{"pageNumber":"37","pageRowStart":"900","pageSize":"25","recordCount":40778,"records":[{"id":70266844,"text":"70266844 - 2025 - Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands","interactions":[],"lastModifiedDate":"2025-05-13T15:09:17.143776","indexId":"70266844","displayToPublicDate":"2025-03-26T07:59:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands","docAbstract":"<p>1. Decomposition controls the release of carbon and nutrients from decaying plant litter into soils or the atmosphere. In most biomes decomposition rates can be accurately predicted with simple mathematical models, but these models have long under-predicted decomposition in globally- extensive drylands. </p><p>2. We posit that the exposed surface conditions characteristic of drylands makes litter decomposition uniquely subject to microsite-specific environmental controls and spatially-variable microbial communities. As such, decomposition in dryland ecosystems – which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability – is a prime example of a macrosystems process that can be addressed by merging field data with new predictive models operating across a hierarchical continuum of spatial scales and process resolutions. </p><p>3. A macrosystems approach offers promise to reconcile model-measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g., shrub sub-canopy or intercanopy) to regions (e.g., across a 100s of km2 study site with complex topography, precipitation, and temperature) and ultimately to a continental perspective (e.g., North American drylands). </p><p>4. Recent developments in technology and data availability position the scientific community to integrate lab, field, modeling, and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro-to-macroscale. This multi-scale approach promises a path forward to resolving a longstanding disconnect between measured and modeled data in dryland litter decomposition. </p><p>5. Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach. </p><p>6. We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems.</p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.70029","usgsCitation":"Throop, H.L., Li, J., Moorhead, D., Reed, S., Todd-Brown, K., Besser, A., Bloom, D., Ingalls, T., and Cueva, A., 2025, Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands: Functional Ecology, 11 p., https://doi.org/10.1111/1365-2435.70029.","productDescription":"11 p.","ipdsId":"IP-176124","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488192,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.70029","text":"Publisher Index Page"},{"id":485815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":936890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Jiwei","contributorId":355122,"corporation":false,"usgs":false,"family":"Li","given":"Jiwei","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moorhead, Daryl L.","contributorId":355123,"corporation":false,"usgs":false,"family":"Moorhead","given":"Daryl L.","affiliations":[{"id":84710,"text":"Toledo University, Biology Department, Toledo, OH USA","active":true,"usgs":false}],"preferred":false,"id":936892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":936893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Todd-Brown, Katherine","contributorId":197914,"corporation":false,"usgs":false,"family":"Todd-Brown","given":"Katherine","affiliations":[],"preferred":false,"id":936894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Besser, Alexi","contributorId":355124,"corporation":false,"usgs":false,"family":"Besser","given":"Alexi","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bloom, Dellena","contributorId":355125,"corporation":false,"usgs":false,"family":"Bloom","given":"Dellena","affiliations":[{"id":84713,"text":"University of Florida, Engineering School of Sustainable Infrastructure and Environment, Gainesville, FL USA","active":true,"usgs":false}],"preferred":false,"id":936896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ingalls, Thomas","contributorId":355126,"corporation":false,"usgs":false,"family":"Ingalls","given":"Thomas","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cueva, Alejandro","contributorId":355127,"corporation":false,"usgs":false,"family":"Cueva","given":"Alejandro","affiliations":[{"id":84714,"text":"El Colegio de la Frontera Sur, Departemento de Ecosistema Ecologico, San Cristobal, Mexico","active":true,"usgs":false}],"preferred":false,"id":936898,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70264861,"text":"70264861 - 2025 - Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction","interactions":[],"lastModifiedDate":"2025-05-28T14:53:12.678207","indexId":"70264861","displayToPublicDate":"2025-03-25T10:05:14","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction","docAbstract":"<p><span>The Sangre de Cristo Range in southern Colorado exposes some of the deepest Cenozoic structural levels in the Rocky Mountain region, including mylonitic shear zones associated with both the Laramide orogeny and Rio Grande rift. We investigated the relation between Laramide contraction and Rio Grande rift extension with detailed geologic mapping, kinematic analysis, and geochronometry in a 50 km</span><sup>2</sup><span>&nbsp;area centered on the Independence Mine shear zone (IMSZ). The 15−100-m-thick IMSZ is one of several shallowly to moderately (∼45° ± 20°) W-SW−dipping brittle-plastic shear zones along the western flank of the range. These shear zones display microstructural evidence of initiation as top-NE contractional mylonite zones, consistent with regional Laramide kinematics, which have been pervasively overprinted by shear fabrics indicating top-SW extensional reactivation. Both top-NE and top-SW shear fabrics involve cataclasis and quartz dislocation creep, although top-SW shear is more commonly localized along phyllosilicate-lined shear bands. Shear zones are hosted predominately within Proterozoic gneiss, and contain abundant chlorite and white mica derived from alteration of hornblende and feldspar, which indicates that weakening driven by fluid reactions played an important role in localizing strain. Extensional overprinting appears to be most pervasive along more steeply dipping portions of shear zones and where secondary phyllosilicates form an interconnected weak phase, which suggests that reactivation was primarily controlled by geometry and rheological contrasts inherited from contraction. One top-SW shear zone adjacent to the IMSZ cuts a late Oligocene gabbro stock, and monazite grains synkinematic with top-SW shear in the IMSZ yielded late Oligocene to Early Miocene U-Th-Pb dates that correspond with initiation of the Rio Grande rift. Reactivation of weak reverse faults may represent an important structural control during initial extension in the middle crust, prior to slip along the high-angle Sangre de Cristo normal fault system.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02772.1","usgsCitation":"Sitar, M., Singleton, J.S., Rahl, J., Caine, J., King, J., Kylander-Clark, A.R., and O’Sullivan, P., 2025, Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction: Geosphere, v. 21, no. 3, p. 446-469, https://doi.org/10.1130/GES02772.1.","productDescription":"24 p.","startPage":"446","endPage":"469","ipdsId":"IP-163394","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488514,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02772.1","text":"Publisher Index Page"},{"id":483877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Sangre de Christo Range","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.75,\n              38.125\n            ],\n            [\n              -105.75,\n              37.5\n            ],\n            [\n              -105.25,\n              37.5\n            ],\n            [\n              -105.25,\n              38.125\n            ],\n            [\n              -105.75,\n              38.125\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Sitar, Michael C. 0000-0003-0688-1067","orcid":"https://orcid.org/0000-0003-0688-1067","contributorId":352709,"corporation":false,"usgs":false,"family":"Sitar","given":"Michael C.","affiliations":[{"id":48080,"text":"Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":932081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singleton, John S. 0000-0001-9399-7732","orcid":"https://orcid.org/0000-0001-9399-7732","contributorId":306242,"corporation":false,"usgs":false,"family":"Singleton","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":932082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rahl, Jeffrey M. 0000-0002-9195-8294","orcid":"https://orcid.org/0000-0002-9195-8294","contributorId":352710,"corporation":false,"usgs":false,"family":"Rahl","given":"Jeffrey M.","affiliations":[{"id":37754,"text":"Washington and Lee University, Lexington, VA","active":true,"usgs":false}],"preferred":false,"id":932083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":932084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Jacob","contributorId":352711,"corporation":false,"usgs":false,"family":"King","given":"Jacob","affiliations":[{"id":48080,"text":"Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":932085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kylander-Clark, Andrew R C","contributorId":269776,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","email":"","middleInitial":"R C","affiliations":[{"id":27356,"text":"UC-Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Sullivan, Paul","contributorId":352712,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","affiliations":[{"id":84291,"text":"GeoSep Services, Moscow, ID","active":true,"usgs":false}],"preferred":false,"id":932087,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70268343,"text":"70268343 - 2025 - C4 photosynthesis, trait spectra, and the fast-efficient phenotype","interactions":[],"lastModifiedDate":"2025-06-23T14:52:23.53561","indexId":"70268343","displayToPublicDate":"2025-03-25T09:49:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"C<sub>4</sub> photosynthesis, trait spectra, and the fast-efficient phenotype","title":"C4 photosynthesis, trait spectra, and the fast-efficient phenotype","docAbstract":"<p><span>It has been 60 years since the discovery of C</span><sub>4</sub><span>&nbsp;photosynthesis, an event that rewrote our understanding of plant adaptation, ecosystem responses to global change, and global food security. Despite six decades of research, one aspect of C</span><sub>4</sub><span>&nbsp;photosynthesis that remains poorly understood is how the pathway fits into the broader context of adaptive trait spectra, which form our modern view of functional trait ecology. The C</span><sub>4</sub><span>&nbsp;CO</span><sub>2</sub><span>-concentrating mechanism supports a general C</span><sub>4</sub><span>&nbsp;plant phenotype capable of fast growth and high resource-use efficiencies. The fast-efficient C</span><sub>4</sub><span>&nbsp;phenotype has the potential to operate at high productivity rates, while allowing for less biomass allocation to root production and nutrient acquisition, thereby providing opportunities for the evolution of novel trait covariances and the exploitation of new ecological niches. We propose the placement of the C</span><sub>4</sub><span>&nbsp;fast-efficient phenotype near the acquisitive pole of the world-wide leaf economic spectrum, but with a pathway-specific span of trait space, wherein selection shapes both acquisitive and conservative adaptive strategies. A trait-based perspective of C</span><sub>4</sub><span>&nbsp;photosynthesis will open new paths to crop improvement, global biogeochemical modeling, the management of invasive species, and the restoration of disturbed ecosystems, particularly in grasslands.</span></p>","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.70057","usgsCitation":"Monson, R., Li, S., Ainsworth, E.A., Fan, Y., Hodge, J., Knapp, A.K., Leakey, A., Lombardozzi, D., Reed, S., Sage, R.F., Smith, M.D., Smith, N.G., Still, C.J., and Way, D.A., 2025, C4 photosynthesis, trait spectra, and the fast-efficient phenotype: New Phytologist, v. 246, no. 3, p. 879-893, https://doi.org/10.1111/nph.70057.","productDescription":"15 p.","startPage":"879","endPage":"893","ipdsId":"IP-175808","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.70057","text":"Publisher Index Page"},{"id":491104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"246","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Monson, Russell K.","contributorId":357242,"corporation":false,"usgs":false,"family":"Monson","given":"Russell K.","affiliations":[{"id":85357,"text":"Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado 80309, USA","active":true,"usgs":false}],"preferred":false,"id":940873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Shuai","contributorId":357243,"corporation":false,"usgs":false,"family":"Li","given":"Shuai","affiliations":[{"id":85358,"text":"Guangdong Provincial Key Lab. of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China; Carl R. Woese Institute for Genomic Biology, Uni of Illinois at Urbana-Champaign, Urbana, Illinois, USA","active":true,"usgs":false}],"preferred":false,"id":940874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ainsworth, Elizabeth A.","contributorId":266079,"corporation":false,"usgs":false,"family":"Ainsworth","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":54883,"text":"USDA ARS GCPRU, 1201 W. Gregory Drive, Urbana, IL 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fan, Yuzhen","contributorId":357244,"corporation":false,"usgs":false,"family":"Fan","given":"Yuzhen","affiliations":[{"id":85359,"text":"Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia","active":true,"usgs":false}],"preferred":false,"id":940876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodge, John G.","contributorId":357245,"corporation":false,"usgs":false,"family":"Hodge","given":"John G.","affiliations":[{"id":85360,"text":"Center for Advanced Bioenergy and Bioproducts Innovation, Urbana, Illinois, 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knapp, Alan K.","contributorId":223624,"corporation":false,"usgs":false,"family":"Knapp","given":"Alan","email":"","middleInitial":"K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leakey, Andrew D.B.","contributorId":266112,"corporation":false,"usgs":false,"family":"Leakey","given":"Andrew D.B.","affiliations":[{"id":54910,"text":"Departments of Plant Biology and Crop Sciences, University of Illinois at Urbana-Champaign, 1206 W Gregory Dr, Urbana, IL 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940879,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lombardozzi, Danica","contributorId":357246,"corporation":false,"usgs":false,"family":"Lombardozzi","given":"Danica","affiliations":[{"id":85361,"text":"Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80521 USA","active":true,"usgs":false}],"preferred":false,"id":940880,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":940881,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sage, Rowan F.","contributorId":296142,"corporation":false,"usgs":false,"family":"Sage","given":"Rowan","email":"","middleInitial":"F.","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":940882,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smith, Melinda D.","contributorId":223621,"corporation":false,"usgs":false,"family":"Smith","given":"Melinda","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940883,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Nicholas G.","contributorId":266125,"corporation":false,"usgs":false,"family":"Smith","given":"Nicholas","email":"","middleInitial":"G.","affiliations":[{"id":54920,"text":"Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA","active":true,"usgs":false}],"preferred":false,"id":940884,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Still, Christopher J.","contributorId":167581,"corporation":false,"usgs":false,"family":"Still","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":24761,"text":"University of California, Santa Barbara; Oregon State University","active":true,"usgs":false}],"preferred":false,"id":940885,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Way, Danielle A.","contributorId":199465,"corporation":false,"usgs":false,"family":"Way","given":"Danielle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":940886,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70265266,"text":"70265266 - 2025 - No magmatic driving force for Europan sea-floor volcanism","interactions":[],"lastModifiedDate":"2025-05-28T14:55:26.641908","indexId":"70265266","displayToPublicDate":"2025-03-24T15:17:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6448,"text":"Nature Astronomy","active":true,"publicationSubtype":{"id":10}},"title":"No magmatic driving force for Europan sea-floor volcanism","docAbstract":"The internal ocean of Jupiter’s moon Europa is thought to be a prime candidate for hosting extraterrestrial life. Europa’s silicate interior may contribute to habitability via the generation of reactants through hydrothermal activity, serpentinization, or other geological processes occurring on or just below Europa’s seafloor. However, silicate melting is thought to occur at >100 km depth in Europa’s mantle and it is unknown if this magma is able to penetrate and travel through the moon’s likely thick, brittle lithosphere to erupt at the seafloor. Here we combine previous modeling approaches to Europan interior melt generation and lithospheric dyke transport to show that Europan seafloor volcanism is strongly inhibited by its lithosphere. The low stress state of the Europan interior hinders the ability of dykes to penetrate through the lithosphere. Should dykes form, they penetrate <5% of the 200–250 km-thick lithosphere. Low mantle melt fractions (3–5%) drive sluggish pore-space magma flow, leading to dyke influxes 10,000 times lower than that necessary for seafloor eruption. These results strongly suggest that models of Europan habitability reliant on present-day volcanism at its seafloor are implausible.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41550-025-02508-8","usgsCitation":"Green, A., Elder, C., Bland, M., Tackley, P., and Byrne, P., 2025, No magmatic driving force for Europan sea-floor volcanism: Nature Astronomy, v. 9, p. 640-649, https://doi.org/10.1038/s41550-025-02508-8.","productDescription":"10 p.","startPage":"640","endPage":"649","ipdsId":"IP-163125","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":484178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europa","volume":"9","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, A.P.","contributorId":352969,"corporation":false,"usgs":false,"family":"Green","given":"A.P.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":331017,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Michael Thomas 0000-0001-5543-1519","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":352963,"corporation":false,"usgs":true,"family":"Bland","given":"Michael Thomas","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":932628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tackley, Paul","contributorId":352966,"corporation":false,"usgs":false,"family":"Tackley","given":"Paul","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":932629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Byrne, Paul K.","contributorId":237950,"corporation":false,"usgs":false,"family":"Byrne","given":"Paul K.","affiliations":[{"id":47656,"text":"Planetary Research Group, Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":932630,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70265967,"text":"70265967 - 2025 - Assessing earthquake risks to lifeline infrastructure systems in the United States","interactions":[],"lastModifiedDate":"2025-04-22T16:01:31.164657","indexId":"70265967","displayToPublicDate":"2025-03-24T10:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21204,"text":"International Journal of Critical Infrastructure Protection","active":true,"publicationSubtype":{"id":10}},"title":"Assessing earthquake risks to lifeline infrastructure systems in the United States","docAbstract":"<p><span>The security and economic stability of the United States rely heavily on robust lifeline infrastructure systems and yet the risks to such systems are seldom quantified at the national scale. For example, while earthquake risks to buildings in the United States have been investigated at the national scale regularly, such risks to gas pipelines have rarely been investigated nationally. In this paper, we use examples from two critical infrastructure sectors to demonstrate (1) the nature of earthquake risks to lifeline infrastructure systems, (2) complexities involved in regional seismic risk assessments, and (3) how such risks change with time. We found that bridge risks can be underestimated by at least 64 % when viewed from repair costs instead of traffic demands and that regional risks can be underestimated by 19 % when spatial correlations of ground motion are ignored. Further, exceedance of traffic demand can be 50 times more likely to occur when viewed at the regional scale than when viewed at an individual bridge. Similarly, exceedance of repairs can be 180 times more likely to occur when viewed at the pipeline network level than at a segment-specific level. Finally, sensitivity analyses with the 2018 and 2023 USGS National Seismic Hazard Models indicate an increase in bridge risk of at least 24 % and an increase in exposed gas pipeline mileage of 43 %. The evolution of risks, complexities involved in assessments, and limited resources jointly underscore the need for more routine updates to nationwide seismic risk assessments of lifeline systems in the United States.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijcip.2025.100758","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2025, Assessing earthquake risks to lifeline infrastructure systems in the United States: International Journal of Critical Infrastructure Protection, v. 49, 100758, https://doi.org/10.1016/j.ijcip.2025.100758.","productDescription":"100758","ipdsId":"IP-170667","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":484841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934186,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70266111,"text":"70266111 - 2025 - The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","interactions":[],"lastModifiedDate":"2025-04-25T15:31:50.116638","indexId":"70266111","displayToPublicDate":"2025-03-24T10:29:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21214,"text":"Peer Community Journal","active":true,"publicationSubtype":{"id":10}},"title":"The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","docAbstract":"<p><span>Survival is a key life history parameter that can inform management decisions and basic life history research. Because true survival is often confounded with emigration from the study area, many studies are forced to estimate apparent survival (i.e., probability of surviving and remaining inside the study area), which can be much lower than true survival for highly mobile species.&nbsp; One method for estimating true survival is the Barker joint live-recapture/live-resight (JLRLR) model, which combines capture data from a study area (hereafter the ‘capture site’) with resighting data from a broader geographic area. This model assumes that live resights occur throughout the entire area where animals can disperse to and this assumption is often not met in practice. Here we use simulation to evaluate survival bias from a JLRLR model under study design scenarios that differ in the site selection for resights: global, random, fixed including the capture site, and fixed excluding the capture site. Simulation results indicate that fixed designs that included the capture site showed negative survival bias, whereas fixed designs that excluded the capture site exhibited positive survival bias. The magnitude of the bias was dependent on movement and survival, where scenarios with high survival and frequent movement had minimal bias. In an effort to help minimize bias, we developed a multistate version of the JLRLR and demonstrated reductions in survival bias compared to the single-state version for most designs. Our results suggest minimizing bias can be accomplished by: 1) using a random resight design when feasible if global sampling is not possible, 2) using the multistate JLRLR model when appropriate, 3) including the capture site in the resight sampling frame when possible, and 4) reporting survival as apparent survival if fixed sites are used for resight with the single state JLRLR model.</span></p>","language":"English","publisher":"PeerJ","doi":"10.24072/pcjournal.533","usgsCitation":"Dzul, M.C., Yackulic, C., and Kendall, W.L., 2025, The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models: Peer Community Journal, v. 5, e34, 24 p., https://doi.org/10.24072/pcjournal.533.","productDescription":"e34, 24 p.","ipdsId":"IP-158705","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":487775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24072/pcjournal.533","text":"Publisher Index Page"},{"id":485061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":934620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265015,"text":"70265015 - 2025 - Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","interactions":[],"lastModifiedDate":"2025-04-28T15:14:09.946352","indexId":"70265015","displayToPublicDate":"2025-03-24T09:11:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Bayesian calibration of the <sup>40</sup>K decay scheme with implications for <sup>40</sup>K-based geochronology","title":"Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","docAbstract":"<p><span>The K/Ar and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar geochronometers are based on the naturally occurring radionuclide&nbsp;</span><sup>40</sup><span>K. Their precision and accuracy are limited by uncertainties on the&nbsp;</span><sup>40</sup><span>K decay constants and, in the case of the&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar geochronometer, the isotopic composition of neutron fluence monitors. To address these limitations, we introduce a Bayesian calibration of the&nbsp;</span><sup>40</sup><span>K decay scheme. We formulate robust priors for all model parameters including partial&nbsp;</span><sup>40</sup><span>K decay constants,&nbsp;</span><sup>238</sup><span>U and&nbsp;</span><sup>235</sup><span>U decay constants, and age offset parameters to account for phenomena that can perturb apparent U-Pb and&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages. We then harness a set of complementary&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar,&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb, and&nbsp;</span><sup>235</sup><span>U/</span><sup>207</sup><span>Pb data from well- characterized geological samples with ages from 1.919 ka to 2000 Ma to derive Bayesian estimates of the&nbsp;</span><sup>40</sup><span>K decay constants. Posterior values for the partial&nbsp;</span><sup>40</sup><span>K decay constants are&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3B2;</mi></mrow><mo is=&quot;true&quot;>-</mo></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>β</sub>-</span></span></span><span>= (4.9252&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0054)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−10</sup><span>&nbsp;yr</span><sup>−1</sup><span>,&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3B2;</mi></mrow><mo is=&quot;true&quot;>+</mo></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>β</sub>+</span></span></span><span>&nbsp;= (5.6658&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.1543)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−15</sup><span>&nbsp;yr</span><sup>−1</sup><span>,&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msup is=&quot;true&quot;><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>EC</mi></mrow><mrow is=&quot;true&quot;><mo is=&quot;true&quot;>&amp;#x2217;</mo></mrow></msup></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>EC0</sub></span></span></span><span>&nbsp;= (5.7404&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-8-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0053)&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-9-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−11</sup><span>&nbsp;yr</span><sup>−1</sup><span>, and&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-10-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><msub is=&quot;true&quot;><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>EC</mi></mrow><mn is=&quot;true&quot;>0</mn></msub></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>EC0</sub></span></span></span><span>= (4.9060&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-11-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.2942)</span><span class=\"math\"><span id=\"MathJax-Element-12-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−13</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;(uncertainties reported at the 68 % (1&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-13-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi is=&quot;true&quot;>&amp;#x3C3;</mi></math>\"><span class=\"MJX_Assistive_MathML\">σ</span></span></span><span>) credible interval). These combine to a total&nbsp;</span><sup>40</sup><span>K decay constant&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-14-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub is=&quot;true&quot;><mi is=&quot;true&quot;>&amp;#x3BB;</mi><mrow is=&quot;true&quot;><mi mathvariant=&quot;italic&quot; is=&quot;true&quot;>tot</mi></mrow></msub></math>\"><span class=\"MJX_Assistive_MathML\">λ<sub>tot</sub></span></span></span><span>= (5.5042&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-15-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.0054)</span><span class=\"math\"><span id=\"MathJax-Element-16-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xD7;</mo></math>\"><span class=\"MJX_Assistive_MathML\">×</span></span></span><span>&nbsp;10</span><sup>−10</sup><span>&nbsp;yr</span><sup>−1</sup><span>. Model estimates of the&nbsp;</span><sup>238</sup><span>U and&nbsp;</span><sup>235</sup><span>U decay constants are statistically indistinguishable from those reported by&nbsp;</span><span class=\"anchor-text-container\"><span class=\"anchor-text\">Jaffey</span></span><span class=\"anchor-text-container\"><span class=\"anchor-text\"> et al. (1971)</span></span><span>. Posterior values of the&nbsp;</span><sup>40</sup><span>K decay constants and the&nbsp;</span><sup>40</sup><span>Ar*/</span><sup>40</sup><span>K isotopic composition of Fish Canyon sanidine (FCs) define a K/Ar FCs age of 28.183&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-17-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>&amp;#xB1;</mo></math>\"><span class=\"MJX_Assistive_MathML\">±</span></span></span><span>&nbsp;0.017 Ma (1&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-18-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi is=&quot;true&quot;>&amp;#x3C3;</mi></math>\"><span class=\"MJX_Assistive_MathML\">σ</span></span></span><span>). Significantly, Bayesian calibrated&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages align with astronomically tuned ages throughout the Cenozoic and with&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb and&nbsp;</span><sup>235</sup><span>U/</span><sup>207</sup><span>Pb ages in the Mesozoic, Paleozoic, and Proterozoic, as well as having comparable precision to the&nbsp;</span><sup>238</sup><span>U/</span><sup>206</sup><span>Pb method. Thus, Bayesian calibration of the 40 K decay scheme and the K/Ar age of FCs reconciles the&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar, U-Pb, and astronomical chronometers.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2025.03.024","usgsCitation":"Carter, J., Hasler, C., Fuentes, A., Tholt, A., Morgan, L.E., and Renne, P.R., 2025, Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology: Geochimica et Cosmochimica Acta, v. 397, p. 149-163, https://doi.org/10.1016/j.gca.2025.03.024.","productDescription":"14 p.","startPage":"149","endPage":"163","ipdsId":"IP-172690","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":483986,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"397","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Jack N.","contributorId":317971,"corporation":false,"usgs":false,"family":"Carter","given":"Jack N.","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hasler, Caroline","contributorId":352885,"corporation":false,"usgs":false,"family":"Hasler","given":"Caroline","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuentes, Anthony","contributorId":352886,"corporation":false,"usgs":false,"family":"Fuentes","given":"Anthony","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tholt, Andrew","contributorId":352887,"corporation":false,"usgs":false,"family":"Tholt","given":"Andrew","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":932303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":932304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Renne, Paul R. 0000-0003-1769-5235","orcid":"https://orcid.org/0000-0003-1769-5235","contributorId":229577,"corporation":false,"usgs":false,"family":"Renne","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":37390,"text":"Department of Earth and Planetary Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":932305,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264851,"text":"70264851 - 2025 - An enhanced national-scale urban tree canopy cover dataset for the United States","interactions":[],"lastModifiedDate":"2025-03-26T15:27:52.723666","indexId":"70264851","displayToPublicDate":"2025-03-24T08:13:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"An enhanced national-scale urban tree canopy cover dataset for the United States","docAbstract":"<p><span>Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R</span><sup>2</sup><span>) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R</span><sup>2</sup><span>&nbsp;of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-025-04816-0","usgsCitation":"Corro, L.M., Bagstad, K.J., Heris, M., Ibsen, P.C., Schleeweis, K., Diffendorfer, J., Troy, A., Megown, K., and O'Neil-Dunne, J., 2025, An enhanced national-scale urban tree canopy cover dataset for the United States: Scientific Data, v. 12, 490, 14 p., https://doi.org/10.1038/s41597-025-04816-0.","productDescription":"490, 14 p.","ipdsId":"IP-166001","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-025-04816-0","text":"Publisher Index Page"},{"id":483878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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,{"id":70265789,"text":"70265789 - 2025 - Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","interactions":[],"lastModifiedDate":"2025-04-16T14:26:35.866043","indexId":"70265789","displayToPublicDate":"2025-03-23T09:18:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp <i>Ctenopharyngodon idella</i> in the Sandusky River","title":"Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","docAbstract":"<p><span>Natural resources management is often concerned with conserving rare-native or controlling rare-invasive fishes. Informing and assessing conservation and control efforts frequently requires information from captures. When little is understood about spatial and temporal fish distributions, captures can be infrequent and costly. If successful management depends on effective management response, optimizing for efficiency may be the difference between success and failure. We compared per vessel hour capture efficiencies for invasive grass carp (</span><i>Ctenopharyngodon idella</i><span>) between two methods: electrofishing-only (electrofishing) and in combination with a trammel net (combination). Capture and effort information including 174 captures from 1853 capture attempts from 1706 total hours of effort in the Sandusky River, OH, USA from 2020–2023 was used to fit a generalized linear model. Captures were allowed to vary by river kilometer, month, and year to account for unequal capture rates and effort. Captures were offset by total vessel hours or the count of independent efforts to compare methods that prioritize detection at a single location (e.g., combination) to methods that prioritize exploiting more locations (e.g., electrofishing). Including trammel nets was intended to increase single site detection, but we found that electrofishing-only was at least 2.4x more efficient (catch per vessel hour) than when combined with a trammel net with no significant difference in catch per removal effort. Complex methods intended to increase single site detection may reduce the number of efforts completed. Therefore, overall capture efficiency and total capture numbers for rare fish may be increased through methods that prioritize per-hour efficiency.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107344","usgsCitation":"Hunter, R., Qian, S.S., Fischer, J., Brown, R., Nathan, L., Dettmers, J., Roberts, J., Hilling, C.D., Acre, M.R., Mapes, R., Young, R., and Mayer, C.M., 2025, Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River: Fisheries Research, v. 285, 107344, 10 p., https://doi.org/10.1016/j.fishres.2025.107344.","productDescription":"107344, 10 p.","ipdsId":"IP-170360","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science 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,{"id":70269982,"text":"70269982 - 2025 - Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes","interactions":[],"lastModifiedDate":"2025-08-07T15:54:16.040989","indexId":"70269982","displayToPublicDate":"2025-03-22T10:47:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes","docAbstract":"<p><span>Biological invasions driven by international trade heighten the urgency for development of invasion risk models, as the traits and parameters that consistently predict successful invasion remain unresolved. For four regions of North America that include parts of the United States and Canada (Sacramento-San Joaquin River Basins, Lower Colorado River Basin, Great Lakes Region, Mid-Atlantic Region), we construct and compare classification tree models to reveal robust predictors for the establishment and ecological impact stages of freshwater fish invasion. We subsequently apply the models to identify invasive fish species in trade and conduct pathway analyses to determine which trades (aquarium, biological supply, live bait, live food, water garden) and source continents pose the greatest risk to each region. Model results differed by invasion stage and region. Across regions, establishment models shared climate-related predictors including climate match and temperature tolerance. Three of the four impact models contained prior establishment success. The greatest number of species (548) were predicted to establish in the Sacramento-San Joaquin while the fewest (5) were predicted to establish in the Mid-Atlantic. Forty species were predicted to establish in multiple regions, five of which were also predicted to have high impact. The aquarium trade and Asia supplied the most species predicted to establish. Taken together, the results highlight region-specific models, indicating no universal model predicts invasion. Climate-related and prior establishment variables were most useful to risk assessments. The regional models, and identified high-risk pathways and potential invaders, could be applied to prevent future fish invasions in North America.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-025-03560-1","usgsCitation":"Howeth, J., Amjad, S., Gantz, C., Mandrak, N., Angermeier, P., Marchetti, M., Olden, J., and Lodge, D., 2025, Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes: Biological Invasions, v. 27, 107, 26 p., https://doi.org/10.1007/s10530-025-03560-1.","productDescription":"107, 26 p.","ipdsId":"IP-171323","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-025-03560-1","text":"Publisher Index 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,{"id":70266168,"text":"70266168 - 2025 - Predicting bat roosts in bridges using Bayesian Additive Regression Trees","interactions":[],"lastModifiedDate":"2025-04-30T14:55:09.773729","indexId":"70266168","displayToPublicDate":"2025-03-22T08:11:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bat roosts in bridges using Bayesian Additive Regression Trees","docAbstract":"Human-built structures can provide important habitat for wildlife, but predicting which structures are most likely to be used remains challenging. To evaluate the predictive capabilities of data-driven ensemble modeling approaches, we conducted surveys for bats and signs of bat use, such as urine and guano staining, at bridges across the southwestern United States. We developed a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that the lack of nearby water resources was associated with a lower predicted probability of bat presence or signs of bat use at bridges. While the presence of nearby water resources was associated with higher average predicted probability of bat presence or signs of bat use, high uncertainty surrounding these estimates indicates that other factors also play a role in determining which bridge roosts bats are more likely to use. As such, our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. We extrapolated our model to unsurveyed bridges across the study region and provide an interactive dashboard application interface for the exploration of these results. Overall, this study demonstrates the application of BART as a predictive tool for prioritizing future bridge surveys for bats roosting in transportation structures.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03551","usgsCitation":"Oram, J., Wray, A.K., Davis, H.T., de Wit, L., Frick, W.F., Hoegh, A.B., Irvine, K.M., Pollock, P., Schuhmann, A.N., Tousley, F.C., and Reichert, B., 2025, Predicting bat roosts in bridges using Bayesian Additive Regression Trees: Global Ecology and Conservation, v. 60, e03551, 12 p., https://doi.org/10.1016/j.gecco.2025.e03551.","productDescription":"e03551, 12 p.","ipdsId":"IP-176127","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490934,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HVQHW","text":"USGS data release","linkHelpText":"North American Bat Monitoring Program (NABat) OneHealth (ver. 2.0, June 2025)"},{"id":487849,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03551","text":"Publisher Index Page"},{"id":485140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, New Mexico, Texas","otherGeospatial":"southwestern United 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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":934782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Wit, Luz A.","contributorId":353942,"corporation":false,"usgs":false,"family":"de Wit","given":"Luz A.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":934783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frick, Winifred F. 0000-0002-9469-1839","orcid":"https://orcid.org/0000-0002-9469-1839","contributorId":337076,"corporation":false,"usgs":false,"family":"Frick","given":"Winifred","email":"","middleInitial":"F.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":934784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":934785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":934786,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pollock, Patrick","contributorId":353945,"corporation":false,"usgs":false,"family":"Pollock","given":"Patrick","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":934787,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":934788,"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":934789,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":934790,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70265231,"text":"70265231 - 2025 - Linking environmental variability to long-term demographic change of an endangered species using integrated population models","interactions":[],"lastModifiedDate":"2025-05-12T15:43:41.572164","indexId":"70265231","displayToPublicDate":"2025-03-21T09:21:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linking environmental variability to long-term demographic change of an endangered species using integrated population models","docAbstract":"<ol class=\"\"><li>Understanding how species populations change with environmental conditions is important for implementing effective habitat management and conservation strategies. Challenges to evaluating population-level responses to environmental conditions arise when data are sparse or not spatiotemporally aligned, especially for at-risk species with small, declining numbers.</li><li>We synthesized 30 years (1992–2021) of three partially aligned data sets to build a Bayesian integrated population model (IPM) and evaluate demographic and environmental drivers of growth rates for six separately managed ‘subpopulations’ (A–F) of the federally endangered Cape Sable seaside sparrow endemic to the Florida Everglades.</li><li>We found that juvenile survival peaked at inundation periods (hydroperiods) around 100–220 days and dropped sharply outside those values, while adult survival increased with longer periods of water depth &lt;20 cm, but not with longer periods of water depth &gt;20 cm. Fecundity increased when water depths were more stable, more area was dry, intervals between fires were longer and less area was burned.</li><li>Changes in population growth rates tended to occur in years that juvenile and adult survival were associated with hydroperiod, especially in the two largest subpopulations B and E. Population growth rates were also associated with hydrologic conditions during the breeding season and fire dynamics through changes in fecundity, most notably in the smaller subpopulations A, C/F and D.</li><li><i>Synthesis and applications</i>. Our IPM represents the first long-term population analysis of the Cape Sable seaside sparrow connecting demographic processes to environmental factors. Our results suggest that sustaining periods of shallow water year-round may enhance Cape Sable seaside sparrow survival and population growth. Also, limiting water depth variability and maintaining dry conditions during the breeding season and inhibiting fires in consecutive years may increase fecundity and population growth. Identifying the mechanistic links between environmental and population dynamics could inform how species are expected to respond to management decisions and anticipated ecosystem changes.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70038","collaboration":"U.S. Fish and Wildlife Service, National Park Service","usgsCitation":"Martinez, M.T., D’Acunto, L., and Romanach, S., 2025, Linking environmental variability to long-term demographic change of an endangered species using integrated population models: Journal of Applied Ecology, v. 62, no. 5, p. 1137-1151, https://doi.org/10.1111/1365-2664.70038.","productDescription":"15 p.","startPage":"1137","endPage":"1151","ipdsId":"IP-163974","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488471,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.70038","text":"Publisher Index Page"},{"id":484130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.27756478832899,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.9167\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"62","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Marisa Takada 0000-0002-1915-6019","orcid":"https://orcid.org/0000-0002-1915-6019","contributorId":304805,"corporation":false,"usgs":true,"family":"Martinez","given":"Marisa","email":"","middleInitial":"Takada","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265260,"text":"70265260 - 2025 - Drought in the Delta: Socio-ecological impacts, responses, and tools","interactions":[],"lastModifiedDate":"2025-04-03T23:10:53.927858","indexId":"70265260","displayToPublicDate":"2025-03-20T15:43:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Drought in the Delta: Socio-ecological impacts, responses, and tools","docAbstract":"Droughts are frequent events in the western United States, and can disrupt water supply and degrade water quality, challenging water management in the Sacramento–San Joaquin Delta (Delta). This chapter for the State of Bay–Delta Science report describes what drought means for the Delta, how drought is managed in the Delta, and how drought management has changed over time. Projections of future climate indicate the possibility of increased frequency and severity of droughts which would have increasing effects on California’s water system, society, and ecological functions within and beyond the Delta. California has experienced several major droughts in the 20th and 21st centuries, each of which has caused significant social and ecological impacts and motivated improvements in water management. Droughts decrease native fish populations, increase harmful algal blooms, and promote the spread of many invasive plant and animal species. For people living within the Delta and those that rely on Delta water exports, droughts increase drinking water costs and decrease agricultural production, negatively affecting agricultural economies and labor markets. Tools developed in response to droughts include actions that increase supply, such as building water infrastructure, actions to reduce demand, such as water conservation campaigns, and mitigation actions, such as monetary relief for drought-impacted communities. Improving drought resilience requires development of additional drought responses, increased forecasting accuracy, and increased awareness of impacts on vulnerable communities and ecosystems. Even with development of additional management actions, strategies, and regulations, there will likely be difficulties meeting the current levels of demand for water. Drought conditions already cause conflict between human and environmental uses, and with more extreme droughts possible in the future and projected increases in demand, it will be challenging to provide for all users’ needs even with major changes to water management in the Delta.","language":"English","publisher":"San Francisco Estuary and Watershed Science","doi":"10.15447/sfews.2025v23iss1art3","usgsCitation":"Hartman, R., Knowles, N., Fencl, A., and Ekstrom, J., 2025, Drought in the Delta: Socio-ecological impacts, responses, and tools: San Francisco Estuary and Watershed Science, v. 23, no. 1, 3, 62 p., https://doi.org/10.15447/sfews.2025v23iss1art3.","productDescription":"3, 62 p.","ipdsId":"IP-165574","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":488603,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2025v23iss1art3","text":"Publisher Index Page"},{"id":484181,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.34896936938145,\n              38.77286456314664\n            ],\n            [\n              -123.34896936938145,\n              36.830761244624284\n            ],\n            [\n              -120.62613364311007,\n              36.830761244624284\n            ],\n            [\n              -120.62613364311007,\n              38.77286456314664\n            ],\n            [\n              -123.34896936938145,\n              38.77286456314664\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, Rosemary","contributorId":352954,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":932621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Noah 0000-0001-5652-1049","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":206338,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":932622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fencl, Amanda","contributorId":352956,"corporation":false,"usgs":false,"family":"Fencl","given":"Amanda","affiliations":[{"id":27801,"text":"Union of Concerned Scientists","active":true,"usgs":false}],"preferred":false,"id":932623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ekstrom, Julia","contributorId":352958,"corporation":false,"usgs":false,"family":"Ekstrom","given":"Julia","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":932624,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70264694,"text":"ofr20251004 - 2025 - Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","interactions":[],"lastModifiedDate":"2025-03-26T19:46:15.392167","indexId":"ofr20251004","displayToPublicDate":"2025-03-20T13:10:17","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1004","displayTitle":"Science Needs for Determining the Effects of Climate Change on Harmful Algal Blooms in the Southeastern United States","title":"Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","docAbstract":"<p>The Southeastern United States has many lakes, streams, and reservoirs that serve as important drinking water sources with recreational, agricultural, and ecological uses. However, harmful algal blooms (HABs) are becoming more common in these waters, causing health issues for humans and animals. HABs have been listed as a contaminant of emerging concern, and the magnitude, frequency, and duration of HABs appear to be increasing at the global scale. While it is well known that nutrients stimulate algae growth, it is not clear how climate change and other parameters stimulate the development of toxin production by HABs. The scientific literature describes parameters, such as storm occurrence, temperature, dissolved metals, erosion of soils, increasing length of growing season, discharge, and hydroperiod, that may affect algae growth and toxin production. Climate and hydrologic models address many of the physical and environmental parameters that influence HABs, but no climate models directly address HABs. This report compiles information from the existing literature pertaining to HABs and the modeling and forecasting of HABS. This compilation is done through the incorporation of climate change models. HAB research that involves climate change will require multiple disciplines that bring together ecologists, hydrologists, climatologists, engineers, economists, and new technology. Resource managers could use geographic data about the occurrence and distribution of HABs to develop models that identify waterbodies more vulnerable to HAB events. Development of such models will require teams capable of integrating biological, chemical, and physical factors. Model development will require additional research that can resolve anthropogenic and climate-related environmental factors to identify trends in freshwater HABs. The complexity and interconnectedness of the parameters that influence HAB occurrences will make model development challenging and require rigorous regional calibration.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251004","issn":"2331-1258","collaboration":"Prepared in cooperation with the Southeast Climate Adaptation Science Center and  Tennessee State University","usgsCitation":"Byl, T.D., Moore, D.M., Cunningham, C., and Young, D., 2025, Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States: U.S. Geological Survey Open-File Report 2025–1004, 29 p., https://doi.org/10.3133/ofr20251004.","productDescription":"vii, 29 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-156959","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":483554,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1004 HTML"},{"id":483549,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1004/coverthb.jpg"},{"id":483553,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1004 XML"},{"id":483551,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.pdf","size":"7.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1004"},{"id":483550,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1004/images"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211<br></p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-olk-copy-source=\"MailCompose\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Background on HABs and Cyanobacteria</li><li>Drivers of HAB Events</li><li>Development of Models</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-03-20","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Byl, Tom D. 0000-0001-6907-9149","orcid":"https://orcid.org/0000-0001-6907-9149","contributorId":352440,"corporation":false,"usgs":true,"family":"Byl","given":"Tom D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Devin M. 0009-0003-6919-8625","orcid":"https://orcid.org/0009-0003-6919-8625","contributorId":352441,"corporation":false,"usgs":false,"family":"Moore","given":"Devin M.","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Champagne 0000-0001-6318-5434","orcid":"https://orcid.org/0000-0001-6318-5434","contributorId":352442,"corporation":false,"usgs":true,"family":"Cunningham","given":"Champagne","affiliations":[],"preferred":true,"id":931301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, De’Etra","contributorId":352443,"corporation":false,"usgs":false,"family":"Young","given":"De’Etra","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931300,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70264658,"text":"sir20255013 - 2025 - Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2025-07-23T17:11:15.939504","indexId":"sir20255013","displayToPublicDate":"2025-03-19T11:57:37","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":"2025-5013","displayTitle":"Hydrogeologic Investigation, Framework, and Conceptual Flow Model of the Antlers Aquifer, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","docAbstract":"<p>The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. Every 20 years, the Oklahoma Water Resources Board is required to update the hydrologic investigation on which the maximum annual yield determinations were based. The maximum annual yield allocated per acre of land is used to set the equal-proportionate share pumping rate. The maximum annual yield of 5,913,600 acre-feet per year and equal-proportionate-share of 2.1 acre-feet per acre per year currently (2025) in place for the Antlers aquifer were issued by the Oklahoma Water Resources Board on February 14, 1995. Because more than 20 years have elapsed since the 1995 final order for the Antlers aquifer was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an in-depth hydrologic study that included a hydrogeologic framework and conceptual groundwater-flow model for the 1980–2022 study period.</p><p>The results of an analysis of land use, long-term climate patterns, streamflow and base-flow patterns, historical groundwater use, as well as groundwater-level fluctuations across the Antlers aquifer are described. In addition, groundwater quality was analyzed for total dissolved solids concentrations and major ions for the Antlers aquifer. An updated hydrogeologic framework was developed that included refining the aquifer boundary in Oklahoma, the creation of new potentiometric surface and saturated thickness of fresh groundwater maps, one multiple-well aquifer test, slug tests, and an analysis of lithologic logs across the aquifer. A conceptual groundwater flow model and water budget were developed by incorporating estimates of recharge from precipitation, saturated-zone evapotranspiration, streambed seepage, lateral groundwater flows, vertical leakage, and withdrawals from groundwater wells.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255013","issn":"2328-0328","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Fetkovich, E.J., Morris, A.S., Dale, I.A., Codner, C., Kirby, E.A., Baciocco, C.A., Rogers, I.M.J., Wagner, D.L., Tomlinson, Z.D., and Fiorentino, E.G., 2025, Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022: U.S. Geological Survey Scientific Investigations Report 2025–5013, 55 p., https://doi.org/10.3133/sir20255013.","productDescription":"Report: x, 55 p.; Data Release; Dataset","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-149893","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":492792,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118496.htm","linkFileType":{"id":5,"text":"html"}},{"id":483543,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255013/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5013 HTML"},{"id":483492,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://waterdata.usgs.gov/nwis","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483491,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14C6QFS","text":"USGS Data Release","linkHelpText":"- Soil-water-balance model and data used in the hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1967–2022"},{"id":483483,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5013/coverthb.jpg"},{"id":483484,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5013/images"},{"id":483485,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5013/sir20255013.pdf","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5013"},{"id":483542,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5013/sir20255013.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5013 XML"}],"country":"United States","state":"Oklahoma, Texas","otherGeospatial":"Antlers aquifer study","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.55,\n              34.5\n            ],\n            [\n              -97.55,\n              33.25\n            ],\n            [\n              -94.5,\n              33.25\n            ],\n            [\n              -94.5,\n              34.5\n            ],\n            [\n              -97.55,\n              34.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/ot-water\" href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane<br>Austin, TX 78754–4501</p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology of the Antlers Aquifer and Surrounding Units</li><li>Hydrogeologic Framework of the Antlers Aquifer</li><li>Conceptual Groundwater Flow Model and Water Budget</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-03-19","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Fetkovich, Evin J. 0000-0002-8899-8543","orcid":"https://orcid.org/0000-0002-8899-8543","contributorId":328666,"corporation":false,"usgs":true,"family":"Fetkovich","given":"Evin","email":"","middleInitial":"J.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Amy S. 0000-0002-9847-5607","orcid":"https://orcid.org/0000-0002-9847-5607","contributorId":352415,"corporation":false,"usgs":true,"family":"Morris","given":"Amy S.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dale, Isaac A. 0000-0003-0844-0193","orcid":"https://orcid.org/0000-0003-0844-0193","contributorId":352322,"corporation":false,"usgs":true,"family":"Dale","given":"Isaac A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Codner, Chloe 0009-0009-6577-8706","orcid":"https://orcid.org/0009-0009-6577-8706","contributorId":352321,"corporation":false,"usgs":true,"family":"Codner","given":"Chloe","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirby, Ethan A. 0000-0001-7521-5477","orcid":"https://orcid.org/0000-0001-7521-5477","contributorId":352416,"corporation":false,"usgs":true,"family":"Kirby","given":"Ethan A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baciocco, Colin A. 0000-0002-9548-9077","orcid":"https://orcid.org/0000-0002-9548-9077","contributorId":352323,"corporation":false,"usgs":true,"family":"Baciocco","given":"Colin A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931147,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogers, Ian M.J. 0000-0001-8492-5358","orcid":"https://orcid.org/0000-0001-8492-5358","contributorId":46036,"corporation":false,"usgs":true,"family":"Rogers","given":"Ian","email":"","middleInitial":"M.J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931139,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Derrick L. 0000-0002-9291-7785","orcid":"https://orcid.org/0000-0002-9291-7785","contributorId":345145,"corporation":false,"usgs":false,"family":"Wagner","given":"Derrick","email":"","middleInitial":"L.","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":true,"id":931140,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tomlinson, Zachary D.","contributorId":352418,"corporation":false,"usgs":false,"family":"Tomlinson","given":"Zachary D.","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":true,"id":931141,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Eric G. Fiorentino","contributorId":351558,"corporation":false,"usgs":false,"family":"Eric G. Fiorentino","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":false,"id":931142,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70264423,"text":"70264423 - 2025 - Hydrological whiplash: Highlighting the need for better understanding and quantification of sub-seasonal hydrological extreme transitions","interactions":[],"lastModifiedDate":"2025-03-31T14:48:27.054575","indexId":"70264423","displayToPublicDate":"2025-03-19T09:44:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Hydrological whiplash: Highlighting the need for better understanding and quantification of sub-seasonal hydrological extreme transitions","docAbstract":"<p><span>In this commentary, we aim to (1) describe ways that hydrological intensification and hydrological whiplash (sub-seasonal transitions between hydrological extremes) may impact water management decision-making, (2) introduce the complexities of identifying and quantifying hydrological extreme transitions, (3) discuss the processes controlling hydrological transitions and trends in hydrological extremes through time, (4) discuss considerations involved in modeling hydrological extreme transitions, and (5) motivate additional research by suggesting priority research questions that diverge from an assumption of independence between extreme events.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70113","usgsCitation":"Hammond, J., Anderson, B., Simeone, C., Brunner, M., Munoz-Castro, E., Archfield, S.A., Magee, E., and Armitage, R., 2025, Hydrological whiplash: Highlighting the need for better understanding and quantification of sub-seasonal hydrological extreme transitions: Hydrological Processes, v. 39, no. 3, e70113, 9 p., https://doi.org/10.1002/hyp.70113.","productDescription":"e70113, 9 p.","ipdsId":"IP-174142","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":484020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Bailey","contributorId":352305,"corporation":false,"usgs":false,"family":"Anderson","given":"Bailey","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simeone, Caelan 0000-0003-3263-6452","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221008,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brunner, Manuela","contributorId":352306,"corporation":false,"usgs":false,"family":"Brunner","given":"Manuela","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munoz-Castro, Eduardo","contributorId":352307,"corporation":false,"usgs":false,"family":"Munoz-Castro","given":"Eduardo","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - 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,{"id":70266530,"text":"70266530 - 2025 - A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales","interactions":[],"lastModifiedDate":"2025-05-09T14:47:14.01538","indexId":"70266530","displayToPublicDate":"2025-03-19T09:42:52","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":"A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales","docAbstract":"<p><span>The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as ‘inconclusive’ and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling for&nbsp;</span><i>Pseudogymnoascus destructans (Pd)</i><span>, the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence of&nbsp;</span><i>Pd</i><span>&nbsp;at bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM’s results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM’s estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had been&nbsp;</span><i>Pd</i><span>&nbsp;positive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding of&nbsp;</span><i>Pd</i><span>&nbsp;dynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-93865-x","usgsCitation":"Gridder, J., Udell, B.J., Reichert, B., Foster, J., Kendall, W.L., Cheng, T., and Frick, W.F., 2025, A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales: Scientific Reports, v. 15, 9423, 10 p., https://doi.org/10.1038/s41598-025-93865-x.","productDescription":"9423, 10 p.","ipdsId":"IP-166127","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490111,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-93865-x","text":"Publisher Index Page"},{"id":485644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.26363777562113,\n              49.48504400263704\n            ],\n            [\n              -97.26363777562113,\n              32.49418643417637\n            ],\n            [\n              -70.38881830989425,\n              32.49418643417637\n            ],\n            [\n              -70.38881830989425,\n              49.48504400263704\n            ],\n            [\n              -97.26363777562113,\n              49.48504400263704\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Gridder, John F.","contributorId":354814,"corporation":false,"usgs":false,"family":"Gridder","given":"John F.","affiliations":[{"id":84669,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":936476,"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":936477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":936478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Jeffery T.","contributorId":351633,"corporation":false,"usgs":false,"family":"Foster","given":"Jeffery T.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":936479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, William Louis 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":257230,"corporation":false,"usgs":false,"family":"Kendall","given":"William","email":"","middleInitial":"Louis","affiliations":[{"id":51981,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, 201 J.V.K. Wagar Building 1484 Campus Delivery, Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":936480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheng, Tina L.","contributorId":127716,"corporation":false,"usgs":false,"family":"Cheng","given":"Tina L.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":936481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frick, Winifred F. 0000-0002-9469-1839","orcid":"https://orcid.org/0000-0002-9469-1839","contributorId":337076,"corporation":false,"usgs":false,"family":"Frick","given":"Winifred","email":"","middleInitial":"F.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":936482,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70270681,"text":"70270681 - 2025 - A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee","interactions":[],"lastModifiedDate":"2025-08-25T13:35:28.429518","indexId":"70270681","displayToPublicDate":"2025-03-19T09:36:42","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-166-2025","title":"A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee","docAbstract":"<p><span>We have developed a comprehensive database for freshwater mussels for the Duck River drainage in Tennessee, including its largest tributary, the Buffalo River. &nbsp;This database is intended to serve as an expandable template that could be applied statewide. &nbsp;The Duck River is one of the most biologically diverse rivers in the world, with historically over 70 mussel species, and it has been selected as a priority watershed by multiple management and conservation entities. &nbsp;The database for this system compiles over 7,000 mussel records, spanning 200 years, from multiple Federal, State, academic, and private entities, representing 77 native species. &nbsp;The database is spatially explicit and includes temporal and methodological data for each record, and notes of negative survey data were made when possible. &nbsp;The database can facilitate the creation of distribution maps for each species and temporal maps of species richness to show watershed-wide trends. &nbsp;This project addresses the present lack of a centralized mussel database in Tennessee for a critical system. It will be available to facilitate species status assessments, inform conservation planning, and serve as a model for similar databases for other Tennessee watersheds.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css36499787","usgsCitation":"Womble, K.I., and Rosenberger, A.E., 2025, A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee: Cooperator Science Series CSS-166-2025, ii, 100 p., https://doi.org/10.3996/css36499787.","productDescription":"ii, 100 p.","ipdsId":"IP-174003","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496393,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/css36499787","text":"Publisher Index Page"},{"id":494515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Duck River drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88,\n              36.15\n            ],\n            [\n              -88,\n              35\n            ],\n            [\n              -86,\n              35\n            ],\n            [\n              -86,\n              36.15\n            ],\n            [\n              -88,\n              36.15\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Womble, Kristen Irwin","contributorId":360120,"corporation":false,"usgs":false,"family":"Womble","given":"Kristen","middleInitial":"Irwin","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":946812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":946813,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70264714,"text":"70264714 - 2025 - Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2025-03-20T14:36:34.442104","indexId":"70264714","displayToPublicDate":"2025-03-19T09:32:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin","docAbstract":"<p><span>Salinity levels in streams and tributaries of the Colorado River Basin have been a major concern for the United States and Mexico for over 50 years as the water is used by millions of people for domestic and industrial purposes. Recently, the United States Geological Survey expanded stream monitoring networks including the number of sites where continuous (15-min) specific conductance is measured in the Colorado River Headwaters and Gunnison River Basin located east of the Colorado-Utah state line (hereafter, UCOL). The purpose of this study is to apply a proxy method to determine salinity and total dissolved solids concentrations from specific conductance and major-ion water type that is applicable to monitoring sites in the UCOL. Within the UCOL, carbonate rich waters originate from high-elevation mountain regions in the eastern UCOL, calcium sulfate rich waters are mainly found in the western half of the UCOL including the Gunnison River Basin, and waters of variable composition are found along the lower reaches of the Colorado River and Eagle River. It was found that the chemistry of sites with variable composition changes seasonally and is impacted by both geogenic and anthropogenic processes, potentially including seasonal application of deicing road salt. The specific conductance – water type proxy can be used to reliably (±10 %) predict salinity and total dissolved solids at 66 monitoring sites in the UCOL. The method is rapid, can generate high-resolution measurements, is cost-effective, and greatly expands the utility of specific conductance measurements. Furthermore, the high-resolution estimates provide an accurate approach to determining long-term salinity loads as short-term events are accurately accounted for.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2025.106358","usgsCitation":"McCleskey, R., Cravotta, C., Miller, M., Chapin, T.W., Tillman, F.D., and Keith, G.L., 2025, Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin: Applied Geochemistry, v. 184, 106358, 11 p., https://doi.org/10.1016/j.apgeochem.2025.106358.","productDescription":"106358, 11 p.","ipdsId":"IP-170952","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":483579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.8482146743099,\n              40.404889992338354\n            ],\n            [\n              -109.03080773170848,\n              40.404889992338354\n            ],\n            [\n              -109.03080773170848,\n              38.16700844876755\n            ],\n            [\n              -104.8482146743099,\n              38.16700844876755\n            ],\n            [\n              -104.8482146743099,\n              40.404889992338354\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCleskey, R. 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III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":338312,"corporation":false,"usgs":false,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":81112,"text":"Cravotta Geochemical Consulting","active":true,"usgs":false}],"preferred":false,"id":931415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":931416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapin, Tanner William 0000-0003-3905-3241","orcid":"https://orcid.org/0000-0003-3905-3241","contributorId":297923,"corporation":false,"usgs":true,"family":"Chapin","given":"Tanner","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931419,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264723,"text":"70264723 - 2025 - Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures","interactions":[],"lastModifiedDate":"2025-07-09T15:58:44.092141","indexId":"70264723","displayToPublicDate":"2025-03-19T07:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures","docAbstract":"We use the deterministic earthquake simulator RSQSim to generate complex sequences of ruptures on fault systems used for hazard assessment. We show that the source motions combined with a wave propagation code create surface ground motions that fall within the range of epistemic uncertainties for the Next Generation Attenuation‐West2 set of empirical models. We show the model is well calibrated where there are good data constraints, and has good correspondence in regions with fewer data constraints. We show magnitude, distance, and mechanism dependence all arising naturally from the same underlying friction. The deterministic physics‐based approach provides an opportunity for better understanding the physical origins of ground motions. For example, we find that reduced stress drops in shallow layers relative to constant stress drop with depth lead to peak ground velocities in the near field that better match empirical models. The simulators may also provide better extrapolations into regimes that are poorly empirically constrained by data because physics, rather than surface shaking data parameterizations, is underlying the extrapolations. Having shown the model is credible, we apply it to a problem where observations are lacking. We examine the case of crustal faults above a shallow subduction interface seen to break coseismically in simulations of the New Zealand fault system. These types of events were left out of consideration in the most recent New Zealand national seismic hazard model due to the modeling complexity and lack of observational data to constrain ground‐motion models (GMMs). Here, we show that in the model, by breaking up the coseismic crustal and interface rupturing fault motions into two separate subevents, and then recombining the resulting ground‐motion measures in a square‐root‐of‐sum‐of‐squares incoherent manner, we reproduce well the ground‐motion measures from the full event rupture. This provides a new method for extrapolating GMMs to more complex multifault ruptures.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240141","usgsCitation":"Shaw, B.E., Milner, K., and Goulet, C.A., 2025, Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures: Seismological Research Letters, v. 96, no. 4, p. 2431-2444, https://doi.org/10.1785/0220240141.","productDescription":"14 p.","startPage":"2431","endPage":"2444","ipdsId":"IP-170334","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483583,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaw, Bruce E.","contributorId":194146,"corporation":false,"usgs":false,"family":"Shaw","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":931438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin Ross 0000-0002-9118-6378","orcid":"https://orcid.org/0000-0002-9118-6378","contributorId":352491,"corporation":false,"usgs":true,"family":"Milner","given":"Kevin Ross","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":931439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goulet, Christine A 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":336587,"corporation":false,"usgs":true,"family":"Goulet","given":"Christine","email":"","middleInitial":"A","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":931440,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70264368,"text":"fs20243037 - 2025 - United States Register of Introduced and Invasive Species","interactions":[],"lastModifiedDate":"2025-08-07T20:34:26.292535","indexId":"fs20243037","displayToPublicDate":"2025-03-18T16:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3037","displayTitle":"United States Register of Introduced and Invasive Species","title":"United States Register of Introduced and Invasive Species","docAbstract":"<p>The pervasive and insidious threat of invasive species costs the United States more than $120 billion, annually. An invasive species is an organism that is not native to a locality and causes (or is likely to cause) harm. An introduced species is one that is nonnative to a locality and occurs there because of human activities or their consequences, including the species’ intentional or unintentional escape, release, dissemination, or placement. The United States Register of Introduced and Invasive Species (US-RIIS, ver. 2.0) contains 14,700 records for three localities: Alaska (545 records), Hawaii (5,628 records), and the conterminous United States (L48; 8,527 records). For these localities, the US-RIIS catalogs introduced species that have become established, thus providing a basis for their prioritization and management. To be included on the US-RIIS, a species must be nonnative to the entire locality and reproducing anywhere in the locality. Each US-RIIS record has information on taxonomy, dates of introduction (where available; version 2.0 for 47 percent of the records), invasion status (invasive or introduced), use for biocontrol (if applicable), and a citation for the information source(s). The US-RIIS was designed to be compatible with country contributions to the Global Register of Introduced and Invasive Species Initiative, which compiles annotated and verified country-wide inventories of introduced and invasive species. Within the US-RIIS, the density of introduced species per 10,000 square kilometers among the localities ranges markedly, from 3 in Alaska to 1,988 in Hawaii (11 in the L48). The comparative taxonomic composition of the largest groups in the sublists also varies: the Alaska sublist has a majority of flowering plants; Hawaii has a majority of insects; and the L48 is about equally divided between insects and flowering plants. Another benefit of the US-RIIS is that it provides a baseline for effective modeling of species trends and interactions, geospatially and temporally; therefore, it can also be used to track introduced sleeper species that will eventually become invasive.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243037","programNote":"Science Synthesis, Analysis, and Research Program","usgsCitation":"Simpson, A., Wiltermuth, M.T., and Dorado, M., 2025, United States Register of Introduced and Invasive Species (ver. 1.1, April 2025): U.S. Geological Survey Fact Sheet 2024–3037, 4 p., https://doi.org/10.3133/fs20243037.","productDescription":"Report: 4 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-157268","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":493745,"rank":9,"type":{"id":36,"text":"NGMDB Index 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March 18, 2025; Version 1.1: April 8, 2025","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/science-analytics-and-synthesis-sas/\" data-mce-href=\"https://www.usgs.gov/programs/science-analytics-and-synthesis-sas/\">Science Analytics and Synthesis Program</a><br>U.S. Geological Survey<br>Box 25046, MS 302<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Introduction</li><li>Methods</li><li>Results</li><li>What’s the Difference?&nbsp; Introduced and Invasive Species</li><li>How Can You Help?</li><li>For More Information</li></ul>","publishedDate":"2025-03-18","revisedDate":"2025-04-08","noUsgsAuthors":false,"publicationDate":"2025-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Simpson, Annie 0000-0001-8338-5134","orcid":"https://orcid.org/0000-0001-8338-5134","contributorId":352267,"corporation":false,"usgs":false,"family":"Simpson","given":"Annie","affiliations":[{"id":84145,"text":"U.S. Geological Survey, Former Employee","active":true,"usgs":false}],"preferred":false,"id":930545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":930546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorado, Mireya","contributorId":352268,"corporation":false,"usgs":false,"family":"Dorado","given":"Mireya","affiliations":[{"id":84146,"text":"Student, Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":930547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272248,"text":"70272248 - 2025 - Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks","interactions":[],"lastModifiedDate":"2025-11-20T16:04:16.55833","indexId":"70272248","displayToPublicDate":"2025-03-18T08:53:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks","docAbstract":"<p>Objective</p><p> Although conserving fish biodiversity in lotic systems is challenging, protected areas can provide refuge from certain environmental stressors. In the Appalachian region, USA, the National Park Service manages Delaware Water Gap National Recreation Area (DEWA) and New River Gorge National Park &amp; Preserve (NERI), which contain abundant and diverse freshwater resources. To assess the effectiveness of these protected areas in conserving stream fishes, we evaluated decadal changes and ecological drivers of species occupancy and detection. </p><p>Methods </p><p>Using fish assemblage data from backpack electrofishing surveys conducted in both parks during 2013–2014 and 2022–2023, we quantified temporal differences in species occupancy and detection probabilities using a Bayesian hierarchical multispecies occupancy modeling approach. For the 2022–2023 survey, we included habitat variables as predictors of occupancy and detection. </p><p>Results</p><p><span>Community composition and occupancy probabilities for species in both parks remained similar through time, with the most recent occupancy estimates ranging from 0.07 (90% CI = 0.02, 0.14) for Variegate Darter&nbsp;</span><i>Etheostoma variatum</i><span>&nbsp;and Rainbow Darter&nbsp;</span><i>E. ­caeruleum</i><span>&nbsp;to 0.73 (90% credible interval = 0.59, 0.85) for Blacknose Dace&nbsp;</span><i>Rhinichthys atratulus</i><span>. Changes in occupancy were more prominent at Delaware Water Gap National Recreation Area than New River Gorge National Park &amp; Preserve, with Yellow Perch&nbsp;</span><i>Perca flavescens</i><span>&nbsp;having a posterior mean difference of −0.17 [90% credible interval = −0.35, −0.01] and American Eel&nbsp;</span><i>Anguilla rostrata</i><span>&nbsp;having a high posterior probability (&gt;80%) of occupancy increasing by at least 1%. Habitat variables were related to community structure, but effects varied in significance, magnitude, and direction among species and parks. Conversely, species-specific detection probabilities were comparatively less affected by environmental and sampling effort predictors.</span></p><p><span>Conclusions</span></p><p><span>Between 2013 and 2023, occupancy estimates for 44 fish species across two protected, ecologically diverse landscapes remained relatively stable. Furthermore, we highlight the efficacy of national parks in maintaining freshwater fish biodiversity amidst rapid global change.</span></p><p><span><br data-mce-bogus=\"1\"></span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnae001","usgsCitation":"Stum, M.B., Tzilkowski, C.J., Marshall, M.R., Buderman, F.E., and Wagner, T., 2025, Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks: Transactions of the American Fisheries Society, v. 154, no. 1, p. 17-34, https://doi.org/10.1093/tafafs/vnae001.","productDescription":"18 p.","startPage":"17","endPage":"34","ipdsId":"IP-171219","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":496759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/tafafs/vnae001","text":"Publisher Index Page"},{"id":496690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Pennsylvania, West Virginia","otherGeospatial":"Delaware Water Gap National Recreation Area, New River Gorge National Park and Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.89843107159835,\n              41.431514746901854\n            ],\n            [\n              -75.18455995359527,\n              40.990801971458694\n            ],\n            [\n              -74.90504430165323,\n              40.90329116200766\n            ],\n            [\n              -74.63249562743557,\n              41.39060918496995\n            ],\n            [\n              -74.89843107159835,\n              41.431514746901854\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.03803453005847,\n              37.87180093795311\n            ],\n            [\n              -81.03803453005847,\n              37.81645041875879\n            ],\n            [\n              -80.95306469595798,\n              37.81645041875879\n            ],\n            [\n              -80.95306469595798,\n              37.87180093795311\n            ],\n            [\n              -81.03803453005847,\n              37.87180093795311\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"154","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stum, Morgan B.","contributorId":362504,"corporation":false,"usgs":false,"family":"Stum","given":"Morgan","middleInitial":"B.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":950572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tzilkowski, Caleb J.","contributorId":362506,"corporation":false,"usgs":false,"family":"Tzilkowski","given":"Caleb","middleInitial":"J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":950573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marshall, Matthew R.","contributorId":362508,"corporation":false,"usgs":false,"family":"Marshall","given":"Matthew","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":950574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buderman, Frances E.","contributorId":362510,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":950575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":218091,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":950576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264525,"text":"sir20255007 - 2025 - A model uncertainty quantification protocol for evaluating the value of observation data","interactions":[],"lastModifiedDate":"2025-07-23T17:09:46.818291","indexId":"sir20255007","displayToPublicDate":"2025-03-17T11:20:49","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":"2025-5007","displayTitle":"A Model Uncertainty Quantification Protocol for Evaluating the Value of Observation Data","title":"A model uncertainty quantification protocol for evaluating the value of observation data","docAbstract":"<p>The history-matching approach to parameter estimation with models enables a powerful offshoot analysis of data worth—using the uncertainty of a model forecast as a metric for the worth of data. Adding observation data will either have no impact on forecast uncertainty or will reduce it. Removing existing data will either have no impact on forecast uncertainty or will increase it. The history-matching framework makes it possible to perform this quantitative analysis leveraging the connections among observations, model parameters, and model forecasts. We show this behavior on a specific groundwater flow model of the Mississippi Alluvial Plain and show where the analysis can be informative for considering the potential design of an observation network based on existing or potential observations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255007","usgsCitation":"Fienen, M.N., Schachter, L.A., and Hunt, R.J., 2025, A model uncertainty quantification protocol for evaluating the value of observation data: U.S. Geological Survey Scientific Investigations Report 2025–5007, 12 p., https://doi.org/10.3133/sir20255007.","productDescription":"vi; 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171702","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":483399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5007/sir20255007.pdf","text":"Report","size":"7.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025–5007"},{"id":483398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5007/coverthb.jpg"},{"id":483404,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255007/full","text":"Report"},{"id":483400,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5007/sir20255007.XML","text":"Report","description":"SIR 2025–5007"},{"id":483403,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5007/images"},{"id":492790,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118495.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umid-water\" href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, Wisconsin 53726</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>Purpose and Scope </li><li>A Note on Software Packages Used</li><li>Background Mathematics</li><li>Linear Uncertainty Methods—Three Main Approaches</li><li>Results of Analysis in the Mississippi Alluvial Plain Using Linear Uncertainty Methods</li><li>Limitations and Lessons Learned </li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-03-17","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schachter, Laura A. 0000-0001-7012-0081 lschachter@usgs.gov","orcid":"https://orcid.org/0000-0001-7012-0081","contributorId":304706,"corporation":false,"usgs":true,"family":"Schachter","given":"Laura","email":"lschachter@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930794,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70267350,"text":"70267350 - 2025 - Predicting pup-rearing habitat for Mexican wolves","interactions":[],"lastModifiedDate":"2025-06-23T15:23:29.362572","indexId":"70267350","displayToPublicDate":"2025-03-17T10:19:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Predicting pup-rearing habitat for Mexican wolves","docAbstract":"<p><span>Population monitoring is essential to document recovery efforts for threatened and endangered species. Mexican wolves (</span><i>Canis lupus baileyi</i><span>) are an endangered subspecies of gray wolves that historically occupied large portions of the American Southwest and Mexico. Recently, the Mexican wolf population in the United States has been growing rapidly and traditional approaches for population monitoring (e.g., capture and radio collaring) are becoming difficult and expensive as wolves expand into new areas. We developed predictive models of pup-rearing habitat (i.e., den and rendezvous sites) that could help guide future population monitoring efforts. We located 255 den sites and 129 rendezvous sites in Arizona and New Mexico, USA (1998–2023) using tracking collars and site visits. We sampled habitat conditions in wolf-occupied regions of Arizona and New Mexico and fit logistic regressions to these data following a use–available study design to estimate resource selection functions (RSF) for den and rendezvous sites. We hypothesized wolves would select areas that offered greater physical protection, lower human-disturbance, and access to reliable water sources for pup-rearing but that the relative importance of these features would differ between the denning and rendezvous site seasons. Mexican wolves selected den sites at higher elevations in steeper and rougher terrain that were closer to permanent waterbodies but farther from rural roads. Selection of rendezvous sites was also associated with higher elevations and proximity to waterbodies but varied with availability of green leaf biomass on the landscape. While still highly predictive, our rendezvous site model was less predictive than our den model (Spearman's correlation averaged 0.81 [SE = 0.05] vs. 0.90 [SE = 0.03], respectively), possibly because water and green leaf biomass are more spatially diffuse and variable because of monsoonal rains during the rendezvous site season. Our results suggest that terrain features associated with physical protection and access to reliable water were most important in characterizing suitable pup-rearing habitat for Mexican wolves. By predicting suitable den and rendezvous site habitat across portions of the Mexican Wolf Experimental Population Area, our models can help guide future population monitoring by reducing the total search area when surveying for wolves and increase the probability of detecting all members of a pack.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70017","usgsCitation":"Bassing, S., Oakleaf, J., Cain, J.W., Greenleaf, A., Gardner, C., and Ausband, D.E., 2025, Predicting pup-rearing habitat for Mexican wolves: Journal of Wildlife Management, v. 89, no. 5, e70017, 19 p., https://doi.org/10.1002/jwmg.70017.","productDescription":"e70017, 19 p.","ipdsId":"IP-169774","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486238,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":488960,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70017","text":"Publisher Index Page"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.15656068155297,\n              37.15236143729469\n            ],\n            [\n              -114.79334387076136,\n              36.19839033323856\n            ],\n            [\n              -114.82092420356022,\n              32.28431539821898\n            ],\n            [\n              -111.22371663071222,\n              31.529018437535207\n            ],\n            [\n              -108.37781874007106,\n              31.259432273304338\n            ],\n            [\n              -108.00163404937481,\n              31.805280742585737\n            ],\n            [\n              -103.03648352957026,\n              31.93273826397835\n            ],\n            [\n              -103.13422840316065,\n              37.15236143729469\n            ],\n            [\n              -114.15656068155297,\n              37.15236143729469\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"89","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bassing, Sarah B.","contributorId":355638,"corporation":false,"usgs":false,"family":"Bassing","given":"Sarah B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":937834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oakleaf, John K.","contributorId":355639,"corporation":false,"usgs":false,"family":"Oakleaf","given":"John K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greenleaf, Allison R.","contributorId":355640,"corporation":false,"usgs":false,"family":"Greenleaf","given":"Allison R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Colby M.","contributorId":355641,"corporation":false,"usgs":false,"family":"Gardner","given":"Colby M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937839,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265779,"text":"70265779 - 2025 - A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records","interactions":[],"lastModifiedDate":"2025-04-15T15:17:05.760533","indexId":"70265779","displayToPublicDate":"2025-03-17T10:11:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records","docAbstract":"<p><span>Great Aleutian underthrusting earthquakes produced destructive tsunamis impacting Hawaiʻi in 1946 and 1957. Prior modeling of the 1957 tsunami deposit and runup records on eastern Aleutian and Hawaiian Islands jointly with tide-gauge observations across the Pacific Ocean constrained a rupture model with shallow slip up to 26 m along 600 km of the plate boundary. Here we implement this modeling approach to older deposits and show alternating deep and shallow megathrust slip up to 26, 32, and 22 m for great earthquakes along the same segment in the 18</span><sup>th</sup><span>, 15</span><sup>th</sup><span>, and 14</span><sup>th</sup><span>&nbsp;centuries. All three modeled prehistoric Aleutian earthquakes produce tsunami inundation in Hawaiʻi with the most severe, 14</span><sup>th</sup><span>&nbsp;century event having impacts exceeding the 1957 event. The along-dip variability of these four ruptures spanning seven centuries provides insights on earthquake cycles for engineering design and hazard assessment. The 15</span><sup>th</sup><span>&nbsp;century and 1957 rupture models provide evidence for recurrence of tsunami earthquakes, which can produce disproportionately large tsunamis for a given moment magnitude due to reduced rigidity in the shallow megathrust. The 14</span><sup>th</sup><span>&nbsp;and 18</span><sup>th</sup><span>&nbsp;century events likely ruptured deeper regions that did not slip in 1957, suggesting potential for corresponding deeper failure in the next great eastern Aleutian earthquake.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-025-57802-w","usgsCitation":"Yamazaki, Y., Cheung, K.F., Lay, T., La Selle, S., Witter, R., and Jaffe, B., 2025, A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records: Nature Communications, v. 16, 2638, 16 p., https://doi.org/10.1038/s41467-025-57802-w.","productDescription":"2638, 16 p.","ipdsId":"IP-169333","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488253,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-57802-w","text":"Publisher Index Page"},{"id":484585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Hawaii","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -146.41033794940356,\n              60.59031062994006\n            ],\n            [\n              -179.99,\n              60.59031062994006\n            ],\n            [\n              -179.99,\n              18\n            ],\n            [\n              -146.41033794940356,\n              18\n            ],\n            [\n              -146.41033794940356,\n              60.59031062994006\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              172.7792582818936,\n              55.23104605282941\n            ],\n            [\n              172.7792582818936,\n              48.90879653399284\n            ],\n            [\n              179.99,\n              48.90879653399284\n            ],\n            [\n              179.99,\n              55.23104605282941\n            ],\n            [\n              172.7792582818936,\n              55.23104605282941\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Yamazaki, Yoshiki","contributorId":216792,"corporation":false,"usgs":false,"family":"Yamazaki","given":"Yoshiki","email":"","affiliations":[{"id":39517,"text":"University of Hawaii at Mano","active":true,"usgs":false}],"preferred":false,"id":933512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheung, Kwok Fai","contributorId":329690,"corporation":false,"usgs":false,"family":"Cheung","given":"Kwok","email":"","middleInitial":"Fai","affiliations":[{"id":78685,"text":"University of Hawai'i at Manoa","active":true,"usgs":false}],"preferred":false,"id":933513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lay, Thorne","contributorId":328838,"corporation":false,"usgs":false,"family":"Lay","given":"Thorne","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":933514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":933515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":933516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":335664,"corporation":false,"usgs":false,"family":"Jaffe","given":"Bruce E.","affiliations":[{"id":80462,"text":"former USGS PCMSC employee","active":true,"usgs":false}],"preferred":false,"id":933517,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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