-7396-3452 pattonb@usgs.gov","orcid":"https://orcid.org/0000-0002-7396-3452","contributorId":5458,"corporation":false,"usgs":true,"family":"Patton","given":"Brett","email":"pattonb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":955893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - 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,{"id":70273779,"text":"70273779 - 2026 - Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","interactions":[],"lastModifiedDate":"2026-01-29T14:54:24.411943","indexId":"70273779","displayToPublicDate":"2026-01-24T08:46:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system","docAbstract":"<p><span>Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2026.103615","usgsCitation":"Newman, C.P., and Pepin, J.D., 2026, Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system: Geothermics, v. 136, 103615, 14 p., https://doi.org/10.1016/j.geothermics.2026.103615.","productDescription":"103615, 14 p.","ipdsId":"IP-180997","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":499294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2026.103615","text":"Publisher Index Page"},{"id":499224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Steamboat Springs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -106.87961681380281,\n              40.567\n            ],\n            [\n              -106.87961681380281,\n              40.45\n            ],\n            [\n              -106.68,\n              40.45\n            ],\n            [\n              -106.68,\n              40.567\n            ],\n            [\n              -106.87961681380281,\n              40.567\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"136","noUsgsAuthors":false,"publicationDate":"2026-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pepin, Jeffrey D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeffrey","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954761,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274166,"text":"70274166 - 2026 - A catalogue of Do's and Don'ts in the modeling of environmental systems","interactions":[],"lastModifiedDate":"2026-03-03T15:08:37.444188","indexId":"70274166","displayToPublicDate":"2026-01-24T08:01:33","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A catalogue of Do's and Don'ts in the modeling of environmental systems","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2026.106893","usgsCitation":"Sun, X., Jakeman, A.J., Hamilton, S.H., Grimm, V., Hunt, R.J., El Sawah, S., Wang, H., Croke, B., and Chen, M., 2026, A catalogue of Do's and Don'ts in the modeling of environmental systems: Environmental Modelling and Software, v. 198, 106893, 13 p., https://doi.org/10.1016/j.envsoft.2026.106893.","productDescription":"106893, 13 p.","ipdsId":"IP-176780","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"198","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sun, Xifu","contributorId":367094,"corporation":false,"usgs":false,"family":"Sun","given":"Xifu","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":956746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamilton, Serena H","contributorId":248834,"corporation":false,"usgs":false,"family":"Hamilton","given":"Serena","email":"","middleInitial":"H","affiliations":[{"id":50035,"text":"School of Science, Edith Cowan University, Joondalup, WA, Australia","active":true,"usgs":false}],"preferred":false,"id":956772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grimm, Volker","contributorId":224014,"corporation":false,"usgs":false,"family":"Grimm","given":"Volker","affiliations":[{"id":26949,"text":"Helmholtz Centre for Environmental Research, Germany","active":true,"usgs":false}],"preferred":false,"id":956773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":214444,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"El Sawah, Sondoss","contributorId":367096,"corporation":false,"usgs":false,"family":"El Sawah","given":"Sondoss","affiliations":[{"id":87548,"text":"University of New South Wales Canberra","active":true,"usgs":false}],"preferred":false,"id":956749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Hsiao-Hsuan","contributorId":349683,"corporation":false,"usgs":false,"family":"Wang","given":"Hsiao-Hsuan","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":956750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Croke, Barry 0000-0001-9216-1554","orcid":"https://orcid.org/0000-0001-9216-1554","contributorId":248856,"corporation":false,"usgs":false,"family":"Croke","given":"Barry","email":"","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":956747,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Min","contributorId":330043,"corporation":false,"usgs":false,"family":"Chen","given":"Min","affiliations":[{"id":78773,"text":"University of Wisconsin-Madison, Wisconsin, USA","active":true,"usgs":false}],"preferred":false,"id":956751,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70274536,"text":"70274536 - 2026 - Extreme Potomac floods at Washington D.C. during the past 500 years","interactions":[],"lastModifiedDate":"2026-03-31T15:13:33.863387","indexId":"70274536","displayToPublicDate":"2026-01-23T10:08:43","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Extreme Potomac floods at Washington D.C. during the past 500 years","docAbstract":"<p><span>Washington D.C. faces one of the highest 100-year flood risks of any major city along the U.S. East Coast. In addition to storm-surge inundation during hurricanes and nor'easters, water-level observations for Washington are strongly skewed by major floods on the Potomac River. Using geologic and historic records we find new evidence for ice-jam flooding at Georgetown during the Little Ice Age, as recently as 1784, that was up to ∼2x the magnitude of the largest events of the past hundred years (1936, 1942). Over the 19th century (a) human modifications to the Potomac estuary as well as (b) increasingly heavy rainfall and (c) land-clearance in the watershed may have contributed to increasingly frequent large floods at Washington. Early surveys of the U.S. Capitol Building and other local landmarks also suggest sea level on the Potomac estuary at Washington has risen by upwards of 0.7&nbsp;m (2.2&nbsp;ft) since the 1790s.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL118329","usgsCitation":"Toomey, M., Cronin, T.M., Rodysill, J.R., Seidenstein, J.L., and Willard, D., 2026, Extreme Potomac floods at Washington D.C. during the past 500 years: Geophysical Research Letters, v. 53, no. 2, e2025GL118329, 10 p., https://doi.org/10.1029/2025GL118329.","productDescription":"e2025GL118329, 10 p.","ipdsId":"IP-171642","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":502073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl118329","text":"Publisher Index Page"},{"id":501861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","city":"WAshington D.C.","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.12661486872723,\n              38.949829500116806\n            ],\n            [\n              -77.12661486872723,\n              38.764446761388854\n            ],\n            [\n              -76.97381536652976,\n              38.764446761388854\n            ],\n            [\n              -76.97381536652976,\n              38.949829500116806\n            ],\n            [\n              -77.12661486872723,\n              38.949829500116806\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":958149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodysill, Jessica R. 0000-0002-3602-7227 jrodysill@usgs.gov","orcid":"https://orcid.org/0000-0002-3602-7227","contributorId":207577,"corporation":false,"usgs":true,"family":"Rodysill","given":"Jessica","email":"jrodysill@usgs.gov","middleInitial":"R.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":958151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seidenstein, Julia Lynn 0000-0002-0585-1977","orcid":"https://orcid.org/0000-0002-0585-1977","contributorId":290625,"corporation":false,"usgs":true,"family":"Seidenstein","given":"Julia","email":"","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":958153,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70276594,"text":"70276594 - 2026 - Linking community-climate disequilibrium to ecosystem function","interactions":[],"lastModifiedDate":"2026-06-10T14:31:52.477393","indexId":"70276594","displayToPublicDate":"2026-01-23T09:17:09","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Linking community-climate disequilibrium to ecosystem function","docAbstract":"<p><span>Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community-climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, we develop a simple theoretical model to address both of these problems by linking community-climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near-term even when climate change is expected to enhance functioning in the long-term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre-existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community-climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community-climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.70314","usgsCitation":"Stemkovski, M., Cortez, M.H., Bernhardt, J.R., Bladen, K.K., Bradford, J., Clark-Wolf, K., Evans, M.E., Johnson, L.C., Lynch, A., Pastore, M.A., Pinsky, M.L., Rollinson, C.R., Selmoni, O., Walker, A.P., Williams, J.W., and Adler, P.B., 2026, Linking community-climate disequilibrium to ecosystem function: Ecology Letters, v. 29, no. 1, e70314, 13 p., https://doi.org/10.1111/ele.70314.","productDescription":"e70314, 13 p.","ipdsId":"IP-173961","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":505493,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.70314","text":"Publisher Index Page"},{"id":505262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Stemkovski, Michael","contributorId":303009,"corporation":false,"usgs":false,"family":"Stemkovski","given":"Michael","email":"","affiliations":[{"id":65599,"text":"Utah State University, Biology Dept.","active":true,"usgs":false}],"preferred":false,"id":962747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cortez, Michael H.","contributorId":372093,"corporation":false,"usgs":false,"family":"Cortez","given":"Michael","middleInitial":"H.","affiliations":[{"id":88248,"text":"Department of Biological Science, Florida State University, Tallahassee, FL, 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,{"id":70273771,"text":"70273771 - 2026 - Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas","interactions":[],"lastModifiedDate":"2026-01-28T15:44:10.069314","indexId":"70273771","displayToPublicDate":"2026-01-23T08:36:18","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16135,"text":"GeoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1&nbsp;km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10&nbsp;μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km</span><sup>2</sup><span>&nbsp;as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.</span></span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GH001666","usgsCitation":"Azad, S., Stahl, M.O., Erickson, M., DeYoung, B.A., Connolly, C.T., Chillrud, L., Schilling, K., Navas-Acien, A., Basu, A., Mailloux, B., Bostick, B.C., and Chillrud, S.N., 2026, Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas: GeoHealth, v. 10, no. 1, e2025GH001666, 18 p., https://doi.org/10.1029/2025GH001666.","productDescription":"e2025GH001666, 18 p.","ipdsId":"IP-177700","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":499326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gh001666","text":"Publisher Index Page"},{"id":499171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":206446,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda","email":"merickso@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeYoung, Beck A.","contributorId":365740,"corporation":false,"usgs":false,"family":"DeYoung","given":"Beck","middleInitial":"A.","affiliations":[{"id":87203,"text":"Department of Geosciences, Union College","active":true,"usgs":false}],"preferred":false,"id":954708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connolly, Craig T.","contributorId":255063,"corporation":false,"usgs":false,"family":"Connolly","given":"Craig","email":"","middleInitial":"T.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":954709,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chillrud, Lawrence","contributorId":365741,"corporation":false,"usgs":false,"family":"Chillrud","given":"Lawrence","affiliations":[{"id":87204,"text":"Department of Electrical Engineering, Northwestern University","active":true,"usgs":false}],"preferred":false,"id":954710,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schilling, Kathrin","contributorId":318215,"corporation":false,"usgs":false,"family":"Schilling","given":"Kathrin","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":954711,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Navas-Acien, Ana","contributorId":257950,"corporation":false,"usgs":false,"family":"Navas-Acien","given":"Ana","email":"","affiliations":[{"id":52179,"text":"Columbia University Mailman School of Public Health","active":true,"usgs":false}],"preferred":false,"id":954712,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Basu, Anirban","contributorId":318223,"corporation":false,"usgs":false,"family":"Basu","given":"Anirban","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":954713,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mailloux, Brian","contributorId":365762,"corporation":false,"usgs":false,"family":"Mailloux","given":"Brian","affiliations":[{"id":82397,"text":"Department of Environmental Science, Barnard College, Columbia University","active":true,"usgs":false}],"preferred":false,"id":954751,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bostick, Benjamin C.","contributorId":365742,"corporation":false,"usgs":false,"family":"Bostick","given":"Benjamin","middleInitial":"C.","affiliations":[{"id":40291,"text":"Lamont-Doherty Earth Observatory of Columbia University","active":true,"usgs":false}],"preferred":false,"id":954714,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chillrud, Steven N.","contributorId":365743,"corporation":false,"usgs":false,"family":"Chillrud","given":"Steven","middleInitial":"N.","affiliations":[{"id":40291,"text":"Lamont-Doherty Earth Observatory of Columbia University","active":true,"usgs":false}],"preferred":false,"id":954715,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70273774,"text":"70273774 - 2026 - Strength of depensation not influenced by fish population productivity","interactions":[],"lastModifiedDate":"2026-01-28T16:17:13.025728","indexId":"70273774","displayToPublicDate":"2026-01-22T10:11:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Strength of depensation not influenced by fish population productivity","docAbstract":"<p><span>A long-held assumption in the management of exploited fisheries is that fish populations will compensate with increased recruit survival to replenish the population when adult stock size is reduced through harvest. Observations of depensatory recruitment (reduced recruit survival at low adult stock size) and critical depensatory thresholds have challenged the compensation assumption. Post et al. (2002) postulated that critical depensatory thresholds were related to fish population productivity. Walleye&nbsp;</span><i>Sander vitreus</i><span>&nbsp;are a culturally, economically, and recreationally important sportfish whose persistence is being challenged by natural recruitment declines throughout much of its native range. Depensation, among other abiotic and biotic stressors, has been implicated in walleye natural recruitment declines. If walleye population productivity is related to critical depensatory thresholds, then population productivity benchmarks could be established to reduce the probability of crossing them. We used empirically-derived and model predicted depensation values (</span><i>q</i><span>) and empirical estimates of walleye population productivity to test for relationships between these variables in northern Wisconsin lakes. We found little evidence for a relationship between&nbsp;</span><i>q</i><span>&nbsp;and walleye population productivity across all lakes examined. Our finding failed to support the theoretical postulation of a relationship between these variables by Post et al. (2002) for walleye. Little evidence for a relationship between&nbsp;</span><i>q</i><span>&nbsp;and population productivity suggests that depensatory thresholds may differ among individual walleye populations and that walleye populations may transition abruptly between compensatory and depensatory states. Given our findings, conservation efforts for walleye that solely focus on low productivity populations may miss other trends because population productivity may not be considered a broad predictor of crossing a critical depensatory threshold.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2026.107665","usgsCitation":"Sass, G.S., Mrnak, J.T., Shaw, S.L., Feiner, Z., Dassow, C.J., Rypel, A.L., and Embke, H., 2026, Strength of depensation not influenced by fish population productivity: Fisheries Research, v. 294, 107665, 8 p., https://doi.org/10.1016/j.fishres.2026.107665.","productDescription":"107665, 8 p.","ipdsId":"IP-177311","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":499176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"294","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sass, Greg S.","contributorId":365759,"corporation":false,"usgs":false,"family":"Sass","given":"Greg","middleInitial":"S.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mrnak, Joesph T.","contributorId":365760,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joesph","middleInitial":"T.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Stephanie L","contributorId":365761,"corporation":false,"usgs":false,"family":"Shaw","given":"Stephanie","middleInitial":"L","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":954742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feiner, Zachary S.","contributorId":348857,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":954743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dassow, Colin J.","contributorId":293206,"corporation":false,"usgs":false,"family":"Dassow","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":954744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rypel, Andrew L.","contributorId":199498,"corporation":false,"usgs":false,"family":"Rypel","given":"Andrew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":954745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":954746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70275603,"text":"70275603 - 2026 - The development of long-term mean annual total nitrogen and total phosphorus load models for Mississippi, U.S., using RSPARROW","interactions":[],"lastModifiedDate":"2026-05-05T17:20:49.34724","indexId":"70275603","displayToPublicDate":"2026-01-22T10:09:34","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"The development of long-term mean annual total nitrogen and total phosphorus load models for Mississippi, U.S., using RSPARROW","docAbstract":"<p><span>Water-quality degradation from nutrient pollution remains a major challenge for resource managers. Developing effective strategies requires tools to characterize nutrient sources and transport. This study used the RSPARROW framework to develop and assess new, smaller-scale models for Total Nitrogen (TN) and Total Phosphorus (TP) transport across Mississippi (MS). These state-level models were built using 15 years (2005–2020) of observation data and considered variables including multiple nutrient sources, land characteristics, and attenuation processes. The MS models demonstrated comparable accuracy to larger regional SPARROW models, validating the use of smaller-scale models for local management. Results showed agricultural sources are the major contributors to TN, dominated by fertilizer in northern MS and livestock manure in the south. Urban land cover also significantly influenced TN and was the second most significant source of TP, following geologic material (background P). Fertilizer and manure were also important TP sources. This study provides valuable, spatially explicit data on nutrient distribution in MS streams, supporting the state’s nutrient reduction planning. It concludes by highlighting the need for future model improvements via updated source data and mean annual flow estimates.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w18030292","usgsCitation":"Roland, V.L., Gain, E., and Hicks, M.B., 2026, The development of long-term mean annual total nitrogen and total phosphorus load models for Mississippi, U.S., using RSPARROW: Water, v. 18, no. 3, 292, 31 p., https://doi.org/10.3390/w18030292.","productDescription":"292, 31 p.","ipdsId":"IP-168403","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":504204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w18030292","text":"Publisher Index Page"},{"id":504006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Louisiana, Mississippi, North Carolina, Tennessee","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.20528575909753,\n              35.23886172277952\n            ],\n            [\n              -92.21636813057978,\n              30.712924232415943\n            ],\n            [\n              -86.91983998127752,\n              30.92462366874065\n            ],\n            [\n              -85.89674933208819,\n              32.76620143145887\n            ],\n            [\n              -82.67246605005776,\n              34.944462510438534\n            ],\n            [\n              -79.36241766400043,\n              36.31548286327417\n            ],\n            [\n              -90.20528575909753,\n              35.23886172277952\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Victor L. II 0000-0002-6260-9351","orcid":"https://orcid.org/0000-0002-6260-9351","contributorId":336938,"corporation":false,"usgs":false,"family":"Roland","given":"Victor","suffix":"II","middleInitial":"L.","affiliations":[{"id":80919,"text":"U.S Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":961022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gain, Emily 0000-0002-7834-2145","orcid":"https://orcid.org/0000-0002-7834-2145","contributorId":293625,"corporation":false,"usgs":true,"family":"Gain","given":"Emily","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hicks, Matthew B. 0000-0001-5516-0296 mhicks@usgs.gov","orcid":"https://orcid.org/0000-0001-5516-0296","contributorId":3778,"corporation":false,"usgs":true,"family":"Hicks","given":"Matthew","email":"mhicks@usgs.gov","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":961150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273773,"text":"70273773 - 2026 - Mountain goat declines in a protected, interior, native population","interactions":[],"lastModifiedDate":"2026-01-28T15:42:30.936097","indexId":"70273773","displayToPublicDate":"2026-01-22T09:37:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Mountain goat declines in a protected, interior, native population","docAbstract":"<p><span>A shifting climate poses threats to alpine-adapted species including mountain goats. We used long-term (12 years) citizen science monitoring data and Bayesian N-mixture modeling to estimate population trends and drivers of population metrics among mountain goats in Glacier National Park (GNP). Median goats per site (</span><i>n</i><span> = 37 sites) declined by 45% (95% credible interval [CRI] = 32%, 57%) from 77.8 (95% CRI = 64.4, 95.1) in 2008 to 42.3 (95% CRI = 34.3, 52.2) in 2019, with consistent declines from 2008 until 2015, when the number of estimated goats stabilized. The decline exceeds IUCN criteria for classifying a population as vulnerable, &gt;30% declines over only two generations. Across years, relatively few goats occupied northwestern GNP. Goat numbers declined the most at northeastern sites, trended toward decline in most southern sites, and increased at only two west-central sites. The proportion of permanent snow and glaciers, the presence of natural mineral licks, and habituation strongly increased the initial abundance of goats in the area. Weather variables had the greatest influence on population growth rates, particularly precipitation between May 15 and June 15 of the previous summer, the neonatal period. Lower growth occurred with less snow water equivalent and lower mean winter temperature, early summer temperature, and early summer precipitation. Projected reductions of permanent snow, increasing spring and summer temperatures, and insufficient and variable spring precipitation raise concerns for the future of native goats in this region. Our analyses reveal ways to improve detection rates of goats during surveys, which is important for optimizing the precision of estimates and the power to detect future trends. Detection increased with goat habituation, retention of observers with experience, use of binoculars, and conducting surveys at lower temperatures and earlier dates. Improving detection will be particularly important given the lower number of goats currently observed in the park. Research to estimate park-wide population size, evaluate genetic structure and diversity, assess changing habitat, human recreation levels and forage, and forward-project climate effects on persistence will be crucial to understanding the context of these results and conserving this iconic, metapopulation at the southern edge of the distribution of native mountain goats.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70465","usgsCitation":"Graves, T., Janousek, W.M., Yarnall, M., and Belt, J., 2026, Mountain goat declines in a protected, interior, native population: Ecosphere, v. 17, no. 1, e70465, 17 p., https://doi.org/10.1002/ecs2.70465.","productDescription":"e70465, 17 p.","ipdsId":"IP-128275","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70465","text":"Publisher Index Page"},{"id":499544,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91GTUL3","text":"USGS data release","linkHelpText":"Mountain goats (Oreamnos americanus) in Glacier National Park, Montana, USA, and Waterton Lakes National Park, Alberta, Canada, 2008-2023"},{"id":499170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.60080650878787,\n              48.99458864720981\n            ],\n            [\n              -114.48645916591128,\n              49.005131748927084\n            ],\n            [\n              -114.0989861284199,\n              48.45748119419969\n            ],\n            [\n              -113.89364327444952,\n              48.479975245922134\n            ],\n            [\n              -113.55795234795937,\n              48.2165274365571\n            ],\n            [\n              -113.33118241357474,\n              48.30924537874591\n            ],\n            [\n              -113.2169046513653,\n              48.412463176207496\n            ],\n            [\n              -113.40439160499024,\n              48.70318915560594\n            ],\n            [\n              -113.41331955516296,\n              48.74677172670576\n            ],\n            [\n              -113.46867284623328,\n              48.78796372490032\n            ],\n            [\n              -113.59723532871878,\n              48.93362924512738\n            ],\n            [\n              -113.60080650878787,\n              48.99458864720981\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":954737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yarnall, Michael","contributorId":300614,"corporation":false,"usgs":false,"family":"Yarnall","given":"Michael","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":954738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belt, Jami","contributorId":177314,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","affiliations":[],"preferred":false,"id":954739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274041,"text":"70274041 - 2026 - Remote compositional analyses of space-weathered lunar maria","interactions":[],"lastModifiedDate":"2026-02-20T14:58:36.389731","indexId":"70274041","displayToPublicDate":"2026-01-22T08:55:31","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17061,"text":"Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Remote compositional analyses of space-weathered lunar maria","docAbstract":"<p><span>Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.</span></p>","language":"English","publisher":"IOP Science","doi":"10.3847/PSJ/ae2b57","usgsCitation":"Jung, J., Lapotre, M.G., Milliken, R.E., Minson, S.E., 2026, Remote compositional analyses of space-weathered lunar maria: Planetary Science Journal, v. 7, no. 1, 18, 13 p., https://doi.org/10.3847/PSJ/ae2b57.","productDescription":"18, 13 p.","ipdsId":"IP-183800","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":500824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/ae2b57","text":"Publisher Index Page"},{"id":500336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Jung, Ji-In 0000-0001-8728-7320","orcid":"https://orcid.org/0000-0001-8728-7320","contributorId":366818,"corporation":false,"usgs":false,"family":"Jung","given":"Ji-In","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":956269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lapotre, Matheiu G. 0000-0001-9941-1552","orcid":"https://orcid.org/0000-0001-9941-1552","contributorId":366819,"corporation":false,"usgs":false,"family":"Lapotre","given":"Matheiu","middleInitial":"G.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":956270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milliken, Ralph E. 0000-0003-3240-4918","orcid":"https://orcid.org/0000-0003-3240-4918","contributorId":366820,"corporation":false,"usgs":false,"family":"Milliken","given":"Ralph","middleInitial":"E.","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":956271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273700,"text":"70273700 - 2026 - Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","interactions":[],"lastModifiedDate":"2026-01-26T14:20:22.073435","indexId":"70273700","displayToPublicDate":"2026-01-22T08:44:42","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning","docAbstract":"<p><span>Remote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union (</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"mrow\"><span id=\"MathJax-Span-5\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-6\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-7\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>) of 0.57, with performance rising to an actual&nbsp;</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-8\" class=\"math\"><span><span id=\"MathJax-Span-9\" class=\"mrow\"><span id=\"MathJax-Span-10\" class=\"semantics\"><span id=\"MathJax-Span-11\" class=\"mrow\"><span id=\"MathJax-Span-12\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-13\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-14\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>&nbsp;of 0.89 on the subset of predictions with high confidence (predicted&nbsp;</span><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"&lt;math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;&gt;&lt;semantics&gt;&lt;mrow&gt;&lt;mi&gt;I&lt;/mi&gt;&lt;mi&gt;o&lt;/mi&gt;&lt;mi&gt;U&lt;/mi&gt;&lt;/mrow&gt;&lt;/semantics&gt;&lt;/math&gt;\"><span id=\"MathJax-Span-15\" class=\"math\"><span><span id=\"MathJax-Span-16\" class=\"mrow\"><span id=\"MathJax-Span-17\" class=\"semantics\"><span id=\"MathJax-Span-18\" class=\"mrow\"><span id=\"MathJax-Span-19\" class=\"mi\">\uD835\uDC3C</span><span id=\"MathJax-Span-20\" class=\"mi\">\uD835\uDC5C</span><span id=\"MathJax-Span-21\" class=\"mi\">\uD835\uDC48</span></span></span></span></span></span></span><span>&nbsp;&gt; 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs18020375","usgsCitation":"Brimhall, N., Bladen, K.K., Kerby, T., Legleiter, C.J., Swapp, C., Fluckiger, H., Bahr, J.E., Roberts, M., Hart, K., Stegman, C.L., Bean, B., and Moon, K., 2026, Compilation of a nationwide river image dataset for identifying river channels and river rapids via deep learning: Remote Sensing, v. 18, no. 2, 375, 22 p., https://doi.org/10.3390/rs18020375.","productDescription":"375, 22 p.","ipdsId":"IP-182435","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":499312,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18020375","text":"Publisher Index 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University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":954332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kerby, Tom 0009-0002-1189-3820","orcid":"https://orcid.org/0009-0002-1189-3820","contributorId":365453,"corporation":false,"usgs":false,"family":"Kerby","given":"Tom","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":954334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swapp, Cameron 0009-0004-9019-1097","orcid":"https://orcid.org/0009-0004-9019-1097","contributorId":365454,"corporation":false,"usgs":false,"family":"Swapp","given":"Cameron","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fluckiger, Hannah 0009-0004-8246-1376","orcid":"https://orcid.org/0009-0004-8246-1376","contributorId":365455,"corporation":false,"usgs":false,"family":"Fluckiger","given":"Hannah","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bahr, Julie E 0009-0005-9937-5885","orcid":"https://orcid.org/0009-0005-9937-5885","contributorId":365457,"corporation":false,"usgs":false,"family":"Bahr","given":"Julie","middleInitial":"E","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":954337,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roberts, Makenna 0009-0002-7084-3276","orcid":"https://orcid.org/0009-0002-7084-3276","contributorId":365462,"corporation":false,"usgs":false,"family":"Roberts","given":"Makenna","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954338,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hart, Kaden 0009-0001-0652-9242","orcid":"https://orcid.org/0009-0001-0652-9242","contributorId":365468,"corporation":false,"usgs":false,"family":"Hart","given":"Kaden","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954339,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stegman, Christina L.","contributorId":365580,"corporation":false,"usgs":false,"family":"Stegman","given":"Christina","middleInitial":"L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":954340,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bean, Brennan 0000-0002-2853-0455","orcid":"https://orcid.org/0000-0002-2853-0455","contributorId":365485,"corporation":false,"usgs":false,"family":"Bean","given":"Brennan","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954341,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moon, Kevin 0000-0002-4457-9988","orcid":"https://orcid.org/0000-0002-4457-9988","contributorId":365486,"corporation":false,"usgs":false,"family":"Moon","given":"Kevin","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":954342,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70273273,"text":"sim3542 - 2026 - Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York","interactions":[],"lastModifiedDate":"2026-02-03T17:09:44.672869","indexId":"sim3542","displayToPublicDate":"2026-01-21T19:43:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3542","displayTitle":"Bedrock Geologic Map of the Eagle Lake Quadrangle, Essex County, New York","title":"Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York","docAbstract":"<p>The bedrock geology of the 7.5-minute Eagle Lake quadrangle, Essex County, New York, consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of an anorthosite-mangerite-charnockite-granite (AMCG) suite, now exposed mostly as orthogneiss, at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) predated AMCG magmatism and is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the paragneiss host rocks. A sample of hornblende quartz syenite from the AMCG suite, collected from an abandoned railroad cut on Old Furnace Road, yielded a U-Pb zircon age of 1,149±10 million years before present. D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into the previously deformed lithologies. The LMG crystallized at approximately 1.15 to 1.14 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation of the Marcy anorthosite began during D3 along a mylonitic extensional detachment, as a type of core complex. Protracted D3 produced F3 folds exhibited in regional domes and basins, such as the Hammondville antiform, reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. Lower Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. The Potsdam Sandstone preserves the Cambrian stratigraphy in outliers above the Great Unconformity. The Paleozoic rocks are weakly folded and block faulted. Parts of the quadrangle are covered by undifferentiated glacial deposits, but much of the quadrangle contains only a variably thick, veneer of unmapped glacial till over significant areas of exposed bedrock. The map also shows waste rock piles and locations of historical mining operations. This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondack Mountains, and provide a modern context for historical mines. This Scientific Investigations Map of the Eagle Lake 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, and two cross sections. The explanatory pamphlet includes a discussion of the geology.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3542","collaboration":"Prepared in cooperation with the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Regan, S.P., Geer, P.S., Merschat, A.J., Suarez, K.A., McAleer, R.J., Walton, M.S., Jr., and Crider, E.A., Jr., 2026, Bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York: U.S. Geological Survey Scientific Investigations Map 3542, 1 sheet, scale 1:24,000, 57-p. pamphlet, https://doi.org/10.3133/sim3542.","productDescription":"Pamphlet: ix, 57 p.; 1 Sheet: 63.43 x 35.22 inches; Data Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-151166","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":498080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3542/coverthb.jpg"},{"id":498081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_pamphlet.pdf","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3542 Pamphlet"},{"id":498752,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_pamphlet.XML","description":"SIM 3542 XML"},{"id":498753,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6XYEL","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Eagle Lake quadrangle, Essex County, New York"},{"id":498867,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119158.htm","linkFileType":{"id":5,"text":"html"}},{"id":498751,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3542/sim3542_sheet.pdf","size":"56.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3542 Sheet"}],"country":"United States","state":"New York","otherGeospatial":"Eagle Lake quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.625,\n              44\n            ],\n            [\n              -73.625,\n              43.875\n            ],\n            [\n              -73.5,\n              43.875\n            ],\n            [\n              -73.5,\n              44\n            ],\n            [\n              -73.625,\n              44\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\" data-mce-href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\">Florence Bascom Geoscience Center</a><br>U.S. Geological Survey<br>926A National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Plain Language Summary</li><li>Introduction</li><li>Lithostratigraphy</li><li>Gamma Radiation Measurements</li><li>Structural Geology</li><li>Tectonics and Metamorphism</li><li>U-Th-Pb Geochronology</li><li>Geochemistry</li><li>Economic Geology</li><li>References Cited</li><li>Appendix 1. Representative Photographs of Map Units From the Eagle Lake Quadrangle</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2026-01-21","noUsgsAuthors":false,"plainLanguageSummary":"<p>The U.S. Geological Survey mapped the bedrock geology of the 7.5-minute Eagle Lake quadrangle, Essex County, New York, to establish a framework for 1:24,000-scale detailed bedrock geologic mapping in the Adirondack Mountains, and provide a modern context for historical iron, graphite, and feldspar mines that operated in the 1800s. The report includes the most detailed 1:24,000-scale bedrock geologic map ever published in the Adirondack Mountains. The region is underlain by highly complex Precambrian igneous and metamorphic rocks that range in age from about 1.2 to 1.0 billion years old. The high quality of the naturally occurring mineral magnetite extracted from local iron mines led to the first use of an electric motor in Ironville, proclaimed to be the birthplace of the electric age. Abandoned iron and pegmatite mines locally contain elevated abundances of rare earth elements; some of the deposits have elevated natural radioactivity above background concentrations.</p>","publicationDate":"2026-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":355444,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":952978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regan, Sean P. 0000-0002-8445-5138","orcid":"https://orcid.org/0000-0002-8445-5138","contributorId":360816,"corporation":false,"usgs":false,"family":"Regan","given":"Sean","middleInitial":"P.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":952979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geer, Phillip S.","contributorId":364641,"corporation":false,"usgs":false,"family":"Geer","given":"Phillip","middleInitial":"S.","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":952980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":952981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suarez, Kaitlyn A. 0000-0003-4133-3074","orcid":"https://orcid.org/0000-0003-4133-3074","contributorId":224240,"corporation":false,"usgs":false,"family":"Suarez","given":"Kaitlyn","middleInitial":"A.","affiliations":[{"id":33634,"text":"University of Massachusetts at Amherst","active":true,"usgs":false}],"preferred":false,"id":952982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":952983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walton,, Matt S. Jr.","contributorId":364642,"corporation":false,"usgs":false,"family":"Walton,","given":"Matt","suffix":"Jr.","middleInitial":"S.","affiliations":[{"id":29853,"text":"Yale University, New Haven, Conn.","active":true,"usgs":false}],"preferred":false,"id":952984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crider,, E. Allen Jr. 0000-0003-2393-5290 ecrider@usgs.gov","orcid":"https://orcid.org/0000-0003-2393-5290","contributorId":203507,"corporation":false,"usgs":true,"family":"Crider,","given":"E. Allen","suffix":"Jr.","email":"ecrider@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":952985,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70273409,"text":"ofr20251057 - 2026 - Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","interactions":[],"lastModifiedDate":"2026-02-03T17:09:16.100992","indexId":"ofr20251057","displayToPublicDate":"2026-01-21T07:00:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1057","displayTitle":"Distribution, Abundance, Breeding Activities, and Habitat Use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 Summary Report","title":"Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report","docAbstract":"<h1>Executive Summary&nbsp;</h1><p>The purpose of this report is to provide the Marine Corps with a summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (<i>Vireo bellii pusillus</i>) at Marine Corps Base Camp Pendleton, California (MCBCP or Base). The report presents results of vireo surveys and monitoring in 2024 and summarizes a subset of data collected from 2020 through 2024. Surveys for the Least Bell's Vireo were completed at MCBCP between April 4 and July 9, 2024. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed two to four times. We detected 542 territorial male vireos and 17 transient vireos in core survey areas. An additional 102 territorial male vireos and 2 transients were detected in non-core survey areas. Transient vireos were detected on 5 of the 10 drainages/sites surveyed (core and non-core areas). In core survey areas, 87 percent of vireo territories were on the four most populated drainages, with the Santa Margarita River containing 67 percent of all territories in core areas surveyed on Base. In core areas, 77 percent of male vireos were confirmed as paired; 76 percent of male vireos in non-core areas were confirmed as paired.</p><p>The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP decreased 3 percent from 2023. In five core survey area drainages, the number of territories increased by at least two, and in two core survey area drainages, the Santa Margarita River and Las Flores Creek, the number of vireo territories decreased by at least nine between 2023 and 2024. The number of vireo territories at Marine Corps Air Station, Camp Pendleton did not change from 2023 to 2024. The proportion of surveys during which Brown-headed Cowbirds (<i>Molothrus ater</i>) were detected decreased to 0.03 from a peak of 0.45 in 2022. Cowbirds were detected in April and June in 2024.</p><p>Most core-area vireos (58 percent, including transients) used mixed willow (<i>Salix</i> spp.) riparian habitat. An additional 9 percent of birds occupied willow habitat co-dominated by Western sycamores (<i>Platanus racemosa</i>). Riparian scrub dominated by mule fat (<i>Baccharis salicifolia</i>), sandbar willow (<i>S. exigua</i>), or blue elderberry (<i>Sambucus mexicana</i>) was used by 33 percent of vireos. Habitat dominated by non-native vegetation was used by 1 percent of vireos.</p><p>Since 2020, the number of vireos detected in each of the non-core survey groups was greater than expected, based on the change in vireo numbers in core survey areas. Although, the number of vireo territories on Base decreased from 2020–24, from approximately 1,224 to approximately 960, the trend in vireo territory numbers on Base since 2005 has been positive.</p><p>In 2019, MCBCP began operating an artificial seep along the Santa Margarita River; then, in 2021, two additional artificial seeps became operational. The artificial seeps pumped water to the surface during daylight hours starting in mid-April and ending in August each year and were designed to increase the amount of surface water to enhance Southwestern Willow Flycatcher (<i>Empidonax traillii extimus</i>) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited MCBCP, including the seep areas, within the past several years; therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents the fifth year of annual monitoring and analyses summarizing all 5 years of vireo and vegetation response to the artificial seeps.</p><p>In 2020, we established four study sites along the Santa Margarita River, two surrounding and extending downstream from existing and proposed seep pumps at the Old Treatment Ponds and along Pump Road and two Reference sites in similar habitat downstream from the Seep sites. Seep pumps began operating at the Old Treatment Ponds in 2020 and along Pump Road in 2021. In 2023, seep pumps at the Pump Road Seep site did not function, and we recategorized that study site as Intermediate. We sampled vegetation at Seep, Intermediate, and Reference sites to determine the effects of surface-water enhancement by seep pumps. In 2024, vegetation cover was highest near the ground and decreased with increasing height. Woody vegetation made up most of the cover at all height categories. We determined that Seep and Intermediate sites differed from each other in addition to differing from Reference sites, which likely is, in part, because seep-pump operation at the Intermediate site was inconsistent compared to the Seep site. Soil saturation in 2024 was high at the Intermediate site and was associated with high native herbaceous cover and low non-native herbaceous cover. Sites differed, with the Intermediate site having more upper canopy cover in general, the Seep site having more low woody cover, and the Reference sites having more mid-canopy non-native vegetation cover.</p><p>Soil saturation significantly increased from 2020 through 2024 at the Seep site and was significantly higher at Seep and Intermediate sites than at their paired Reference sites in all years. Soil saturation likely was increased by the supplemental surface water at the Seep site. However, soil saturation at the Intermediate site was not clearly associated with seep pumps but likely affected by soil saturation at the site before seep-pump installation and flooding from high precipitation. Canopy height increased at the Intermediate site from 2020 through 2024 and increased with increasing soil saturation at the Intermediate and Reference sites. The canopy at the Seep site was shorter than at the Intermediate and Reference sites and decreased from 2020 through 2024 because tall trees were damaged and killed by shothole borer beetles (<i>Euwallacea</i> spp.).</p><p>We used Redundancy Analysis to discover associations among vegetation types, plant species, and other environmental variables (soil saturation, site, precipitation, and seep operation, defined as the site and year seep pumps were operating). These associations explained less than 15 percent of the variability in the vegetation, with the remaining 85 percent of variation unexplained. Generally, as soil saturation increased, understory vegetation increased and non-native cover decreased in the mid-and upper canopy. Non-native herbaceous plant species decreased in wetter soil.</p><p>The Seep site was characterized by more understory and less canopy, contrasting with the Intermediate site, which was characterized by less understory and more higher canopy cover. The addition of surface water via seep pumps or precipitation was associated with more vegetation near the ground. Higher early winter precipitation was associated with taller canopy and more woody vegetation in the upper canopy. We also created a Redundancy Analysis model isolating the components of Southwestern Willow Flycatcher habitat, as identified by Howell and others (2018). In this model, increased soil saturation resulted in increased cover of stinging nettle (<i>Urtica dioica</i>) and black willow (<i>Salix gooddingii</i>) below 3 meters (m), total cover 3–6 m, and black willow above 6 m. Cover of poison hemlock (<i>Conium maculatum</i>) and stinging nettle below 3 m was higher at the Seep site and lower at the Intermediate site.</p><p>Vireo territory density among the Seep, Intermediate, and Reference sites was similar before the seep pumps were installed. However, vireo territory density at Seep and Intermediate sites combined was significantly higher than at Reference sites after the seep pumps were installed.</p><p>We banded and resighted color banded vireos as part of a long-term evaluation of vireo survival, site fidelity, between-year movement, and the effect of surface-water enhancement on vireo return rate and between-year movement. We banded 164 Least Bell's Vireo nestlings during the 2024 season.</p><p>In 2024, we resighted 31 Least Bell's Vireos on Base that had been banded before the 2024 breeding season, and we were able to identify 25 of them. Of the 25 that we could identify, 24 were banded on Base and 1 was originally banded on the San Luis Rey River. Adult birds of known age ranged from 1 to 9 years old.</p><p>Base-wide survival of vireos was affected by sex, age, and year. Males had significantly higher annual survival than females (60 percent versus 47 percent, respectively). Adults had higher annual survival than first-year vireos (61 percent versus 11 percent, respectively). The return rate of adult vireos to Seep, Intermediate, or Reference sites was not affected by the original banding site (Seep versus Intermediate versus Reference).</p><p>Most returning adult vireos, predominantly males, showed strong between-year site fidelity. Of the adults present in 2023, 92 percent (all males) returned in 2024 to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.4±0.03 kilometers (km). The average movement of first-year vireos detected in 2024 that fledged from a known nest on MCBCP in 2023 was 2.4±3.1 km.</p><p>We monitored 47 Least Bell's Vireo pairs to evaluate the effects of surface-water enhancement on nest success and breeding productivity. Breeding productivity in 2024 was similar among Seep, Intermediate, and Reference sites (2.8, 3.0, and 3.0 young fledged per pair, respectively), and the percentage of pairs that fledged at least one young was not significantly different among sites (83, 91, and 96 percent, respectively). According to the best model, daily nest survival from 2020–24 was not related to site. Other measures of breeding productivity were also similar among Seep, Intermediate, and Reference site pairs.</p><p>Between 2020 and 2024, the number of vireo fledglings produced per pair increased with increasing native herbaceous cover under 3 m and decreasing cover of all herbaceous vegetation under 5 m and was not affected by precipitation, site, or seep operation. The number of vireo fledglings produced per egg was lower at the Seep and Intermediate sites than at the Reference sites and increased with decreasing late winter precipitation, cover of poison hemlock, black mustard, non-native vegetation above 2 m, and all vegetation over 2 m. Vireo pairs at Seep and Intermediate sites were less likely to fledge young than vireo pairs at Reference sites. All vireo pairs were more likely to fledge young with less cover of poison hemlock and more cover of poison oak.</p><p>From 2020 through 2024, vireos placed their nests in 24 plant species. The most used plants in all years were willows, mostly red (<i>S. laevigata</i>), or arroyo (<i>S. lasiolepis</i>). The fate of a vireo nest (whether it successfully fledged young or not) was not affected by placement in native or non-native vegetation, by site, or by year, but nests were more likely to be successful if they were placed in woody plants than in herbaceous plants. Successful nests were placed higher in the host plant and farther from the outer edge of the nest clump than unsuccessful nests.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251057","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, U.S. Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Lynn, S., Houston, A., Kus, B.E., and Mendia, S.M., 2026, Distribution, abundance, breeding activities, and habitat use of the Least Bell's Vireo at Marine Corps Base Camp Pendleton, California—2020–24 summary report: U.S. Geological Survey Open-File Report 2025–1057, 128 p., https://doi.org/10.3133/ofr20251057.","productDescription":"xii, 128 p.","numberOfPages":"128","onlineOnly":"Y","ipdsId":"IP-176723","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498564,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1057/images"},{"id":498563,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1057 XML"},{"id":498562,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251057/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1057 HTML"},{"id":498561,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1057/ofr20251057.pdf","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1057 PDF"},{"id":498560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1057/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.5833,\n              33.5\n            ],\n            [\n              -117.5833,\n              33.1667\n            ],\n            [\n              -117.25,\n              33.1667\n            ],\n            [\n              -117.25,\n              33.5\n            ],\n            [\n              -117.5833,\n              33.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/werc\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Study Area and Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Least Bell’s Vireo Survey Areas at Marine Corps Base Camp Pendleton, 2024</li><li>Appendix 2. Vegetation Sampling Locations and Vegetation Sampling Data Sheet, Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 3. Principal Components Analysis Loadings for Vegetation Types and Plant Species at all Height Categories, 2020 through 2024</li><li>Appendix 4. Locations of Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 5. Number of Territorial Male Least Bell Vireos in Core Survey Areas at Marine Corps Base Camp Pendleton, California, by Drainage, 2005–24</li><li>Appendix 6. Proportion of Lease Bell’s Vireo Territories, Including Areas Occupied by Transients, Dominated or Co-Dominated by Non-Native Vegetation, by Drainage, 2005–24</li><li>Appendix 7. Redundancy Analysis Loadings for Model 1, Vegetation Type Variation</li><li>Appendix 8. Redundancy Analysis Loadings for Model 2, Plant Species Variation</li><li>Appendix 9. Redundancy Analysis Loadings for Vegetation Variation for Southwestern Willow Flycatcher Habitat</li><li>Appendix 10. Banded Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 11. Between-Year Movement of Adult and Juvenile Least Bell’s Vireos Detected at Marine Corps Base Camp Pendleton, California, 2024</li><li>Appendix 12. Status and Nesting Activities of Least Bell’s Vireos at Marine Corps Base Camp Pendleton, California, 2024</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2026-01-21","noUsgsAuthors":false,"publicationDate":"2026-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynn, Suellen 0000-0003-1543-0209 suellen_lynn@usgs.gov","orcid":"https://orcid.org/0000-0003-1543-0209","contributorId":3843,"corporation":false,"usgs":true,"family":"Lynn","given":"Suellen","email":"suellen_lynn@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houston, Alexandra 0000-0002-8599-8265 ahouston@usgs.gov","orcid":"https://orcid.org/0000-0002-8599-8265","contributorId":139460,"corporation":false,"usgs":true,"family":"Houston","given":"Alexandra","email":"ahouston@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendia, Shannon M. 0000-0003-4520-7024 smendia@usgs.gov","orcid":"https://orcid.org/0000-0003-4520-7024","contributorId":223097,"corporation":false,"usgs":true,"family":"Mendia","given":"Shannon","email":"smendia@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953618,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274601,"text":"70274601 - 2026 - Revisiting the geochronology of late Quaternary marine terraces and uplift rates in coastal Santa Barbara County, California, USA","interactions":[],"lastModifiedDate":"2026-04-01T21:13:19.203403","indexId":"70274601","displayToPublicDate":"2026-01-20T14:07:11","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Revisiting the geochronology of late Quaternary marine terraces and uplift rates in coastal Santa Barbara County, California, USA","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>In several early studies, central California marine terraces between Santa Barbara and Point Conception were interpreted to record sea-level high stands of the last interglacial complex, ∼80&nbsp;ka to ∼120&nbsp;ka (marine isotope stage [MIS] 5). These ages and their elevations (∼20&nbsp;m to ∼45&nbsp;m) indicate modest rates of tectonic uplift, similar to those from other localities in southern and central California. A recent study, using a combination of luminescence and radiocarbon dating, has challenged the older age interpretations, implying much younger terrace ages, between ∼40&nbsp;ka and&nbsp;∼55&nbsp;ka (MIS 3). From these new ages and a considerably lower sea level during MIS 3, much higher rates of tectonic uplift are inferred. In the present study, new uranium-series ages of terrace corals and amino acid age estimates of terrace mollusks were determined to test these competing interpretations. With the exception of a low-elevation terrace in Isla Vista (near Santa Barbara) that dates to MIS 3, terraces farther west are interpreted to date to MIS 5 and imply tectonic uplift rates of 0.20–0.34&nbsp;m/kyr. A compilation of data for the region yields a decreasing rate of late Quaternary uplift from east, near Ventura, to west, near Point Conception. This trend is interpreted to reflect a decreasing influence of the processes of compression and crustal shortening south of the Big Bend in the San Andreas fault.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2026.110179","usgsCitation":"Muhs, D., Schumann, R.R., Bright, J., Roberts, H.M., and Groves, L.T., 2026, Revisiting the geochronology of late Quaternary marine terraces and uplift rates in coastal Santa Barbara County, California, USA: Geomorphology, v. 501, 110179, 29 p., https://doi.org/10.1016/j.geomorph.2026.110179.","productDescription":"110179, 29 p.","ipdsId":"IP-175111","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Santa Barbara County","otherGeospatial":"coastal Santa Barbara County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.71849255644787,\n              34.941506886063436\n            ],\n            [\n              -120.71849255644787,\n              34.36620309495811\n            ],\n            [\n              -119.29011089848893,\n              34.36620309495811\n            ],\n            [\n              -119.29011089848893,\n              34.941506886063436\n            ],\n            [\n              -120.71849255644787,\n              34.941506886063436\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"501","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schumann, R. Randall 0000-0001-8158-6960 rschumann@usgs.gov","orcid":"https://orcid.org/0000-0001-8158-6960","contributorId":1569,"corporation":false,"usgs":true,"family":"Schumann","given":"R.","email":"rschumann@usgs.gov","middleInitial":"Randall","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bright, Jordon","contributorId":63981,"corporation":false,"usgs":false,"family":"Bright","given":"Jordon","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":958477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Helen M.","contributorId":369119,"corporation":false,"usgs":false,"family":"Roberts","given":"Helen","middleInitial":"M.","affiliations":[{"id":16758,"text":"Aberystwyth University","active":true,"usgs":false}],"preferred":false,"id":958478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Groves, Lindsey T. 0000-0002-2097-2689","orcid":"https://orcid.org/0000-0002-2097-2689","contributorId":365815,"corporation":false,"usgs":false,"family":"Groves","given":"Lindsey","middleInitial":"T.","affiliations":[{"id":12725,"text":"Natural History Museum of Los Angeles County","active":true,"usgs":false}],"preferred":false,"id":958479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273754,"text":"70273754 - 2026 - Widespread terrestrial ecosystem disruption at the onset of the Paleocene–Eocene Thermal Maximum","interactions":[],"lastModifiedDate":"2026-01-28T17:02:45.63779","indexId":"70273754","displayToPublicDate":"2026-01-20T10:58:29","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Widespread terrestrial ecosystem disruption at the onset of the Paleocene–Eocene Thermal Maximum","docAbstract":"<p><span>The Paleocene–Eocene Thermal Maximum (PETM, ~56 Mya) interval was marked by massive&nbsp;</span><sup>13</sup><span>C-depleted carbon emissions into the ocean/atmosphere system, manifested as a negative carbon isotope excursion (CIE) in sedimentary components, and ~5 °C global average warming. Episodes of hydrological perturbations and soil-erosion have been widely documented for the PETM but their link with vegetation- and carbon cycle changes remain poorly constrained. Here, we present organic microfossil evidence showing a strong increase in fern-dominated pioneer vegetation that replaced coniferous forests on the margin of the Norwegian Sea during the first millennia of the CIE. With the present stratigraphic constraints, the “fern spike” occurred simultaneously in terrestrial settings along the North Sea, Arctic Ocean, the US east coast and in southern Australia, indicating that pioneer vegetation persisted for several millennia following a partial collapse of previously stable terrestrial ecosystems. Both the ferns and influx of microcharcoal imply recurrent physical disturbance, including soil destabilization and erosion, potentially linked to droughts, wildfires, and strong hydrological forcing resulting from extreme climate change. Together with evidence for reworked clay minerals and ancient organic matter (kerogen), these findings show that highly disturbed terrestrial ecosystems were widespread across mid- and high-latitude regions globally. Carbon cycle model simulations suggest that a substantial loss of standing and buried biomass, along with oxidation of soil organic matter, acted as important positive feedbacks during the onset of the CIE. Additionally, enhanced kerogen weathering likely contributed as another major positive feedback throughout both the onset and main phase of the CIE.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2509231122","usgsCitation":"Nelissen, M., Willard, D., Konijnenburg-van Cittert, H., Bowen, G.J., Hollaar, T., Sluijs, A., Frieling, J., and Brinkhuis, H., 2026, Widespread terrestrial ecosystem disruption at the onset of the Paleocene–Eocene Thermal Maximum: Proceedings of the National Academy of Sciences, v. 123, no. 4, e2509231122, 8 p., https://doi.org/10.1073/pnas.2509231122.","productDescription":"e2509231122, 8 p.","ipdsId":"IP-177301","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":499331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2509231122","text":"Publisher Index Page"},{"id":499184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Nelissen, Mei","contributorId":362170,"corporation":false,"usgs":false,"family":"Nelissen","given":"Mei","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":954541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":954542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konijnenburg-van Cittert, Han","contributorId":365651,"corporation":false,"usgs":false,"family":"Konijnenburg-van Cittert","given":"Han","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":954543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowen, Gabriel J.","contributorId":365652,"corporation":false,"usgs":false,"family":"Bowen","given":"Gabriel","middleInitial":"J.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":954544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hollaar, Teuntje","contributorId":365653,"corporation":false,"usgs":false,"family":"Hollaar","given":"Teuntje","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":954545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sluijs, Appy","contributorId":215371,"corporation":false,"usgs":false,"family":"Sluijs","given":"Appy","email":"","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":954546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frieling, Joost","contributorId":365654,"corporation":false,"usgs":false,"family":"Frieling","given":"Joost","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":954547,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brinkhuis, Henk","contributorId":328591,"corporation":false,"usgs":false,"family":"Brinkhuis","given":"Henk","affiliations":[{"id":36885,"text":"Utrecht University","active":true,"usgs":false}],"preferred":false,"id":954548,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70273667,"text":"70273667 - 2026 - Toxicity of anticoagulant rodenticides on Pacific salmon: Assessing lethal and sublethal effects","interactions":[],"lastModifiedDate":"2026-01-22T15:25:07.928692","indexId":"70273667","displayToPublicDate":"2026-01-20T09:22:10","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23276,"text":"Ecotoxciology and Environmental Safety","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of anticoagulant rodenticides on Pacific salmon: Assessing lethal and sublethal effects","docAbstract":"<p><span>To restore native biodiversity on island ecosystems containing invasive rodents, partial- and whole-island eradications generally rely on broadcast baiting with anticoagulant rodenticides (ARs). This approach can result in bait pellets entering aquatic environments, raising concerns about effects to non-target fish. Salmonids are a dominant group of fishes on many temperate islands targeted for rodent eradication, and AR toxicity data for salmonids are limited. Our goal was to determine if coho salmon (</span><i>Oncorhynchus kisutch</i><span>) are susceptible to coagulopathy and death via exposure to commonly used ARs. We assessed risk of ARs to coho using dose-response curves generated through intraperitoneal injections after determining that coho would not directly ingest the AR baits. Median lethal doses (96-h LD</span><sub>50</sub><span>) estimated using 100 % corn oil carrier were 85.7 µg/g for brodifacoum and 54.0 µg/g for diphacinone. Acetone (30–41 %), used to dissolve ARs in corn oil, reduced the toxicity of diphacinone (LD</span><sub>50</sub><span>&nbsp;= 102.3 µg/g, p &lt; 0.001) but not brodifacoum (LD</span><sub>50</sub><span>&nbsp;= 73.3 µg/g, p = 0.126) indicating that solvent choice can influence toxicity outcomes. Behavioral changes and onset of mortality differed between the two ARs, with diphacinone acting more rapidly. Tissue analysis supported a difference in toxicokinetics between the two ARs, with significant decreases in liver and muscle residues for diphacinone but not brodifacoum. Sublethal brodifacoum exposure (53.9 µg/g; LD</span><sub>13</sub><span>) impaired blood clotting at 72- and 96- h but returned to baseline by 120 h. No clotting impairment was observed up to 144 h after diphacinone exposure (45.5 µg/g; LD</span><sub>4</sub><span>), suggesting a non-coagulopathy mode of action. These findings will inform risk assessments when considering use of these ARs for rodent management near streams and shorelines and clearly demonstrate that brodifacoum causes coagulopathy in coho.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoenv.2026.119748","usgsCitation":"Pavord, L.M., Driessnack, M.K., Shiels, A.B., Volker, S., Rattner, B., and McIntyre, J., 2026, Toxicity of anticoagulant rodenticides on Pacific salmon: Assessing lethal and sublethal effects: Ecotoxciology and Environmental Safety, v. 310, 119748, 10 p., https://doi.org/10.1016/j.ecoenv.2026.119748.","productDescription":"119748, 10 p.","ipdsId":"IP-182338","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoenv.2026.119748","text":"Publisher Index Page"},{"id":498837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"310","noUsgsAuthors":false,"publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pavord, Lillian M.","contributorId":365379,"corporation":false,"usgs":false,"family":"Pavord","given":"Lillian","middleInitial":"M.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":954239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driessnack, Melissa K.","contributorId":365380,"corporation":false,"usgs":false,"family":"Driessnack","given":"Melissa","middleInitial":"K.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":954240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shiels, Aaron B.","contributorId":365381,"corporation":false,"usgs":false,"family":"Shiels","given":"Aaron","middleInitial":"B.","affiliations":[{"id":37295,"text":"USDA APHIS","active":true,"usgs":false}],"preferred":false,"id":954241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Volker, Steven","contributorId":299456,"corporation":false,"usgs":false,"family":"Volker","given":"Steven","affiliations":[{"id":64850,"text":"USDA, APHIS","active":true,"usgs":false}],"preferred":false,"id":954242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rattner, Barnett A. 0000-0003-3676-2843","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":95843,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett A.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":954243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntyre, Jenifer","contributorId":365385,"corporation":false,"usgs":false,"family":"McIntyre","given":"Jenifer","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":954244,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273871,"text":"70273871 - 2026 - The surface is not superficial: Utilizing hyper-local thermal photogrammetry for pedestrian thermal comfort inquiry","interactions":[],"lastModifiedDate":"2026-02-11T15:13:43.569738","indexId":"70273871","displayToPublicDate":"2026-01-19T08:07:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The surface is not superficial: Utilizing hyper-local thermal photogrammetry for pedestrian thermal comfort inquiry","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The scale and magnitude of urban heating are often assessed using Satellite-Derived Land Surface Temperature (SD-LST). Yet, discrepancies in spatial resolution limit SD-LST’s ability to reflect pedestrian thermal experience, potentially leading to ineffective mitigation strategies. Hyper-local measurements of urban heat, defined as surface temperatures (T</span><sub>S</sub><span>) at the scale of pedestrian activity (e.g., bus stops or street segments), may provide more accurate insights into thermal comfort. This study compares hyper-local ~0.01 m resolution T</span><sub>S</sub><span>&nbsp;collected via consumer-grade Forward-Looking Infrared (FLIR) thermography with resampled 30 m resolution SD-LST from Landsat 8 and 9 images to evaluate their utility in predicting thermal comfort indices across 60 bus stops in Denver, Colorado. During the summer of 2023, 270 FLIR measurements were collected over 19 dates, with a four-day subset (</span><span class=\"html-italic\">n</span><span>&nbsp;= 33) coinciding with Landsat imagery. FLIR T</span><sub>S</sub><span>&nbsp;averaged 25.12 ± 5.39 °C, while SD-LST averaged 35.90 ± 12.56 °C, a significant 10.77 °C difference (95% CI: 6.81–14.73;&nbsp;</span><span class=\"html-italic\">p</span><span>&nbsp;&lt; 0.001). FLIR T</span><sub>S</sub><span>&nbsp;strongly correlated with biometeorological metrics such as air temperature and mean radiant temperature (r &gt; 0.8;&nbsp;</span><span class=\"html-italic\">p</span><span>&nbsp;&lt; 0.001), while SD-LST correlations were weak (r &lt; 0.3). Linear mixed-effects models using FLIR T</span><sub>S</sub><span>&nbsp;explained 50–66% of the variance in thermal comfort indices and met ISO 7726 standards. Each 1 °C increase in FLIR TS predicted a 0.75 °C rise in mean radiant temperature. These results highlight hyper-local thermography as a reliable, low-cost tool for urban heat resilience planning.</span></span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs18020348","usgsCitation":"Steinharter, L., Ibsen, P.C., deSouza, P., and McHale, M.R., 2026, The surface is not superficial: Utilizing hyper-local thermal photogrammetry for pedestrian thermal comfort inquiry: Remote Sensing, v. 18, no. 2, 348, 25 p., https://doi.org/10.3390/rs18020348.","productDescription":"348, 25 p.","ipdsId":"IP-183417","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499943,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18020348","text":"Publisher Index Page"},{"id":499747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.29210252650385,\n              39.926551113261525\n            ],\n            [\n              -105.29210252650385,\n              39.49581897348219\n            ],\n            [\n              -104.64227323476742,\n              39.49581897348219\n            ],\n            [\n              -104.64227323476742,\n              39.926551113261525\n            ],\n            [\n              -105.29210252650385,\n              39.926551113261525\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Steinharter, Logan","contributorId":366132,"corporation":false,"usgs":false,"family":"Steinharter","given":"Logan","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":955339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"deSouza, Priyanka","contributorId":366133,"corporation":false,"usgs":false,"family":"deSouza","given":"Priyanka","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":955341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHale, Melissa R.","contributorId":366135,"corporation":false,"usgs":false,"family":"McHale","given":"Melissa","middleInitial":"R.","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":955342,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70276245,"text":"70276245 - 2026 - Anuran occupancy of created wetlands within reforested legacy surface mines in Kentucky and West Virginia","interactions":[],"lastModifiedDate":"2026-05-20T15:07:28.862319","indexId":"70276245","displayToPublicDate":"2026-01-18T10:03:35","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Anuran occupancy of created wetlands within reforested legacy surface mines in Kentucky and West Virginia","docAbstract":"<p><span>Restoration of habitat is an important component of wildlife management. Surface coal mining has altered forest cover in the Central Appalachians, and most reclamation activities on previously mined lands result in non-native grasslands or shrub lands. The Forestry Reclamation Approach (FRA), which emphasizes non-native vegetation removal, soil decompaction, planting of native trees and shrubs, and, in some cases, wetland creation represents an alternative to grassland-based reclamation that may promote forest-associated wildlife on legacy surface mines. We used automated recording units to evaluate the response of anurans to created wetlands and the FRA in Kentucky and West Virginia, USA. We used a Bayesian community occupancy model to compare species occupancy and richness across a range of wetland sizes (6.6–252 m</span><sup>2</sup><span>) and 3 site types: 1) younger FRA (1–6 yr), 2) older FRA (7–23 yr), and 3) unmined, mature forests (&gt;100 yr). In addition, we evaluated factors influencing anuran detection probabilities. Mean occupancy and species richness in both states were highest in the younger FRA, suggesting anurans may rapidly colonize wetlands created on restored mines. In Kentucky, occupancy of several species (green frog [</span><i>Lithobates clamitans</i><span>], pickerel frog [</span><i>L. palustris</i><span>], and wood frog [</span><i>L. sylvaticus</i><span>]) was higher in larger created wetlands, but wetland size was not important in West Virginia. Daily minimum temperature positively influenced detection of anurans in both states, and time of day was also important for detection in West Virginia. Wetland creation and implementation of the FRA may be an important tool for wildlife managers aiming to improve anuran populations and diversity on legacy surface mines in the Central Appalachians.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70156","usgsCitation":"Newman, J.C., Price, S.J., Guzy, J.C., Castle, J., Cox, J.J., Larkin, J.L., and Barton, C.D., 2026, Anuran occupancy of created wetlands within reforested legacy surface mines in Kentucky and West Virginia: Journal of Wildlife Management, v. 90, no. 3, e70156, 16 p., https://doi.org/10.1002/jwmg.70156.","productDescription":"e70156, 16 p.","ipdsId":"IP-174480","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":504552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky, West Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.15472448573897,\n              38.6863505104738\n            ],\n            [\n              -79.79212746942159,\n              38.6863505104738\n            ],\n            [\n              -79.79212746942159,\n              38.416728830781494\n            ],\n            [\n              -80.15472448573897,\n              38.416728830781494\n            ],\n            [\n              -80.15472448573897,\n              38.6863505104738\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.02461619940031,\n              37.720169430689694\n            ],\n            [\n              -84.61403596283867,\n              37.720169430689694\n            ],\n            [\n              -84.61403596283867,\n              36.59273432467556\n            ],\n            [\n              -83.02461619940031,\n              36.59273432467556\n            ],\n            [\n              -83.02461619940031,\n              37.720169430689694\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"90","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Jillian C.","contributorId":371430,"corporation":false,"usgs":false,"family":"Newman","given":"Jillian","middleInitial":"C.","affiliations":[{"id":88141,"text":"ManTech SRS Technologies Inc.","active":true,"usgs":false}],"preferred":false,"id":961812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Steven J.","contributorId":371431,"corporation":false,"usgs":false,"family":"Price","given":"Steven","middleInitial":"J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":961813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":961814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castle, Joshua","contributorId":371432,"corporation":false,"usgs":false,"family":"Castle","given":"Joshua","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":961815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, John J.","contributorId":371433,"corporation":false,"usgs":false,"family":"Cox","given":"John","middleInitial":"J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":961816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larkin, Jeffrey L.","contributorId":371434,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","middleInitial":"L.","affiliations":[{"id":38138,"text":"Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":961817,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barton, Christopher D.","contributorId":371435,"corporation":false,"usgs":false,"family":"Barton","given":"Christopher","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":961818,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
]}