{"pageNumber":"11","pageRowStart":"250","pageSize":"25","recordCount":40758,"records":[{"id":70272733,"text":"70272733 - 2025 - Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0","interactions":[],"lastModifiedDate":"2025-12-05T16:02:59.966789","indexId":"70272733","displayToPublicDate":"2025-12-02T09:59:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0","docAbstract":"<p><span>Models of coastal barrier geomorphic and ecologic change are valuable tools for understanding and predicting when, where, and how barriers evolve and transition between ecogeomorphic states. Few existing models of barrier systems are designed to operate over spatiotemporal scales congruous with effective management practices (i.e., decades/kilometers, referred to herein as “mesoscales”), incorporate important ecogeomorphic feedbacks, and provide probabilistic projections of future change. Here, we present a new numerical model designed to address these gaps by explicitly yet efficiently simulating coupled aeolian, marine, vegetation, and shoreline components of barrier evolution over spatiotemporal scales relevant to management. The Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) simulates subaerial ecomorphologic change of undeveloped barrier systems over kilometers and decades using meter-scale spatial resolution and weekly time steps. MEEB applies simplified parameterizations to represent and couple key ecogeomorphic processes: dune growth, vegetation expansion and mortality, beach and foredune erosion, barrier overwash, and shoreline and shoreface change. The model is parameterized and calibrated with observed elevation, vegetation, and water level data for a case study site of North Core Banks, NC, USA. Simulated ecogeomorphic change in model hindcasts agrees well with observations, demonstrating both favorable skill scores and qualitatively correct behavior. We also describe an additional model framework for producing probabilistic projections that account for uncertainties related to future forcing conditions and intrinsic stochastic dynamics and demonstrate the probabilistic framework's utility with example forecast simulations. As a mesoscale model, MEEB is designed to investigate questions about future barrier ecogeomorphic change of moderate complexity, offering semi-qualitative predictions and semi-quantitative explanations. For example, MEEB can be used to investigate how climate-induced shifts in ecological composition may alter the likelihood of morphologic impacts or to generate probabilistic projections of ecogeomorphic state change.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-18-9319-2025","usgsCitation":"Reeves, I.R., Ashton, A.D., Lentz, E.E., Sherwood, C.R., Passeri, D., and Zeigler, S., 2025, Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0: Geoscientific Model Development, v. 18, p. 9319-9348, https://doi.org/10.5194/gmd-18-9319-2025.","productDescription":"30 p.","startPage":"9319","endPage":"9348","ipdsId":"IP-170312","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":497392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-18-9319-2025","text":"Publisher Index Page"},{"id":497142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Reeves, Ian Robert 0000-0002-6675-3756","orcid":"https://orcid.org/0000-0002-6675-3756","contributorId":363346,"corporation":false,"usgs":true,"family":"Reeves","given":"Ian","middleInitial":"Robert","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew D. 0000-0002-0241-3090","orcid":"https://orcid.org/0000-0002-0241-3090","contributorId":363347,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","middleInitial":"D.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":951467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zeigler, Sara 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951471,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70274180,"text":"70274180 - 2025 - Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective","interactions":[],"lastModifiedDate":"2026-03-04T22:38:45.947857","indexId":"70274180","displayToPublicDate":"2025-12-01T15:30:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective","docAbstract":"<p><span>Aeromagnetic and magnetotelluric (MT) data are used to better understand the geology and mineral resources near the Stibnite-Yellow Pine mining district in central Idaho. The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that allochthonous island-arc rocks west of the Salmon River suture are significantly more magnetic than the Laurentian continental rocks east of the suture and that the granitoids of the Idaho batholith have moderate to low magnetization in both early, metaluminous, and late, peraluminous phases. Application of tilt derivative to aeromagnetic data highlights major crustal-scale structures. The 5-km upward continued magnetic data indicate island-arc rocks have deep magnetic sources. The 110-km-long MT profile images resistivity structure to depths around 30 km. At shallow depths, resistivity corresponds to mapped geologic units, with moderate resistivities underlying volcanic and roof-pendant metasedimentary rocks and moderate to high resistivities occurring beneath the Idaho batholith. Crustal-scale moderate resistivities beneath the suture image the results of tectonomagmatic processes that accompanied suturing and translating allochthonous terranes. Low resistivity values beneath and fringing the batholith are derived from metasedimentary rocks that may have served as a melt source and reductant during melt generation and provided metals during later ore formation.</span></p><p><span>In the Stibnite-Yellow Pine mining district, a high-resolution aeromagnetic compilation is shown to correlate with mapped lithologies and mineral deposit-related structures. The RTP transform distinguishes magnetic and nonmagnetic granitoid phases of the Idaho batholith. The tilt derivative highlights metasedimentary rocks, some of which are favorable ore hosts. The Meadow Creek fault hosts the Stibnite and Hangar Flats deposits and is imaged as a magnetic low due to hydrothermal alteration. Reconstructions of magnetic anomaly offsets and orebodies indicate around 3 km of post-95 Ma dextral separation, with some or all of the offset inferred to postdate the main Au mineralization episode (61–66 Ma).</span></p>","language":"English","publisher":"GeoScienceWorld","doi":"10.5382/econgeo.5182","usgsCitation":"Anderson, E., Rodriguez, B.D., Lund, K., Dail, C., and Breen, B., 2025, Aeromagnetic and magnetotelluric imaging of west-central Idaho and the Stibnite-Yellow Pine mining district: A regional to district perspective: Economic Geology, v. 120, no. 8, p. 1899-1923, https://doi.org/10.5382/econgeo.5182.","productDescription":"26 p.","startPage":"1899","endPage":"1923","ipdsId":"IP-114615","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":500851,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.5182","text":"Publisher Index Page"},{"id":500769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"west-central Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.63626406020117,\n              44.307766155511956\n            ],\n            [\n              -115.63626406020117,\n              43.87879267849277\n            ],\n            [\n              -114.41828968668513,\n              43.87879267849277\n            ],\n            [\n              -114.41828968668513,\n              44.307766155511956\n            ],\n            [\n              -115.63626406020117,\n              44.307766155511956\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"120","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Eric D. 0000-0002-0138-6166","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":202072,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":956794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":956795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lund, Karen 0000-0002-4249-3582 klund@usgs.gov","orcid":"https://orcid.org/0000-0002-4249-3582","contributorId":1235,"corporation":false,"usgs":true,"family":"Lund","given":"Karen","email":"klund@usgs.gov","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":956796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dail, Christopher","contributorId":367119,"corporation":false,"usgs":false,"family":"Dail","given":"Christopher","affiliations":[{"id":87550,"text":"Midas Gold Idaho, Donnelly, ID 83615","active":true,"usgs":false}],"preferred":false,"id":956797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breen, Bill","contributorId":367120,"corporation":false,"usgs":false,"family":"Breen","given":"Bill","affiliations":[{"id":87551,"text":"Independent Consultant, Hope, Idaho 83836","active":true,"usgs":false}],"preferred":false,"id":956798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273917,"text":"70273917 - 2025 - Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.","interactions":[],"lastModifiedDate":"2026-02-17T21:07:05.234713","indexId":"70273917","displayToPublicDate":"2025-12-01T11:42:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1717,"text":"GCAGS Journal","active":true,"publicationSubtype":{"id":10}},"title":"Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.","docAbstract":"The Early Cretaceous (Berriasian–Hauterivian) Hosston Formation in Louisiana and eastward is time correlative to the Travis Peak Formation of Texas and southern Arkansas. The formation is a first-order clastic sequence with a regional carbonate transgressive surface as an upper contact. The Hosston and Travis Peak formations contain conventional natural gas and oil accumulations that have been produced for nearly a century. These mature reservoirs contain terrigenous fluvial-deltaic, shore-zone, and paralic deposits across the productive trend; organic-lean mudstone and siltstone lithologies are found outboard of the Lower Cretaceous shelf margin. Producing reservoirs exhibit normal pressure gradients from 0.43 to 0.55 psi/ft (9.7 to 12.4 kpa/m), depths from 4000 to over 20,000 ft (1220 to 6100 m), and temperatures from 150 to 385°F (65 to 196°C). Wells are primarily vertical completions. The number of new field wildcats has been declining since the late 1990s. This paper presents comprehensive geologic models, which include lithofacies maps, structure and isopach maps, burial history models, regional seismic interpretations, and events charts that underpin the recently completed U.S. Geological Survey assessment of undiscovered, technically recoverable hydrocarbons within the Hosston and Travis Peak formations. This study also provides geographic and stratigraphic distributions of Hosston–Travis Peak reservoir properties, including geopressure, reservoir temperature, porosity, permeability, API gravity, and gas-oil ratios. Results indicate estimated undiscovered, technically recoverable mean resources of 28 million barrels of oil and 35.8 trillion cubic ft of gas in conventional and continuous accumulations within the Lower Cretaceous Hosston and Travis Peak formations of the onshore U.S. Gulf Coast region. Quantitative assessment results are detailed in U.S. Geological Survey Fact Sheet 2025–3021 and associated Data Release.","language":"English","publisher":"Gulf Coast Association of Geological Societies","doi":"10.62371/STWR8033","usgsCitation":"Burke, L.A., Paxton, S.T., Kinney, S.A., Gianoutsos, N.J., Dubiel, R., and Pitman, J., 2025, Geologic models underpinning the 2024 U.S. Geological Survey assessment of undiscovered oil and gas resources in the Hosston and Travis Peak Formations of the onshore Gulf Coast region, U.S.A.: GCAGS Journal, v. 14, p. 87-105, https://doi.org/10.62371/STWR8033.","productDescription":"19 p.","startPage":"87","endPage":"105","ipdsId":"IP-171733","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":500123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500094,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://gcags.org/Journal/2025_V14/2025_GCAGS_Journal_v14_07_p87-105_Burke_Et_Al.html"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.06103212694106,\n              38.66590683410158\n            ],\n            [\n              -104.06103212694106,\n              24.0496145009851\n            ],\n            [\n              -78.58542051058421,\n              24.0496145009851\n            ],\n            [\n              -78.58542051058421,\n              38.66590683410158\n            ],\n            [\n              -104.06103212694106,\n              38.66590683410158\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burke, Lauri A. 0000-0002-2035-8048 lburke@usgs.gov","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":3859,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","email":"lburke@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Stanley T. 0000-0002-9098-1740 spaxton@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-1740","contributorId":739,"corporation":false,"usgs":true,"family":"Paxton","given":"Stanley","email":"spaxton@usgs.gov","middleInitial":"T.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubiel, Russell F. 0000-0002-1280-0350","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":214101,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955759,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pitman, Janet K. 0000-0002-0441-779X","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":228982,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet K.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955760,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70274042,"text":"70274042 - 2025 - Habitat selection by Rocky Mountain Population greater Sandhill Cranes (Antigone canadensis tabida) during spring and autumn migration at a key stopover area","interactions":[],"lastModifiedDate":"2026-02-23T17:04:09.417799","indexId":"70274042","displayToPublicDate":"2025-12-01T10:57:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23304,"text":"Avian Conservation and Ecology.","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Habitat selection by Rocky Mountain Population greater Sandhill Cranes (<i>Antigone canadensis tabida</i>) during spring and autumn migration at a key stopover area","title":"Habitat selection by Rocky Mountain Population greater Sandhill Cranes (Antigone canadensis tabida) during spring and autumn migration at a key stopover area","docAbstract":"<p><span>The San Luis Valley (SLV), Colorado is a critical stopover area for Rocky Mountain Population greater Sandhill Cranes (</span><i>Antigone canadensis tabida</i><span>). During spring and autumn, cranes use crops for foraging and water resources adjacent to foraging areas for roosting and loafing. However, surface water is becoming increasingly limited in the SLV. Understanding the factors that affect use by roosting, loafing, and foraging cranes and where habitat is the most limiting will inform water and habitat management under changing conditions. We used mixed-effects models to determine the effects of habitat variables, ownership, and landcover type on the selection of roosting, loafing, and foraging areas by cranes marked with GPS transmitters (2015–2021). We found that Sandhill Cranes selected for areas with a high amount of water, relatively short vegetation (&lt; 5 m in autumn, &lt; 10 m in spring), close to grain fields (&lt; 5 km), and areas identified as open water for roosting. Loafing Sandhill Cranes also selected for areas with short vegetation and close to grain fields but that had less water and more sandbar and were identified as pastures or wetlands. Although selection was higher for private land overall, we found evidence of avoidance of private lands and a stronger preference for public lands with increasing surface water for roosting in spring. For foraging areas, selection was highest for barley in both seasons, but triticale and other grains had relatively high selection in autumn. Our research confirms the importance of providing roosting and loafing areas on both private and public lands close to foraging areas and provides evidence that roosting and loafing opportunities may be most limited on public lands in the SLV.</span></p>","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ACE-02924-200214","usgsCitation":"Vanausdall, R.A., Kendall, W.L., Collins, D.P., Donnelly, J.P., Hays, Q.R., 2025, Habitat selection by Rocky Mountain Population greater Sandhill Cranes (Antigone canadensis tabida) during spring and autumn migration at a key stopover area: Avian Conservation and Ecology., v. 20, no. 2, 14, 19 p., https://doi.org/10.5751/ACE-02924-200214.","productDescription":"14, 19 p.","ipdsId":"IP-167764","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500589,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02924-200214","text":"Publisher Index Page"},{"id":500424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Luis Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107,\n              38.5\n            ],\n            [\n              -107,\n              37\n            ],\n            [\n              -105,\n              37\n            ],\n            [\n              -105,\n              38.5\n            ],\n            [\n              -107,\n              38.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanausdall, Rachel A.","contributorId":366817,"corporation":false,"usgs":false,"family":"Vanausdall","given":"Rachel","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Daniel P.","contributorId":366821,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel","middleInitial":"P.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donnelly, J. Patrick","contributorId":366822,"corporation":false,"usgs":false,"family":"Donnelly","given":"J.","middleInitial":"Patrick","affiliations":[{"id":81227,"text":"Intermountain West Joint Venture","active":true,"usgs":false}],"preferred":false,"id":956276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hays, Quentin R.","contributorId":366823,"corporation":false,"usgs":false,"family":"Hays","given":"Quentin","middleInitial":"R.","affiliations":[{"id":87508,"text":"Geosystems Analysis","active":true,"usgs":false}],"preferred":false,"id":956277,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70271457,"text":"70271457 - 2025 - Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States","interactions":[],"lastModifiedDate":"2026-01-13T16:43:42.167219","indexId":"70271457","displayToPublicDate":"2025-12-01T10:40:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19892,"text":"Journal of North American Bat Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-scale predictors of Northern Long-eared Bat (<i>Myotis septentrionalis</i>) occupancy in the United States","title":"Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States","docAbstract":"<p><span>Historically,&nbsp;</span><i>Myotis septentrionalis</i><span>&nbsp;(Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).</span></p>","language":"English","publisher":"Eagle Hill Institute","usgsCitation":"Wray, A.K., Udell, B.J., Davis, H.T., Inman, R.D., Lohre, B.T., Price, H.B., Reichard, J.D., Schuhmann, A.N., Straw, B., Tousley, F.C., Utrup, J., Wiens, A.M., and Reichert, B., 2025, Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States: Journal of North American Bat Research, v. 3, no. 15, p. 1-18.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-170297","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":495577,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eaglehill.us/NABRonline/access-pages/015-Wray-accesspage.shtml"},{"id":498592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"15","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wray, Amy Kristine 0000-0001-9685-8308","orcid":"https://orcid.org/0000-0001-9685-8308","contributorId":334941,"corporation":false,"usgs":true,"family":"Wray","given":"Amy","email":"","middleInitial":"Kristine","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udell, Bradley James 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":271174,"corporation":false,"usgs":true,"family":"Udell","given":"Bradley","email":"","middleInitial":"James","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Helen Trice 0000-0001-5449-4331","orcid":"https://orcid.org/0000-0001-5449-4331","contributorId":336752,"corporation":false,"usgs":true,"family":"Davis","given":"Helen","middleInitial":"Trice","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":948819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lohre, Bennet Thomas 0000-0002-7991-3093","orcid":"https://orcid.org/0000-0002-7991-3093","contributorId":336754,"corporation":false,"usgs":true,"family":"Lohre","given":"Bennet","middleInitial":"Thomas","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948820,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Price, Haley Breiann 0009-0003-2850-0971","orcid":"https://orcid.org/0009-0003-2850-0971","contributorId":336755,"corporation":false,"usgs":true,"family":"Price","given":"Haley","middleInitial":"Breiann","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948821,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reichard, Jonathan D. 0000-0002-4792-2868","orcid":"https://orcid.org/0000-0002-4792-2868","contributorId":337073,"corporation":false,"usgs":false,"family":"Reichard","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":948822,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schuhmann, Andrea Nichole 0009-0005-8244-4303","orcid":"https://orcid.org/0009-0005-8244-4303","contributorId":329059,"corporation":false,"usgs":true,"family":"Schuhmann","given":"Andrea","email":"","middleInitial":"Nichole","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948823,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Straw, Bethany R. 0000-0001-9086-4600","orcid":"https://orcid.org/0000-0001-9086-4600","contributorId":271020,"corporation":false,"usgs":true,"family":"Straw","given":"Bethany","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948824,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tousley, Frank Charles 0000-0002-6859-7558","orcid":"https://orcid.org/0000-0002-6859-7558","contributorId":304216,"corporation":false,"usgs":true,"family":"Tousley","given":"Frank","middleInitial":"Charles","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948825,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Utrup, Jill","contributorId":336764,"corporation":false,"usgs":false,"family":"Utrup","given":"Jill","affiliations":[{"id":40296,"text":"United States Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":948826,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948827,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948828,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70272697,"text":"70272697 - 2025 - Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","interactions":[],"lastModifiedDate":"2025-12-04T16:26:55.8147","indexId":"70272697","displayToPublicDate":"2025-12-01T10:13:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimation of dynamic geologic CO<sub>2</sub> storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","title":"Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity","docAbstract":"<p><span>Since the vast majority of carbon dioxide (CO</span><sub>2</sub><span>) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO</span><sub>2</sub><span>&nbsp;storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO</span><sub>2</sub><span>&nbsp;injection rates can be enhanced by extracting brine from the CO</span><sub>2</sub><span>&nbsp;storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO</span><sub>2</sub><span>&nbsp;storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO</span><sub>2</sub><span>&nbsp;injectivity at an injection site that has access to multiple geologic storage units where either CO</span><sub>2</sub><span>&nbsp;or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO</span><sub>2</sub><span>-water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO</span><sub>2</sub><span>&nbsp;injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO</span><sub>2</sub><span>&nbsp;in one unit from interfering with the injection of either brine or CO</span><sub>2</sub><span>&nbsp;in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO</span><sub>2</sub><span>&nbsp;injectivities and enhancement of CO</span><sub>2</sub><span>&nbsp;injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO</span><sub>2</sub><span>&nbsp;injectivity. They also suggest that only injecting CO</span><sub>2</sub><span>&nbsp;into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO</span><sub>2</sub><span>&nbsp;injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO</span><sub>2</sub><span>&nbsp;into all of the accessible and suitable storage units was more likely to maximize the CO</span><sub>2</sub><span>&nbsp;storage resource.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2025.1639952","usgsCitation":"Plampin, M.R., Anderson, S.T., Finsterle, S., and Wiens, A.M., 2025, Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity: Frontiers in Earth Science, v. 13, 1639952, 18 p., https://doi.org/10.3389/feart.2025.1639952.","productDescription":"1639952, 18 p.","ipdsId":"IP-177734","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":497113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2025.1639952","text":"Publisher Index Page"},{"id":497059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Kentucky, Indiana","otherGeospatial":"Illinois Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.66105038187163,\n              41.36771728120675\n            ],\n            [\n              -91.66105038187163,\n              37.13535863641968\n            ],\n            [\n              -84.79728409671057,\n              37.13535863641968\n            ],\n            [\n              -84.79728409671057,\n              41.36771728120675\n            ],\n            [\n              -91.66105038187163,\n              41.36771728120675\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Plampin, Michelle R. 0000-0003-4068-5801","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":363249,"corporation":false,"usgs":false,"family":"Plampin","given":"Michelle","middleInitial":"R.","affiliations":[{"id":86662,"text":"USGS, Geology, Energy & Minerals Science Center, DRP not in active directory","active":true,"usgs":false}],"preferred":false,"id":951354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":951355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Finsterle, Stefan","contributorId":299677,"corporation":false,"usgs":false,"family":"Finsterle","given":"Stefan","email":"","affiliations":[{"id":64929,"text":"Finsterle GeoConsulting, Inc.","active":true,"usgs":false}],"preferred":false,"id":951356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951357,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273720,"text":"70273720 - 2025 - Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2026-01-26T16:15:03.676695","indexId":"70273720","displayToPublicDate":"2025-12-01T09:57:32","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin","docAbstract":"Geothermal resources exist in sedimentary rock where circulation of water for efficient extraction or storage of heat is possible. Except in rare instances where hot water is expressed at the land surface, sedimentary geothermal resources are hidden, so the identification of these systems is optimally accomplished using predictive subsurface modeling.  An integrated approach using detailed paleogeographic interpretations, subsurface geologic mapping, and numerical modeling has produced regional geologic and temperature models for the Upper Colorado River Basin, a large watershed in central North America that contains many sedimentary basins. These models identify areas of hidden sedimentary geothermal resource potential in low temperature (<90°C), moderate temperature (90–150°C), and high temperature (>150°C) fairways across the study area. These models incorporate maps of key horizons in outcrop and the subsurface to create a robust structural framework that can be used to target favorable geology for natural or engineered permeability. This framework is populated with lithologies derived from detailed palaeogeographical maps and over 40,000 bottom hole temperature (BHT) values were used to create a calibrated three-dimensional (3D) temperature model across the region. The resulting maps serve as a regional sedimentary geothermal play fairway screening tool for evaluating different grades of sedimentary geothermal resources and for identifying areas of interest where more detailed, prospect-scale studies can be undertaken.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Gardner, R., Birdwell, J.E., Sweetkind, D., Sullivan, P., Eaton, M., Petermann, H., Clement, A., Hagadorn, J., and Woda, J., 2025, Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin, <i>in</i> Using the Earth to save the Earth, v. 49, p. 1512-1525.","productDescription":"14 p.","startPage":"1512","endPage":"1525","ipdsId":"IP-180873","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499003,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035309"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105,\n              43.25\n            ],\n            [\n              -113,\n              43.25\n            ],\n            [\n              -113,\n              34\n            ],\n            [\n              -105,\n              34\n            ],\n            [\n              -105,\n              43.25\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":954433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":210808,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":954434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Patrick","contributorId":348055,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":954435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eaton, Melia","contributorId":365598,"corporation":false,"usgs":false,"family":"Eaton","given":"Melia","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":954436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Petermann, Holger","contributorId":365599,"corporation":false,"usgs":false,"family":"Petermann","given":"Holger","affiliations":[{"id":27833,"text":"Denver Museum of Nature and Science","active":true,"usgs":false}],"preferred":false,"id":954437,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clement, Annaka","contributorId":365600,"corporation":false,"usgs":false,"family":"Clement","given":"Annaka","affiliations":[{"id":27833,"text":"Denver Museum of Nature and Science","active":true,"usgs":false}],"preferred":false,"id":954438,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hagadorn, James","contributorId":365601,"corporation":false,"usgs":false,"family":"Hagadorn","given":"James","affiliations":[{"id":27833,"text":"Denver Museum of Nature and Science","active":true,"usgs":false}],"preferred":false,"id":954439,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Woda, Joshua 0000-0002-2932-8013","orcid":"https://orcid.org/0000-0002-2932-8013","contributorId":290172,"corporation":false,"usgs":true,"family":"Woda","given":"Joshua","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954440,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70274537,"text":"70274537 - 2025 - What is the (real) rate of soil health practice adoption? Making sense of three data sources","interactions":[],"lastModifiedDate":"2026-04-01T14:57:42.259853","indexId":"70274537","displayToPublicDate":"2025-12-01T09:53:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"What is the (real) rate of soil health practice adoption? Making sense of three data sources","docAbstract":"<p><span>Conservation stakeholders looking to quantify the impact of their investments to increase soil health practice adoption over time often face challenges in interpreting practice adoption data due to discrepancies in language and results among data sources. Similarly, efforts to estimate environmental outcomes of practice adoption, such as water quality and greenhouse gas emissions, can vary depending on different practice adoption input data. To help make sense of different adoption data sources, we compared county-level adoption data for winter cover crops (WCC), no-till (NT), and reduced tillage (RT) in three areas of the United States with contrasting climates and production systems: central Illinois (CIL), southern Illinois (SIL), and western New York (WNY). We analyzed data available during 2015 through 2022 from the Operational Tillage Information System (OpTIS, remote sensing), US Census of Agriculture (AgCensus, a farmer survey), and, specifically in Illinois, the Illinois Soil Conservation Transect Survey (Transect, a roadside survey). The magnitude of differences between the datasets depended on the practice and geographic location. For example, OpTIS and AgCensus tillage data were much more similar in Illinois (average difference of less than 4 percentage points) compared to New York (average differences of 20 percentage points). Similarly, there was less variability and smaller differences between OpTIS and AgCensus WCC data in Illinois compared to WNY. AgCensus tended to report lower WCC adoption for Illinois and greater adoption in WNY compared to OpTIS. All data sources agreed that the rate of change in tillage practices is slow (mainly –1% to 1%) and that adoption of WCC is low (assuming linear growth, it could take nearly a century to reach 50% WCC adoption in CIL). Differences among the datasets were attributed to definitional inconsistencies for RT and NT and how WCC data were acquired. For example, the AgCensus asks if a WCC was planted, whereas OpTIS and Transect evaluate the presence of a standing WCC. Data sources also reflect different time periods (calendar years or crop years) and types of cropland assessed (corn [</span><i>Zea mays</i><span>&nbsp;L.], soybean [</span><i>Glycine max</i><span>&nbsp;{L.} Merr.], or all cropland). We propose two recommendations to improve interpretation and consistency: (1) a working group to harmonize definitions and protocols and develop educational materials for data users, and (2) a research effort that integrates different adoption data types and produces publicly available adoption data at HUC-10 and county scales. Such activities could help improve data access and utility for evidence-based conservation decision-making and enhance the accuracy of environmental models that rely on adoption data as input.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00224561.2025.2580218","usgsCitation":"McGill, B.M., Hively, W.D., Puntel, L.A., Shriver, J., Thieme, A.N., Manter, D.K., and Moore, J.M., 2025, What is the (real) rate of soil health practice adoption? Making sense of three data sources: Journal of Soil and Water Conservation, v. 80, no. 6, p. 724-733, https://doi.org/10.1080/00224561.2025.2580218.","productDescription":"10 p.","startPage":"724","endPage":"733","ipdsId":"IP-172017","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":501927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McGill, Bonnie M.","contributorId":368946,"corporation":false,"usgs":false,"family":"McGill","given":"Bonnie","middleInitial":"M.","affiliations":[{"id":87675,"text":"American Farmland Trust","active":true,"usgs":false}],"preferred":false,"id":958154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":958156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puntel, Laila A.","contributorId":368947,"corporation":false,"usgs":false,"family":"Puntel","given":"Laila","middleInitial":"A.","affiliations":[{"id":87676,"text":"Syngenta Group","active":true,"usgs":false}],"preferred":false,"id":958155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriver, John","contributorId":368948,"corporation":false,"usgs":false,"family":"Shriver","given":"John","affiliations":[{"id":87677,"text":"Regrow","active":true,"usgs":false}],"preferred":false,"id":958157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thieme, Alison N.","contributorId":368949,"corporation":false,"usgs":false,"family":"Thieme","given":"Alison","middleInitial":"N.","affiliations":[{"id":87678,"text":"USDA-ARS-SASL","active":true,"usgs":false}],"preferred":false,"id":958158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Manter, Daniel K.","contributorId":368950,"corporation":false,"usgs":false,"family":"Manter","given":"Daniel","middleInitial":"K.","affiliations":[{"id":87679,"text":"USDA-ARS-SMSBR","active":true,"usgs":false}],"preferred":false,"id":958159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Jennifer M.","contributorId":368951,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","middleInitial":"M.","affiliations":[{"id":87680,"text":"USDA-ARS-FSCRU","active":true,"usgs":false}],"preferred":false,"id":958160,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273263,"text":"70273263 - 2025 - The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi","interactions":[],"lastModifiedDate":"2025-12-29T15:58:04.83704","indexId":"70273263","displayToPublicDate":"2025-12-01T09:52:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The continued decline of the Palila (<i>Loxioides bailleui</i>) on Mauna Kea, Island of Hawaiʻi","title":"The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi","docAbstract":"<p><span>Palila (</span><i>Loxioides bailleui</i><span>) are critically endangered Hawaiian honeycreepers specializing on māmane (</span><i>Sophora chrysophylla</i><span>) seeds and restricted to Mauna Kea volcano on the Island of Hawaiʻi. Recently, the population was estimated to decline by 89% between 1998 and 2021, despite decades of ungulate removal, fence construction, māmane regeneration, fire suppression, and predator control. To inform managers with the most recent update on the status and trends of the Palila population, we analyzed annual bird survey data collected using point-transect distance sampling since 1998, including new annual survey data from 2022, 2023, and 2024. Prior to analysis, we predicted the population trajectory would change between 2021 and 2024 because of continued management actions promoting habitat recovery. We used distance sampling, log-linear regression, and state-space modeling to produce the new estimates and analyze trends across the time series. The 2022 population estimate was 367 to 742 birds (95% confidence interval; point estimate: 545), the lowest in recorded history. The 2023 and 2024 estimates of 374 to 842 birds (point estimate: 596) and 412 to 970 birds (point estimate: 666) were the second and third lowest in our time series, respectively. Our estimates for years before 2022 show population fluctuations between 4000 to 6800 birds from 1998 to 2005, then a steep decline through 2010. For the next decade, abundance fluctuated around 1000 birds, before declining again in 2021 to less than 700 birds. From 1998 to 2024, the population declined by more than 90%, or 205 birds per year, with 100% statistical support for an overall downward trend, despite significant management efforts and research. The greatest threats facing the Palila, if familiar, are not being eliminated swiftly enough to promote their recovery. The currently small and range-limited population is vulnerable to future climate-related events such as drought and fire. Continued monitoring can help to assess the response of Palila to adaptive management actions and changing environmental conditions.</span></p>","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-02920-200210","usgsCitation":"Hunt, N., Asing, C.K., Nietmann, L., Banko, P.C., and Camp, R.J., 2025, The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi: Avian Conservation and Ecology, v. 20, no. 2, 10, 18 p., https://doi.org/10.5751/ACE-02920-200210.","productDescription":"10, 18 p.","ipdsId":"IP-177477","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":498272,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02920-200210","text":"Publisher Index Page"},{"id":498146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.62,\n              19.84\n            ],\n            [\n              -155.62,\n              19.736678155129184\n            ],\n            [\n              -155.4741502151662,\n              19.736678155129184\n            ],\n            [\n              -155.4741502151662,\n              19.84\n            ],\n            [\n              -155.62,\n              19.84\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunt, Noah","contributorId":355564,"corporation":false,"usgs":false,"family":"Hunt","given":"Noah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":952938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asing, Chauncey K.","contributorId":272645,"corporation":false,"usgs":false,"family":"Asing","given":"Chauncey","email":"","middleInitial":"K.","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":952939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nietmann, Lindsey","contributorId":331548,"corporation":false,"usgs":false,"family":"Nietmann","given":"Lindsey","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":952940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":952941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":952942,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70272168,"text":"70272168 - 2025 - Estimation of the accessible and useful resource base for electric-grade enhanced geothermal systems (EGS) resources of the Great Basin, USA","interactions":[],"lastModifiedDate":"2026-01-16T15:45:31.50898","indexId":"70272168","displayToPublicDate":"2025-12-01T09:43:12","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimation of the accessible and useful resource base for electric-grade enhanced geothermal systems (EGS) resources of the Great Basin, USA","docAbstract":"Scientists with the U.S. Geological Survey (USGS) recently completed a provisional assessment of the electric-grade geothermal resources associated with the low-permeability geologic formations of the Great Basin, USA, where resources are assumed to be accessible using enhanced geothermal systems (EGS) technologies (i.e., the engineering of sufficient permeability to facilitate efficient heat extraction).  This assessment required estimation of the accessible resource base (electric-grade heat [>90ºC] at depths where drilling and stimulation are deemed achievable using current technology) and useful resource (heat that can be extracted from the accessible region). Electric-grade heat can be estimated from existing temperature models. The accessible resource base can be estimated as the electric-grade heat that exists at depths shallower than 6 km based on the limitations of current drilling and stimulation technologies, along with evidence for sustained natural fracture conductivity at depth. The useful part of the accessible heat can be estimated as the product of three efficiencies and factors:  the heat extraction efficiency, the viable geology factor, and the reservoir spacing efficiency.  The accessible and useful parts of the resource can be estimated in units of heat, or in units of electric power using an electrical conversion efficiency, which is a function of resource temperature.  We also estimate the ranges for each of the efficiencies and describe the motivations behind the choice of best estimates used for the recent assessment.  An analytic solution is provided for the useful resource above any depth (in units of electric power), where efficiency estimation assumes nearly steady heat extraction rates that cool reservoirs to 90ºC over 30 years of power generation.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resource Council","usgsCitation":"Burns, E., Frash, L.P., and Williams, C.F., 2025, Estimation of the accessible and useful resource base for electric-grade enhanced geothermal systems (EGS) resources of the Great Basin, USA, <i>in</i> Using Earth to save the Earth, v. 49, p. 2020-2034.","productDescription":"15 p.","startPage":"2020","endPage":"2034","ipdsId":"IP-178656","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":498744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498743,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035334"}],"country":"United States","otherGeospatial":"Great Basin","volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frash, Luke P. 0000-0002-5424-4698","orcid":"https://orcid.org/0000-0002-5424-4698","contributorId":362313,"corporation":false,"usgs":false,"family":"Frash","given":"Luke","middleInitial":"P.","affiliations":[{"id":48588,"text":"Los Alamos National Lab","active":true,"usgs":false}],"preferred":false,"id":950292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272571,"text":"sir20255097 - 2025 - Quality of groundwater used for domestic supply in the Gilroy-Hollister basin and surrounding areas, California, 2022","interactions":[],"lastModifiedDate":"2026-02-03T16:41:44.226534","indexId":"sir20255097","displayToPublicDate":"2025-12-01T09:37:12","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5097","displayTitle":"Quality of Groundwater Used for Domestic Supply in the Gilroy-Hollister Basin and Surrounding Areas, California, 2022","title":"Quality of groundwater used for domestic supply in the Gilroy-Hollister basin and surrounding areas, California, 2022","docAbstract":"<p>More than 2&nbsp;million Californians rely on groundwater from domestic wells for drinking-water supply. This report summarizes a 2022 California Groundwater Ambient Monitoring and Assessment Priority Basin Project (GAMA-PBP) water-quality survey of 33 domestic and small-system drinking-water supply wells in the Gilroy-Hollister Valley groundwater basin and the surrounding areas, where more than 20,000 residents are estimated to utilize privately owned domestic wells. The study area includes the Llagas subbasin in the north, the North San Benito subbasin in the south, and the surrounding uplands. The study was focused on groundwater resources used for domestic drinking-water supply, which are mostly drawn from shallower parts of aquifer systems rather than those of groundwater resources used for public drinking-water supply in the same area. This assessment characterized the quality of ambient groundwater in the aquifer before filtration or treatment, rather than the quality of drinking water delivered to the tap.</p><p>To provide context, the measured concentrations of constituents in groundwater were compared to Federal and California State regulatory and non-regulatory benchmarks for drinking-water quality. A grid-based method was used to estimate the areal proportions of groundwater resources used for domestic drinking wells that have water-quality constituents present at high concentrations (above the benchmark), moderate concentrations (between one-half of the benchmark and the benchmark for inorganic constituents, or between one-tenth of the benchmark and the benchmark for organic constituents), and low concentrations (less than one-half or one-tenth the benchmark for inorganic and organic constituents, respectively). This method provides statistically representative results at the study-area scale and permits comparisons to other GAMA-PBP study areas. In the study area, inorganic constituents in groundwater were greater than regulatory benchmarks (U.S.&nbsp;Environmental Protection Agency [EPA] or State of California maximum contaminant levels [MCLs]) for public drinking-water quality in 24&nbsp;percent of domestic groundwater resources. The inorganic constituents present at concentrations greater than MCLs for drinking water were nitrate (as nitrogen), barium, chromium, and selenium. Total dissolved solids (TDS) or manganese were present at concentrations greater than the secondary maximum contaminant levels (SMCLs) that the State of California uses as aesthetic-based benchmarks in 48&nbsp;percent of domestic groundwater resources. No volatile organic compounds or pesticide constituents were present at concentrations greater than regulatory benchmarks. Total coliform bacteria and enterococci were detected in 4&nbsp;percent of domestic groundwater resources. Per- and polyfluoroalkyl substances (PFAS) were detected in 19&nbsp;percent of domestic groundwater resources, and 10&nbsp;percent had concentrations greater than recently enacted (April 2024) EPA MCLs.</p><p>Physical and chemical factors from natural and anthropogenic sources that could affect the groundwater quality were evaluated using results from statistical testing of associations between constituent concentrations and potential explanatory variables. In this study, relevant physical factors include well construction characteristics, groundwater age, site proximity to groundwater recharge or discharge zones, and potential sources of contamination. Relevant chemical factors include the initial chemistry of the recharge water, the mineralogy of the aquifer sediments, and the subsequent shifts in chemistry as biologic and geologic reactions alter groundwater in the subsurface.</p><p>Nitrate concentrations were correlated to agricultural land use, distance from the boundary of the Gilroy-Hollister Valley groundwater basin, and the proportion of modern (post-1950s) water captured by the well. Denitrification under anoxic redox conditions can mitigate some nitrate derived from fertilizer application. Total dissolved solids primarily were derived from water-rock interactions with soils and aquifer materials in the study area, but there were high concentrations where agricultural practices contributed additional TDS. Mineralogy of aquifer sediments and rocks also affect barium, selenium, boron, and chromium concentrations in the Gilroy-Hollister Valley groundwater basin. PFAS were positively correlated with urban land use and the proportion of modern water captured by the well.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255097","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Faulkner, K.E., and Jurgens, B.C., 2025, Quality of groundwater used for domestic supply in the Gilroy-Hollister basin and surrounding areas, California, 2022: U.S. Geological Survey Scientific Investigations Report 2025–5097, 26 p., https://doi.org/10.3133/sir20255097.","productDescription":"viii, 26 p.","onlineOnly":"Y","ipdsId":"IP-160699","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":496802,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/sir/2025/5097/sir20255097.XML","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5097"},{"id":496800,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5097/coverthb.jpg"},{"id":497802,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119048.htm"},{"id":496804,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5097/sir20255097.XML"},{"id":496803,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5097/images"},{"id":496801,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5097/sir20255097.pdf","text":"Report","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5097"}],"country":"United States","state":"California","otherGeospatial":"Gilroy-Hollister basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.61037451371827,\n              37.22507246909019\n            ],\n            [\n              -121.7786749960862,\n              37.08414386069212\n            ],\n            [\n              -121.42503094452843,\n              36.75628159886837\n            ],\n            [\n              -121.29294616762297,\n              36.61961329116167\n            ],\n            [\n              -121.07884238942088,\n              36.64012907347609\n            ],\n            [\n              -121.29720693932853,\n              36.95316849961171\n            ],\n            [\n              -121.61037451371827,\n              37.22507246909019\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/california-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/california-water-science-center\">California Water Science Center</a><br>U.S. Geological Survey<br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Introduction</li><li>Hydrologic Setting</li><li>Methods for Evaluating Groundwater Quality</li><li>Overview of Water-Quality Results</li><li>Factors that Affect Groundwater Quality</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2025-12-01","noUsgsAuthors":false,"plainLanguageSummary":"<p>The U.S. Geological Survey works with the California State Water Resources Control Boards’ Groundwater Ambient Monitoring and Assessment Program to study the quality of groundwater used for&nbsp;<span style=\"mso-spacerun: yes;\" data-mce-style=\"mso-spacerun: yes;\">&nbsp;</span>drinking-water supplies across California. This report examines the quality of groundwater collected from 33 private domestic wells in the Gilroy-Hollister Valley groundwater basin and surrounding area in California’s Central Coast region. Groundwater samples were analyzed for human-made and naturally occurring substances that can be found dissolved in groundwater. They were also analyzed for geochemical tracers that can be used to help determined the age of the groundwater and processes affecting the concentrations of dissolved constituents. The water-quality data were compared to Federal and State benchmarks that are applied to public drinking water, such as regulatory maximum contaminant levels (MCLs). Nitrate was detected at concentrations greater than its Federal MCL benchmark in 17 percent of the groundwater samples. Nitrate concentrations above natural background levels were associated with greater agricultural land use near the well, wells tapping a higher proportion of younger groundwater, and absence of anoxic conditions that promote degradation of nitrate. No volatile organic compounds or pesticide constituents were detected at concentrations greater than MCLs, however per- and polyfluoroalkyl substances (PFAS) were detected at concentrations greater than the Federal MCLs enacted in April 2024 in about 10 percent of the groundwater samples. PFAS are used in many consumer products and industrial processes. Occurrences of these elevated concentrations of PFAS were not associated with known potential sources of PFAS contamination to groundwater but were positively correlated with urban land use and the proportion of younger groundwater tapped by the well. Total dissolved solids (TDS, a measure of salinity) were detected at concentrations about the State nonregulatory upper secondary MCL in 24 percent of the groundwater samples. TDS is primarily derived from natural interactions between water and aquifer materials although agricultural practices may contribute additional TDS is some areas. About 20,000 residents in the Gilroy-Hollister area, and more than 2 million people in California, use private domestic wells for drinking water. Therefore, assessing the quality of groundwater used by domestic wells and understanding the factors affecting that quality is important for protecting public health.</p>","publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Faulkner, Kirsten E. 0000-0003-1628-2877","orcid":"https://orcid.org/0000-0003-1628-2877","contributorId":362930,"corporation":false,"usgs":false,"family":"Faulkner","given":"Kirsten","middleInitial":"E.","affiliations":[{"id":68550,"text":"California Water Science Center","active":true,"usgs":false}],"preferred":false,"id":950836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127839,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","email":"bjurgens@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":950837,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70273375,"text":"70273375 - 2025 - Environmental DNA monitoring of invasive Central American boas in St. Croix at Salt River Bay National Historical Park and Ecological Preserve (SARI)","interactions":[],"lastModifiedDate":"2026-01-09T15:44:43.191562","indexId":"70273375","displayToPublicDate":"2025-12-01T09:35:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":18517,"text":"Science Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SR—2025/367","title":"Environmental DNA monitoring of invasive Central American boas in St. Croix at Salt River Bay National Historical Park and Ecological Preserve (SARI)","docAbstract":"<p><span>Invasive Central American boas (<i>Boa imperator</i>) have established a reproducing population on the western side of St. Croix, U.S. Virgin Islands but prevalence throughout the island is largely unknown. The large snakes threaten endemic and endangered species through competition and predation, jeopardizing island biodiversity. Environmental DNA (eDNA) methods were used to investigate occurrence and focal areas for management efforts in the Salt River Bay National Historical Park and Ecological Preserve (SARI). To validate a previously developed assay, we collected tissue samples and 13 × 60 mL water samples from a captive boa enclosure in St. Croix. We implemented this assay for both a pilot and main field sampling effort. The pilot in December 2023 resulted in analysis of 7 × 60 mL water samples per site from SARI (3 sites) and from the western forests where boas are established (1 site). The main sampling event in July 2024 collected 15 × 60 mL water samples per site within SARI (11 sites) and western forests (4 sites). Pilot sample replicates were filtered individually, while main samples were consolidated into groups, resulting in seven replicates for pilot sites and five replicates for main event sites, totaling 103 environmental samples. eDNA was isolated using a modified phenol-chloroform isolation method to remove PCR inhibitors, and target eDNA was amplified using droplet digital PCR technology. Water samples from the captive boa amplified target eDNA in 12 of 13 samples, indicating assay effectiveness ex-situ. Low concentrations of eDNA (below the 95% limit of detection) were amplified in 4 of 5 sites in the western forest and in 8 of 14 sites within the National Historic Park. Overall, boa eDNA concentrations were consistently low, as expected in water samples targeting a semi-arboreal snake species with a low rate of eDNA shedding. Further optimization of methods could enable recovery of greater eDNA concentrations in future studies. Additional eDNA method testing and ground-truthing may help to improve the assessment of invasive <i>Boa imperator</i> in St. Croix.</span></p>","language":"English","publisher":"National Park Service","doi":"10.36967/2315977","usgsCitation":"Beaver, C., Tays, A.B., Santos, W.F., Harman, M.E., Ewen, K.A., Gwilliam, E.L., and Hunter, M., 2025, Environmental DNA monitoring of invasive Central American boas in St. Croix at Salt River Bay National Historical Park and Ecological Preserve (SARI): Science Report NPS/SR—2025/367, viii, 29 p., https://doi.org/10.36967/2315977.","productDescription":"viii, 29 p.","ipdsId":"IP-174727","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":498507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Salt River Bay National Historical Park and Ecological Preserve, St. Croix, U.S. Virgin Islands","geographicExtents":"{\n  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We analyzed more than 1.4 million bottom-hole temperature (BHT) records from oil and gas well logs to create corrected temperature-depth profiles in a grid across the United States. Total depth values, where available, in documented orphan wells from a U.S. Geological Survey (USGS) database were then correlated to these temperature-depth profiles to estimate a corrected BHT for each orphan well. The orphan wells were then categorized as having low (<90°C), moderate (90–150°C), and high (>150°C) geothermal potential, identifying them as wells in the U.S. that could be used to access geothermal resources. In addition, repurposing these wells could contribute to broader environmental and economic goals, including well remediation, rogue methane emissions reduction, and energy production. 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Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":954451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":954453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":205943,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":954454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954455,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lei, Uei I.","contributorId":365612,"corporation":false,"usgs":false,"family":"Lei","given":"Uei","middleInitial":"I.","affiliations":[{"id":87166,"text":"OWPO","active":true,"usgs":false}],"preferred":false,"id":954456,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sullivan, Patrick","contributorId":348055,"corporation":false,"usgs":false,"family":"Sullivan","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":954457,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70272298,"text":"70272298 - 2025 - Preventing overfitting when using tree-based methods for mapping hydrothermal favorability","interactions":[],"lastModifiedDate":"2026-01-16T15:40:22.275487","indexId":"70272298","displayToPublicDate":"2025-12-01T09:32:29","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preventing overfitting when using tree-based methods for mapping hydrothermal favorability","docAbstract":"Ensemble tree-based algorithms are robust tools for estimating sparsely distributed resources with non-linear dependencies (e.g., hydrothermal systems). These algorithms naturally accommodate the threshold conditions necessary to enable and support hydrothermal systems (e.g., having sufficient heat and permeability) and are simpler than many other non-linear machine learning strategies (e.g., artificial neural networks), which is an advantage when working with few labeled examples from which to learn. In previous work, we used eXtreme Gradient Boosting (XGBoost) to produce regional prediction and uncertainty maps of hydrothermal favorability; however, recent studies suggest that, even when properly applied, XGBoost has some risk of overfitting when there are few labeled examples from which to learn.\n\nTo evaluate overfitting when constructing hydrothermal favorability maps with tree-based methods, we compare XGBoost with Extremely Randomized Trees (ExtraTrees), another ensemble tree-based algorithm that has the potential to underfit when using few labeled examples. We hold all other modeling parameters constant, resulting in two contrasting favorability maps of conventional geothermal resources for the Great Basin. Our results indicate that ExtraTrees demonstrably reduces overfitting compared with XGBoost. After considering overall performance, we conclude that ExtraTrees provides a more suitable modeling approach than XGBoost for the purposes of conventional hydrothermal resource assessments.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Mordensky, S.P., Burns, E., Lipor, J., and DeAngelo, J., 2025, Preventing overfitting when using tree-based methods for mapping hydrothermal favorability, <i>in</i> Using Earth to save the Earth, v. 49, p. 179-203.","productDescription":"25 p.","startPage":"179","endPage":"203","ipdsId":"IP-180956","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":498742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":498741,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035236"}],"volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":950720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950721,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273143,"text":"70273143 - 2025 - Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems","interactions":[],"lastModifiedDate":"2025-12-16T15:37:04.093312","indexId":"70273143","displayToPublicDate":"2025-12-01T09:31:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems","docAbstract":"<p><span>World-class Carlin-type Au deposits hosted in sedimentary rock were formed when profuse Eocene silicic magmatism swept across northern Nevada in response to arc migration. Carlin-type Au deposits formed along with porphyry/skarn Cu-Mo-W-Au deposits, epithermal Ag-Au deposits, and distal disseminated Ag-Au deposits. But unlike these other Au-bearing deposits that have clear associations with igneous intrusions, Carlin-type ore deposits appear to have formed distant from concealed plutons, and their origin remains controversial. Despite decades of abundant geophysical, geochronological, and geochemical studies suggesting the involvement of magmas, concrete evidence for magmatic involvement is still lacking. Consequently, the involvement of contemporaneous igneous systems remains inferred based on age, proximity, and variable isotopic, geochemical, and geophysical clues. A recent synthesis of deposit models postulates that Carlin-type Au deposits are intrusion-related, but that the causative magmas reside deeper (∼6–12&nbsp;km) than in typical porphyry and peripheral systems (∼3–5&nbsp;km), meaning that Carlin-type deposits are perhaps more distal expressions of igneous intrusions. We investigate a collection of “suspect” magmatic systems over a ∼7&nbsp;m.y. timespan (∼41–34 Ma) that are contemporaneous with and near known Carlin-type ore deposits. We report results of a multifaceted array of in situ geochemical analyses (FTIR, EMP, SHRIMP-RG, LA-ICP-MS) of quartz-hosted melt inclusions, biotite, and quartz to better characterize the pre-eruptive characteristics of these magmas. We also report results of thermobarometry and thermodynamic phase equilibria modeling to help place constraints on magmatic reservoir depths and processes. Rather than a single “flavor” of silicic magma, we observe a surprisingly broad compositional spectrum of rhyolites, with one end of the spectrum exhibiting more arc-like (I-type) characteristics and the other end displaying more post-subduction, thick-crust extensional (A-type) characteristics. This broad compositional spectrum suggests a more complex picture of silicic crustal magmatism operating over a narrow span of time during slab rollback. Despite this spectrum, magmatic systems in this study are consistently ferroan and generally peraluminous, which we interpret as an expression of the relatively elevated geotherm at the time and incorporation of variable amounts of highly peraluminous metasedimentary crustal components. The silicic magma spectrum encompasses a range of mineralization associations, including subduction-related Cu-Mo-W-Au-Ag and post-subduction, thick-crust extensional rare-metal Mo-Sn-W-F-Be-Ag-Au, consistent with the prolific and diverse array of ore deposits that formed during this time. Carlin-type Au deposition appears to be associated with nearly the entire magmatic spectrum. This apparent indifference to silicic magma “flavor” would seem to imply that if magmas are involved in Carlin-type Au deposit genesis, they perhaps do not need to be compositionally specialized and/or possibly are only relevant as heat sources driving circulation to remobilize and redistribute metals.</span></p>","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2024-9372","usgsCitation":"Mercer, C.N., Roberge, J., Khoury, R., and Hofstra, A.H., 2025, Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems: American Mineralogist, v. 110, no. 2, p. 1898-1918, https://doi.org/10.2138/am-2024-9372.","productDescription":"21 p.","startPage":"1898","endPage":"1918","ipdsId":"IP-097749","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120,\n              42\n            ],\n            [\n              -120,\n              38\n            ],\n            [\n              -114,\n              38\n            ],\n            [\n              -114,\n              42\n            ],\n            [\n              -120,\n              42\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"110","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":952438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberge, Julie","contributorId":152268,"corporation":false,"usgs":false,"family":"Roberge","given":"Julie","email":"","affiliations":[{"id":18893,"text":"Instituto Politecnico Nacional, ESIA-Ticoman","active":true,"usgs":false}],"preferred":false,"id":952439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khoury, Regina Marie 0000-0003-2421-986X","orcid":"https://orcid.org/0000-0003-2421-986X","contributorId":294769,"corporation":false,"usgs":true,"family":"Khoury","given":"Regina Marie","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":952440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":952441,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273724,"text":"70273724 - 2025 - Exploring Martian geothermal and liquid water potential with basin modeling","interactions":[],"lastModifiedDate":"2026-01-26T15:33:39.007527","indexId":"70273724","displayToPublicDate":"2025-12-01T09:27:01","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring Martian geothermal and liquid water potential with basin modeling","docAbstract":"<p>Assessing the potential for geothermal energy and liquid water presence in the Martian subsurface is crucial for future exploration and habitability studies. In this work, we employed comprehensive&nbsp;finite element model simulations adapted specifically for Martian conditions to estimate subsurface temperatures and the potential for liquid water at depth within Martian crater basins.&nbsp;Rock and fluid property values for basin fill were carefully adjusted to match Martian gravity, radiogenic heat generation, and compositional characteristics derived from rover analyses, Martian&nbsp;meteorite samples, and orbital spectroscopy data. Multiple modeling scenarios were explored to systematically evaluate end-member cases across critical variables such as heat flow, lithological&nbsp;composition, and average surface temperature. Sensitivity testing revealed that heat flow and average annual surface temperatures are the most important variables. Results were used in&nbsp;calculations based on a database of Martian craters to estimate the temperature of crater fill at depth. Our model results indicate significant potential for sustained liquid water in the subsurface&nbsp;within sedimentary deposits across a range of crater sizes and latitudes. They further suggest that viable geothermal reservoirs likely exist and are potentially accessible for future Martian missions&nbsp;seeking energy sources or exploring astrobiological hypotheses. This study provides a methodological framework for geothermal and hydrological assessments for the subsurface of&nbsp;Mars, contributing to ongoing planetary exploration strategies.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Gardner, R., Birdwell, J.E., French, K.L., Okubo, C., Pitman, J., Paxton, S.T., and Flaum, J.A., 2025, Exploring Martian geothermal and liquid water potential with basin modeling, <i>in</i> Using the Earth to save the Earth, v. 49, p. 1526-1541.","productDescription":"16 p.","startPage":"1526","endPage":"1541","ipdsId":"IP-180860","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499005,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035310"}],"otherGeospatial":"Mars","volume":"49","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":954444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":954445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Okubo, Chris 0000-0001-9776-8128 cokubo@usgs.gov","orcid":"https://orcid.org/0000-0001-9776-8128","contributorId":174209,"corporation":false,"usgs":true,"family":"Okubo","given":"Chris","email":"cokubo@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":954446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitman, Janet K. 0000-0002-0441-779X","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":228982,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":954447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paxton, Stanley T. 0000-0002-9098-1740 spaxton@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-1740","contributorId":739,"corporation":false,"usgs":true,"family":"Paxton","given":"Stanley","email":"spaxton@usgs.gov","middleInitial":"T.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954448,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flaum, Jason A. 0000-0003-1251-1142","orcid":"https://orcid.org/0000-0003-1251-1142","contributorId":300809,"corporation":false,"usgs":true,"family":"Flaum","given":"Jason","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954449,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273723,"text":"70273723 - 2025 - Potential for co-production of lithium and geothermal resources in the Gulf Coast","interactions":[],"lastModifiedDate":"2026-01-26T15:53:11.820202","indexId":"70273723","displayToPublicDate":"2025-12-01T09:13:50","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Potential for co-production of lithium and geothermal resources in the Gulf Coast","docAbstract":"<p>Lithium brine extractions and geothermal resource developments often are not economically viable as standalone projects, but they May become cost effective when the potential for both resources exist within the same reservoir. Subsurface datasets were analyzed to identify areas in the U.S. Gulf Coast region with potential for lithium brine and geothermal heat recovery. Temperature, lithium brine content, and reservoir quality data for thirty-four depositional units were evaluated using spatial analysis to interpret high-grade areas where both resources likely coexist. For sedimentary geothermal systems, potential resource areas are sorted by resource grade: as low temperature (&lt;90°C, direct use potential), moderate temperature (90–150°C, direct use and electricity generation), and high temperature (&gt;150°C, primarily electricity generation). Lithium resources were defined by Li lithium brine concentrations in parts per million (ppm): low potential (&lt;100ppm), moderate potential (100–200ppm), and high potential (&gt;200ppm). &nbsp;Reservoir quality affects the viability of both resources and is evaluated using interpreted lithofacies that describe the depositional environments of each unit. Using the results, a series of play fairway analysis maps were generated to support regional evaluations of lithium and geothermal resources and to identify areas of interest for detailed, prospect-scale studies.&nbsp;</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Gardner, R., and Birdwell, J.E., 2025, Potential for co-production of lithium and geothermal resources in the Gulf Coast, <i>in</i> Using the Earth to save the Earth, v. 49, p. 410-418.","productDescription":"9 p.","startPage":"410","endPage":"418","ipdsId":"IP-180858","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499004,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035250"}],"country":"United States","state":"Alabama, Flroida, Georgia, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -102.52415578331033,\n              33.70981542560081\n            ],\n            [\n              -102.52415578331033,\n              24.00347152136203\n            ],\n            [\n              -79.56997834883599,\n              24.00347152136203\n            ],\n            [\n              -79.56997834883599,\n              33.70981542560081\n            ],\n            [\n              -102.52415578331033,\n              33.70981542560081\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954442,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70272971,"text":"70272971 - 2025 - Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","interactions":[],"lastModifiedDate":"2025-12-11T14:50:29.76691","indexId":"70272971","displayToPublicDate":"2025-12-01T08:41:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","docAbstract":"<p><span>Classification of massive datasets by machine learning (ML) algorithms is promising for many scientific domains, especially wildlife monitoring programs that rely on passive acoustic surveys for detecting species. However, treating ML-predicted class labels (e.g., species identity) as truth biases inferences of focal parameters within common modeling frameworks. One solution is to model the misclassification process explicitly using human-validated true-class labels for a subset of observations. Validation by experts can present a substantial bottleneck in otherwise efficient workflows that use ML predictions. Bioacoustics practitioners seek guidance on both the quantity and process for selecting ML-labeled data to validate by an expert. We derive an alternative model formulation that jointly models human-validated and ML-predicted class labels with an observed-data likelihood (ODL) and use empirically informed simulations motivated by a real-data application to explore different probability designs for selecting class labels for validation. Simulation results suggest that with smaller validation sets the ODL formulation increases computational speed and reduces estimation error compared to a default MCMC data augmentation routine. Our methodology is transferable to applications that treat predictions from classification algorithms as the response variable of interest.</span></p>","language":"English","publisher":"Project Euclid","doi":"10.1214/25-AOAS2096","usgsCitation":"Oram, J., Banner, K.M., Stratton, C., Hoegh, A., and Irvine, K., 2025, Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data: Annals of Applied Statistics, v. 19, no. 4, p. 2957-2980, https://doi.org/10.1214/25-AOAS2096.","productDescription":"24 p.","startPage":"2957","endPage":"2980","ipdsId":"IP-149507","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":497379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/25-aoas2096","text":"Publisher Index Page"},{"id":497320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oram, Jacob 0009-0001-8405-529X","orcid":"https://orcid.org/0009-0001-8405-529X","contributorId":353522,"corporation":false,"usgs":false,"family":"Oram","given":"Jacob","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Katharine M.","contributorId":363761,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoegh, Andrew","contributorId":265906,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70272620,"text":"dr1217 - 2025 - Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","interactions":[],"lastModifiedDate":"2026-02-03T16:40:49.220576","indexId":"dr1217","displayToPublicDate":"2025-12-01T07:18:23","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1217","displayTitle":"Range-wide Population Trend Analysis for Greater Sage-Grouse (<em>Centrocercus urophasianus</em>)—Updated 1960–2024","title":"Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","docAbstract":"<p>Greater sage-grouse (<i>Centrocercus urophasianus</i>; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population trend analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefiting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2024. Included in this report are methodological updates to lek count data aggregation, state-space model forecasting, and targeted annual warning system signals, which are detailed under individual Modification sections. State-space models estimated a 2.9-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.2 and 3.4 percent. Cumulative declines were 41.2, 64.1, and 78.8 percent range-wide in Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1217","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Ecosystems Mission Areas—Species Management Research Program and Land Management Research Program","usgsCitation":"Prochazka, B.G., Coates, P.S., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2025, Range-wide population trend analysis for greater sage-grouse (<em>Centrocercus urophasianus</em>)—Updated 1960–2024: U.S. Geological Survey Data Report 1217, 22 p., https://doi.org/10.3133/dr1217.","productDescription":"Report: viii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-182475","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496879,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.XML"},{"id":496877,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"USGS data release","description":"USGS data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (ver. 4.0, November 2025)"},{"id":496878,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1217/images"},{"id":496874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1217/coverthb.jpg"},{"id":496875,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1217"},{"id":496876,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1217/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1217"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.02726904687307,\n              37.11378745198651\n            ],\n            [\n              -107.91246282672654,\n              39.23148053932573\n            ],\n            [\n              -104.18656479624082,\n              42.68923879351195\n            ],\n            [\n              -104.09712675152082,\n              44.90768367632023\n            ],\n            [\n              -103.10713250018665,\n              45.28903162099806\n            ],\n            [\n              -103.07124138706033,\n              46.81624492709619\n            ],\n            [\n              -105.38823344586734,\n              48.94676636341262\n            ],\n            [\n              -120.30657593063506,\n              48.87342393238805\n            ],\n            [\n              -120.60087183124688,\n              42.81488245718879\n            ],\n            [\n              -120.58608571052426,\n              38.32426094909158\n            ],\n            [\n              -117.42786260245566,\n              36.55795546064512\n            ],\n            [\n              -113.02726904687307,\n              37.11378745198651\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br>U.S. Geological Survey<br>3020 State University Drive East<br>Sacramento, California 95819</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>Introduction</li><li>Study Area</li><li>Data Compilation and Inputs</li><li>Range-Wide Sage-Grouse Population Model</li><li>Range-Wide Population Trends</li><li>Climate Cluster Population Trends</li><li>Probability of Future Extirpation</li><li>Watches and Warnings from a Targeted Annual Warning System</li><li>References Cited</li><li>Glossary</li></ul>","publishedDate":"2025-12-01","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":950973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":950974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":950975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":950976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":950977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":950978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanser, Steve E. 0000-0002-4430-2073 shanser@usgs.gov","orcid":"https://orcid.org/0000-0002-4430-2073","contributorId":152523,"corporation":false,"usgs":true,"family":"Hanser","given":"Steve","email":"shanser@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":950979,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wiechman, Lief A. 0000-0002-3804-4426","orcid":"https://orcid.org/0000-0002-3804-4426","contributorId":184047,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","email":"","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":950980,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chenaille, Michael P. 0000-0003-3387-7899 mchenaille@usgs.gov","orcid":"https://orcid.org/0000-0003-3387-7899","contributorId":194661,"corporation":false,"usgs":true,"family":"Chenaille","given":"Michael","email":"mchenaille@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":950981,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70273001,"text":"70273001 - 2025 - A framework for analyzing wild turkey summer sighting data.","interactions":[],"lastModifiedDate":"2025-12-12T17:19:15.483358","indexId":"70273001","displayToPublicDate":"2025-11-30T10:04:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A framework for analyzing wild turkey summer sighting data.","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Wildlife agencies collect data on productivity (e.g., proportion of hens with poults and number of poults per hen) of wild turkey (</span><i>Meleagris gallopavo</i><span>) to monitor population status and trends. However, sampling protocols to collect productivity data rely on opportunistic observations reported by wildlife agency personnel and the public and have changed over time and differed among agencies. A protocol to standardize data collection was adopted by most state wildlife agencies in 2019, but long-term historical datasets exist that cannot be analyzed readily to make inferences about spatial and temporal patterns in wild turkey productivity. We developed statistical models to allow comparisons and model trends in productivity among and within states even though data collection protocols changed over time and differed among states. We found greater spatial variation in the proportion of hens with poults than the number of poults per brood, which may reflect how environmental factors influence wild turkey productivity. Our models can also provide inferences about productivity when data are limited or temporally discontinuous for some spatial units. Additionally, we found that temporal and spatial variation in data collection, even under the new protocol, can affect inferences about trends in productivity. The statistical models we developed address the uncontrolled nature of when and where data are collected and offer the ability to investigate long-term patterns of productivity in relation to factors such as changing climate or habitat conditions.</span></span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1623","usgsCitation":"Diefenbach, D.R., Buderman, F.E., Casalena, M.J., Dye, M., Gates, R., Gigliotti, L., Long, C., Martin, K., Muthersbaugh, M., Peters, M.L., Sloan, J., Stiller, J., and Wiley, M., 2025, A framework for analyzing wild turkey summer sighting data.: Wildlife Society Bulletin, v. 49, no. 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,{"id":70273257,"text":"70273257 - 2025 - The Hawaiian Volcanoes Supersite: Open data for the benefit of science and society","interactions":[],"lastModifiedDate":"2025-12-29T15:14:02.021347","indexId":"70273257","displayToPublicDate":"2025-11-28T09:09:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"The Hawaiian Volcanoes Supersite: Open data for the benefit of science and society","docAbstract":"<p><span>The Hawaiian Volcanoes Supersite was established in 2008 with the goal of making large amounts of volcano monitoring data, especially satellite measurements, freely available at a site of international interest, scientific importance, and impactful natural hazards. The location was chosen because of the long history of volcanological research and innovation on the Island of Hawaiʻi, as well as the need for monitoring, assessing, and mitigating volcanic hazards for the local population. Ground-based data are provided by the U.S. Geological Survey Hawaiian Volcano Observatory, and several national space agencies have contributed thousands of satellite synthetic aperture radar and other data that would have otherwise required special grants or commercial purchase. Since the Hawaiian Volcanoes Supersite was initiated, the vast quantity of open space-based data has resulted in the development of new applications and methodologies, successful responses to volcanic crises, and research that has informed monitoring and hazards mitigation activities. While there remain opportunities for additional coordination among supersite users and for synergistic studies that make use of the full spectrum of available ground- and space-based data, the Hawaiian Volcanoes Supersite has achieved its goals of stimulating basic research to better understand Hawaiian volcanism and aiding in responses to hazardous geologic processes. 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,{"id":70272712,"text":"70272712 - 2025 - Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis","interactions":[],"lastModifiedDate":"2025-12-05T14:42:36.637757","indexId":"70272712","displayToPublicDate":"2025-11-28T08:34:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis","docAbstract":"<p><span>Sources, transport mechanisms and pathways of fine sediment in river systems are dependent on a multitude of climatic, geomorphic and anthropogenic factors, resulting in geomorphic equifinality, in which it is difficult to parse how different landscape processes affect sediment transport across different spatiotemporal scales. The objectives of this study are to 1) provide a conceptual model to consider how differing spatial distributions and hydrologic timing of sediment sources, both upland and in-channel, can result in equifinal sediment transport outcomes, and 2) utilize analytical methods with widely available environmental datasets to infer sediment processes from stream gaging data. Hysteretic patterns of observed storm events were classified based on their direction and timing of peak sediment concentration, relative to streamflow, using records from 35&nbsp;U.S. Geological Survey stream gages in the period between 2007 and 2023 within two different physiographic regions: the Mid-Atlantic Delaware River Basin (DRB) and the Midwestern Illinois River Basin (IRB). The DRB contains mixed forest, urban, suburban and agricultural watersheds over diverse topography, and the IRB is primarily an intensively managed agricultural watershed on flat terrain. We use principal component analysis and linear discriminant analysis to infer regional hydrologic relations with turbidity dynamics, and to identify the primary hydrologic and land surface characteristics most effective at distinguishing between hysteretic classes in each region. These analyses reveal underlying regional relations in storm event hydrodynamics and landscape characteristics that contribute to varying patterns in sediment dynamics. Incorporating these sediment dynamic relations with spatial distributions and hydrologic timing of sediment sources could help to improve process understanding and predictive capability of fine sediment transport in watersheds.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.70176","usgsCitation":"Cho, J., Lund, J.W., Ball, G., Brown, J., Gellis, A.C., Gurley, L., Hamshaw, S.D., Kwang, J., Laws, A.R., Noe, G.E., Oelsner, G.P., Parchaso, F., Peterman-Phipps, C.L., Skalak, K., and Sutfin, N., 2025, Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis: Earth Surface Processes and Landforms, v. 50, no. 15, e70176, 17 p., https://doi.org/10.1002/esp.70176.","productDescription":"e70176, 17 p.","ipdsId":"IP-170744","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":497386,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.70176","text":"Publisher Index Page"},{"id":497134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Illinois, Indiana, New Jersey, New York, Pennsylvania, Wisconsin","otherGeospatial":"Delaware River basin, Illinois River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.68954408345827,\n              38.950028597513835\n            ],\n            [\n              -74.89989316012007,\n              39.102240996914645\n            ],\n            [\n              -74.6338466936656,\n              39.87992689710077\n            ],\n            [\n              -74.54209298691838,\n              42.48383357009601\n            ],\n            [\n              -75.32901972577082,\n              42.66606930681047\n            ],\n            [\n              -75.68467393558525,\n              41.52390339255501\n            ],\n            [\n              -75.94651156666464,\n              40.974819350541964\n            ],\n            [\n              -75.68954408345827,\n              38.950028597513835\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.28425444320338,\n              40.20557521013771\n            ],\n            [\n              -85.90911218453002,\n              41.38513214136876\n            ],\n            [\n              -85.85862424909708,\n              41.667539228044404\n            ],\n            [\n              -86.89276221760612,\n              41.62541848585033\n            ],\n            [\n              -87.491709790281,\n              41.28303800296328\n            ],\n            [\n              -87.72477917112869,\n              41.742290318896494\n            ],\n            [\n              -87.899547984402,\n              42.784080379148435\n            ],\n            [\n              -88.60462403328552,\n              42.60113489689337\n            ],\n            [\n              -88.63226716784871,\n              41.75576859115819\n            ],\n            [\n              -91.24345346002825,\n              40.535056911723274\n            ],\n            [\n              -91.45289956006285,\n              39.49144562335394\n            ],\n            [\n              -89.96846822396331,\n              39.00606367341052\n            ],\n            [\n              -87.23317921294202,\n              40.09312885971303\n            ],\n            [\n              -87.28425444320338,\n              40.20557521013771\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"50","issue":"15","noUsgsAuthors":false,"publicationDate":"2025-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":951405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":211157,"corporation":false,"usgs":true,"family":"Lund","given":"J.","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Grady 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":220746,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Jeb E. 0000-0001-7671-2379","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":225088,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gurley, Laura N. 0000-0002-2881-1038","orcid":"https://orcid.org/0000-0002-2881-1038","contributorId":93834,"corporation":false,"usgs":true,"family":"Gurley","given":"Laura N.","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hamshaw, Scott Douglas 0000-0002-0583-4237","orcid":"https://orcid.org/0000-0002-0583-4237","contributorId":305601,"corporation":false,"usgs":true,"family":"Hamshaw","given":"Scott","email":"","middleInitial":"Douglas","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":951410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kwang, Jeffrey Stephen 0000-0002-3165-9700","orcid":"https://orcid.org/0000-0002-3165-9700","contributorId":348190,"corporation":false,"usgs":true,"family":"Kwang","given":"Jeffrey Stephen","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":951411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laws, Andrew Roy 0009-0001-6928-8335","orcid":"https://orcid.org/0009-0001-6928-8335","contributorId":363272,"corporation":false,"usgs":true,"family":"Laws","given":"Andrew","middleInitial":"Roy","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"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 - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":951414,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Oelsner, Gretchen P. 0000-0001-9329-7357 goelsner@usgs.gov","orcid":"https://orcid.org/0000-0001-9329-7357","contributorId":4440,"corporation":false,"usgs":true,"family":"Oelsner","given":"Gretchen","email":"goelsner@usgs.gov","middleInitial":"P.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951415,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":217719,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":951416,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":951417,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":951418,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sutfin, Nicholas Alan 0000-0003-4429-7814","orcid":"https://orcid.org/0000-0003-4429-7814","contributorId":357883,"corporation":false,"usgs":true,"family":"Sutfin","given":"Nicholas Alan","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951419,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70273803,"text":"70273803 - 2025 - Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","interactions":[],"lastModifiedDate":"2026-02-02T21:34:17.940337","indexId":"70273803","displayToPublicDate":"2025-11-27T15:29:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","docAbstract":"Savannas depend on frequent, low-intensity fires that shape animal and plant communities. These fires alter animal populations, movement, and habitat use. Here, we report on how fires in a longleaf pine (Pinus palustris) savanna affected small mammal microhabitat use via changes in competition and predation. We monitored small mammal populations and vegetation subjected to biennial prescribed fires and compared microhabitat use of three small mammal populations [hispid cotton rats (Sigmodon hispidus), cotton mice (Peromyscus gossypinus) and oldfield mice (Peromyscus polionotus)] in the presence and absence of mesocarnivores while accounting for changes in density and movement of each small mammal species. Densities of cotton rats varied greatly across years but were similar between predator exclosures and controls. However, frequency of use was greater in exclosures than in controls irrespective of vegetation characteristics, suggesting predation risk altered cotton rat microhabitat use. Conversely, higher relative abundance of cotton rats was associated with lower cotton mouse and oldfield mouse use, suggesting spatial separation in niche and indicating that cotton mice expand their realized niche following predation-induced declines of cotton rats associated with prescribed burn events. Our results contribute to a better understanding of pyrodiversity and how interspecific interactions can moderate effects of vegetation changes following prescribed fires.","language":"English","publisher":"Springer","doi":"10.1038/s41598-025-26529-5","usgsCitation":"Shastry, V., Conner, L.M., Morris, G., Royle, A., Smith, L., and Morin, D., 2025, Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires: Scientific Reports, v. 15, no. 1, 42385, 12 p., https://doi.org/10.1038/s41598-025-26529-5.","productDescription":"42385, 12 p.","ipdsId":"IP-181552","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499616,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-26529-5","text":"Publisher Index Page"},{"id":499417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Baker County","otherGeospatial":"Jones Center at Ichauway","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shastry, Varsha","contributorId":365822,"corporation":false,"usgs":false,"family":"Shastry","given":"Varsha","affiliations":[{"id":87229,"text":"Mississippi State University; The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conner, L. Mike","contributorId":365823,"corporation":false,"usgs":false,"family":"Conner","given":"L.","middleInitial":"Mike","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Gail","contributorId":365824,"corporation":false,"usgs":false,"family":"Morris","given":"Gail","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lora","contributorId":156438,"corporation":false,"usgs":false,"family":"Smith","given":"Lora","affiliations":[],"preferred":false,"id":954880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morin, Dana","contributorId":264602,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":954881,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70272640,"text":"70272640 - 2025 - Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","interactions":[],"lastModifiedDate":"2025-12-02T16:25:40.80763","indexId":"70272640","displayToPublicDate":"2025-11-26T10:21:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","docAbstract":"<ol class=\"\"><li>Although nitrogen and phosphorus deficiency of algal blooms have been the focus of substantial attention, organic nutrients can limit algal growth in aquatic systems. Growing evidence indicates thiamine (vitamin B<sub>1</sub>) can influence the community of primary producers in marine systems, but comparatively little is known about the effect of thiamine on freshwater algal productivity.</li><li>We conducted 106 nutrient deficiency experiments with water from 39 Ohio lakes of varying trophic status during the growing seasons (April–October) of 2008–2009. Specifically, we tested the response of phytoplankton biomass (as chlorophyll<span>&nbsp;</span><i>a</i>, chl-<i>a</i>) relative to controls to added nitrogen (N), phosphorus (P), thiamine (Th), or combinations of N + P and N + P + Th. Next, we compared the chl-<i>a</i><span>&nbsp;</span>growth response of treatment/control to published thresholds based on frequentist approaches and compared the conclusions with Bayesian model results that focused on probability of a response.</li><li>Although N + P addition was consistently associated with the largest chl-<i>a</i><span>&nbsp;</span>response, we found evidence of a thiamine influence on phytoplankton growth in some experiments. The Bayesian approach suggested thiamine may become more limiting as the growing season progresses. By late in the growing season, there was an 85% probability of a positive algal growth response to thiamine addition.</li><li>Understanding the role of thiamine or other overlooked nutrients is not likely to alter the prevailing understanding of nutrient deficiency in freshwater ecosystems. However, we present evidence that freshwater phytoplankton may experience thiamine deficiency and suggest limnologists consider thiamine when exploring resource deficiencies.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.70134","usgsCitation":"Rowland, F.E., Vanni, M.J., Hayes, N.M., and Kraft, C.E., 2025, Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes: Freshwater Biology, v. 70, no. 11, e70134, 9 p., https://doi.org/10.1111/fwb.70134.","productDescription":"e70134, 9 p.","ipdsId":"IP-164621","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":496991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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M.","contributorId":363082,"corporation":false,"usgs":false,"family":"Hayes","given":"Nicole","middleInitial":"M.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":951087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraft, Clifford E.","contributorId":363084,"corporation":false,"usgs":false,"family":"Kraft","given":"Clifford","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":951088,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272651,"text":"70272651 - 2025 - Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA","interactions":[],"lastModifiedDate":"2026-01-05T16:59:46.320524","indexId":"70272651","displayToPublicDate":"2025-11-26T09:23:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA","docAbstract":"<p>The depth level at which porphyry Cu–forming magmas fractionated and exsolved mineralizing fluids is actively debated. In the classic model, extensive magma fractionation occurs in large, upper crustal magma chambers, and concomitant fluid exsolution leads to forceful expulsion of residual magmas in the form of porphyry dikes, stocks, and breccia pipes, which subsequently serve as pathways for the mineralizing fluids. In contrast, some recent studies highlighting the role of deep crustal magma fractionation in the production of fertile magmas essentially deny the existence of upper crustal magma chambers at the time of mineralization. To address this, we conducted a detailed thermobarometric investigation of 13 intermediate to felsic, porphyritic intrusive rocks related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, United States, representing two premineralization magmas (61–60 Ma), seven synmineralization magmas (60–58 Ma), and four late- to postmineralization magmas (58–57 Ma).</p><p>For each sample, the pressure of last magma crystallization before final magma ascent to the current exposure level was reconstructed based on Al-in-hornblende barometry of small hornblende inclusions trapped within quartz phenocrysts and through titanium-in-quartz (TitaniQ) thermobarometry of the host quartz phenocrysts themselves. Since quartz is one of the last crystallizing magmatic minerals, and no significant phenocryst growth could have occurred in small dikes and stocks after final magma emplacement, quartz phenocrysts and their contained hornblende inclusions record the depth of last magma crystallization before final magma ascent. When present, hornblende phenocrysts and hornblende inclusions within other major phenocrysts were also analyzed. Both quartz and hornblende barometers return consistent average pressures of 3.2 ± 0.4 kbar for the entire suite of pre- to postmineralization magmas, corresponding to depths of 11 to 14&nbsp;km. The synmineralization magmas return even more consistent average pressures of 3.1 ± 0.2 kbar, corresponding to a depth of 12 ± 1&nbsp;km.</p><p>The volume of the mineralizing porphyry dikes and stocks at the emplacement level is far too small to have provided all the fluids and metals required to form the observed ore deposits. Therefore, the majority of the ore-forming fluids must have originated from the magmas that crystallized at 12 ± 1&nbsp;km depth. The ore deposits, conversely, formed at ~5-km paleodepth. This implies that most of the mineralizing fluids traveled an average vertical distance of ~7&nbsp;km from their magmatic source to the eventual site of ore precipitation. The relatively unaltered nature and low veining degree of deeper parts of mineralized porphyry dikes and stocks suggest that the fluid transport through these intrusive bodies occurred mostly at near-solidus conditions by means of fluid percolation along grain boundaries.</p><p>In summary, our results suggest that (1) a large, upper crustal pluton exists ~7 km beneath the Santa Rita and Hanover-Fierro deposits; (2) abundant phenocryst crystallization occurred at this depth level; and (3) this pluton was the main source for the exsolution of ore-forming fluids. However, the investigated rocks have elevated whole-rock Sr/Y ratios, indicating magma fractionation at deep crustal levels. As a result, our preferred model is a combination of the two end-member models introduced above, with most magma fractionation having occurred in the deep crust and with residual, intermediate to felsic melts having ascended and accumulated at 11 to 14 km paleodepth, where they continued to crystallize with comparatively little crystal-liquid separation, before some of these magmas ascended further to shallow levels and quenched to porphyries.</p>","language":"English","publisher":"Society of Economic Geology","doi":"10.5382/econgeo.5197","usgsCitation":"Audétat, A., Chang, J., and Gaynor, S.P., 2025, Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA: Economic Geology, v. 120, no. 7, p. 1679-1699, https://doi.org/10.5382/econgeo.5197.","productDescription":"21 p.","startPage":"1679","endPage":"1699","ipdsId":"IP-174016","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Hanover-Fierro deposit, Santa Rita mine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108,\n              32.875\n            ],\n            [\n              -108.1667,\n              32.875\n            ],\n            [\n              -108.1667,\n              32.75\n            ],\n            [\n              -108,\n              32.75\n            ],\n            [\n              -108,\n              32.875\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Audétat, Andreas","contributorId":363151,"corporation":false,"usgs":false,"family":"Audétat","given":"Andreas","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Jia","contributorId":363152,"corporation":false,"usgs":false,"family":"Chang","given":"Jia","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaynor, Sean Patrick 0000-0002-8353-511X","orcid":"https://orcid.org/0000-0002-8353-511X","contributorId":346264,"corporation":false,"usgs":true,"family":"Gaynor","given":"Sean","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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