Flood-frequency analysis provides the basis for flood risk estimates used by water-resource managers in land-use planning, and it informs the design of essential infrastructure such as bridges and culverts. Federal guidelines for flood-frequency analysis do not offer guidance on addressing changing climate and land-use conditions when estimating floods. However, failing to consider climatic and land-use changes that cause abrupt or gradual changes in flood regimes can result in a poor representation of the true flood risk.
In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies (Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation) began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The analyses of patterns and changes in hydrology and climate were reported in a multichapter Scientific Investigations Report, the findings of which are summarized in this U.S. Geological Survey Circular. Additional analyses documenting changes in seasonality of flooding and the effects of urbanization and tile drainage were completed and published as separate studies and are also summarized in this Circular. These studies provide extensive exploratory analysis of peak streamflow, daily streamflow, and climate data, setting the stage for advancements in flood-frequency analysis.
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U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies, began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The findings of that study are briefly summarized in this report.
","publicationDate":"2025-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barth, Nancy A. 0000-0002-7060-8244 nabarth@usgs.gov","orcid":"https://orcid.org/0000-0002-7060-8244","contributorId":298020,"corporation":false,"usgs":true,"family":"Barth","given":"Nancy","email":"nabarth@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":942795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Podzorski, Hannah Lee 0000-0001-5204-2606 hpodzorski@usgs.gov","orcid":"https://orcid.org/0000-0001-5204-2606","contributorId":333626,"corporation":false,"usgs":true,"family":"Podzorski","given":"Hannah","email":"hpodzorski@usgs.gov","middleInitial":"Lee","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sando, Steven K. 0000-0003-1206-1030","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":203451,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"","middleInitial":"K.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":942799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams-Sether, Tara 0000-0001-6515-9416","orcid":"https://orcid.org/0000-0001-6515-9416","contributorId":214143,"corporation":false,"usgs":true,"family":"Williams-Sether","given":"Tara","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"O’Shea, Padraic S. 0000-0001-9005-8289 poshea@usgs.gov","orcid":"https://orcid.org/0000-0001-9005-8289","contributorId":196742,"corporation":false,"usgs":true,"family":"O’Shea","given":"Padraic","email":"poshea@usgs.gov","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":942802,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70270226,"text":"70270226 - 2025 - The influence of human presence and footprint on animal space use in US national parks","interactions":[],"lastModifiedDate":"2025-08-13T14:14:41.59291","indexId":"70270226","displayToPublicDate":"2025-07-30T09:03:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"The influence of human presence and footprint on animal space use in US national parks","docAbstract":"Given the importance of protected areas for biodiversity, the growth of visitation to many areas has raised concerns about the effects of humans on wildlife. In 2020, the COVID-19 pandemic led to temporary closure of national parks in the United States, offering a pseudonatural experiment to tease apart the effects of permanent infrastructure and transient human presence on animals. We compiled GPS tracking data from 229 individuals of 10 mammal species in 14 parks and used third-order hierarchical resource selection functions to evaluate the influence of the human footprint on animal space use in 2019 and 2020. Averaged across all parks and species, animals avoided the human footprint, whether the park was open or closed. However, although animals in remote areas showed consistent avoidance, on average those in more developed areas switched from avoidance to selection when protected areas were closed. Findings varied across species: some responded consistently negatively to the footprint (wolves, mountain goats), some positively (mule deer, red fox) and others had a strong exposure-mediated response (elk, mountain lion). Furthermore, some species responded more strongly to the park closure (black bear, moose). This study advances our understanding of complex interactions between recreation and wildlife in protected areas.
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California","docAbstract":"This study assesses the impact of land subsidence on housing sale values in the San Joaquin Valley, California. The study utilizes home sale transactions and vertical land-surface displacement data from Interferometric Synthetic Aperture Radar techniques. Using fine-scale fixed effects, matching, as well as a repeat-sales approach, our results indicate that land subsidence resulted in a 2.4% to 5.8% reduction in housing sale values, with the largest reductions occurring in areas where substantial subsidence occurred. Such findings may have implications for groundwater management and can potentially help inform policy design to help mitigate the causes and impacts of land subsidence.
","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/le.102.1.092324-0083R","usgsCitation":"Nemati, M., Sneed, M., and Dinar, A., 2025, Impact of land subsidence on housing sale values: Evidence from the San Joaquin Valley, California: Land Economics, v. 101, no. 4, 092324-0083R, 49 p., https://doi.org/10.3368/le.102.1.092324-0083R.","productDescription":"092324-0083R, 49 p.","ipdsId":"IP-157861","costCenters":[{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true}],"links":[{"id":497087,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3368/le.102.1.092324-0083r","text":"Publisher Index Page"},{"id":496998,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","volume":"101","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Nemati, Mehdi","contributorId":363076,"corporation":false,"usgs":false,"family":"Nemati","given":"Mehdi","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":951082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sneed, Michelle 0000-0002-8180-382X","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":214186,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dinar, Ariel","contributorId":363077,"corporation":false,"usgs":false,"family":"Dinar","given":"Ariel","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":951084,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272048,"text":"70272048 - 2025 - Reaction kinetics and accelerant effects of sulfides in early mature hydrocarbon generation using hydrous pyrolysis","interactions":[],"lastModifiedDate":"2025-11-14T16:35:31.547406","indexId":"70272048","displayToPublicDate":"2025-07-29T10:31:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2156,"text":"Journal of Analytical and Applied Pyrolysis","active":true,"publicationSubtype":{"id":10}},"title":"Reaction kinetics and accelerant effects of sulfides in early mature hydrocarbon generation using hydrous pyrolysis","docAbstract":"Hydrocarbon generation in organic-rich sediments is influenced by the molecular organic composition and relative abundance of associated minerals. Certain mineral-derived elements act as catalysts and reaction intermediaries, facilitating early-stage hydrocarbon formation in potential source rocks. This study investigated the role of sulfur contributed from pyrite as an accelerant in thermal reaction, focusing on its effects on early maturation and consequent hydrocarbon generation from gilsonite (low-sulfur solid petroleum). Hydrous pyrolysis (HP) experiments were conducted on mixtures of gilsonite and pyrite in varying ratios (1:0.1, 1:0.5, 1:1, 1:2, and 1:10 w/w gilsonite:pyrite) at 320, 350, and 370 °C for 72 h. Untreated and thermally altered residues were analyzed using solid bitumen reflectance (BRo, %), total organic carbon (TOC) content, programmed temperature pyrolysis, scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and X-ray diffraction (XRD) to evaluate the potential accelerant role of pyritic sulfur in hydrocarbon formation. The results show HP residues at 320 and 350 °C with greater pyrite concentrations had higher BRo, while reflectance values were similar in the 370 °C residues, regardless of pyrite concentration, suggesting enhanced reaction at lower thermal conditions. Increasing pyrite content systematically decreased hydrogen index (HI) values while increasing the transformation ratio (TR) and production index (PI), indicating enhanced conversion of organic matter to hydrocarbons with increasing pyrite concentrations. Gas yields increased with pyrite addition, particularly at 350 °C, confirming secondary cracking effects. However, gas production stabilized or declined at higher pyrite loadings (1:10), suggesting alternative reaction pathways such as coke formation. Our data indicate the presence of pyrite lowers the activation energy for thermal cracking, shifting peak experimental hydrocarbon generation temperatures downward by 20–30 °C, with the most pronounced accelerant effects observed at moderate pyrite concentrations (1:0.5 and 1:1). The thermodynamic framework reveals that pyrite stability is influenced by experimental conditions, with pyrrhotite formation favored in the presence of gilsonite due to reduced oxygen fugacity. Pyrite transformation to pyrrhotite, as observed through XRD, SEM-EDS, and predicted by thermodynamic data, further supports the accelerant role of S, as pyrrhotite exhibits a higher hydrogen transfer potential, promoting early oil generation. These findings highlight the importance of pyrite in modulating hydrocarbon generation pathways in organic-rich systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaap.2025.107307","usgsCitation":"Adsul, T., Hackley, P.C., Hatcherian, J.J., McAleer, R.J., Green, C.J., Burnham, A.K., Ghosh, S., Werne, J.P., and Varma, A.K., 2025, Reaction kinetics and accelerant effects of sulfides in early mature hydrocarbon generation using hydrous pyrolysis: Journal of Analytical and Applied Pyrolysis, v. 192, 107307, https://doi.org/10.1016/j.jaap.2025.107307.","productDescription":"107307","ipdsId":"IP-176736","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"192","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adsul, Tushar","contributorId":330815,"corporation":false,"usgs":false,"family":"Adsul","given":"Tushar","email":"","affiliations":[{"id":79028,"text":"Indian Institute of Technology (Indian School of Mines), India","active":true,"usgs":false}],"preferred":false,"id":949842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":949844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":949845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, Carlin J. 0000-0002-6557-6268 cjgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6557-6268","contributorId":193013,"corporation":false,"usgs":true,"family":"Green","given":"Carlin","email":"cjgreen@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burnham, Alan K.","contributorId":362030,"corporation":false,"usgs":false,"family":"Burnham","given":"Alan","middleInitial":"K.","affiliations":[{"id":86422,"text":"Stratify//MH Chew Associates, 7633 Southfront Rd #170, Livermore, California 94551, USA","active":true,"usgs":false}],"preferred":false,"id":949847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ghosh, Santanu","contributorId":330824,"corporation":false,"usgs":false,"family":"Ghosh","given":"Santanu","email":"","affiliations":[{"id":79037,"text":"Mizoram University, India","active":true,"usgs":false}],"preferred":false,"id":949848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Werne, Josef P.","contributorId":362031,"corporation":false,"usgs":false,"family":"Werne","given":"Josef","middleInitial":"P.","affiliations":[{"id":86423,"text":"Organic and Stable Isotope Biogeochemistry Laboratory, Department of Geology and Environmental Science, University of Pittsburgh, 200 Space Research Coordination Center, 4107 O’Hara Street, Pittsburgh, PA 15260, USA","active":true,"usgs":false}],"preferred":false,"id":949849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Varma, Atul K.","contributorId":290219,"corporation":false,"usgs":false,"family":"Varma","given":"Atul","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":949850,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70269987,"text":"70269987 - 2025 - Climate and land use drivers of freshwater fish biodiversity in the northeastern United States","interactions":[],"lastModifiedDate":"2025-08-07T15:19:03.836084","indexId":"70269987","displayToPublicDate":"2025-07-28T10:10:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Climate and land use drivers of freshwater fish biodiversity in the northeastern United States","docAbstract":"Freshwater habitats can sustain high biodiversity, but habitat degradation, species invasion, and overexploitation have imperiled freshwater species. The multiple threats to freshwater habitats and changing stream characteristics due to climate change make it challenging to identify the drivers of fish vulnerability, especially given that the importance of drivers may vary by the biodiversity endpoint. The goals of this study were to 1) describe freshwater (lotic) fish biodiversity across northeastern states in the United States, and 2) identify geographic, climate, and land use drivers of fish biodiversity, toward improving freshwater fish conservation. We predicted habitat suitability for 53 fish species using survey data and corresponding geographic, climate, and land use data. After model fitting, we grouped species using a traditional approach based on traits and a new approach using modeled streamflow and stream temperature to create clusters. We found that climate and land use vulnerable groups did not always have similar geographic patterns or relationships to the climate or land use variables, suggesting that biota vulnerable to changing conditions may be overlooked by reliance on predefined guilds to set conservation goals. Biodiversity groups that were vulnerable to climate variables were also related to land use variables that can be used to identify restoration opportunities. This approach may be useful for managers interested in holistic freshwater management under changing stream conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.111337","usgsCitation":"Rogers, J.B., DiRenzo, G.V., Quiñones, R.M., Richards, T., and Roy, A.H., 2025, Climate and land use drivers of freshwater fish biodiversity in the northeastern United States: Biological Conservation, v. 310, 111337, 18 p., https://doi.org/10.1016/j.biocon.2025.111337.","productDescription":"111337, 18 p.","ipdsId":"IP-172448","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 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\"}}]}","volume":"310","noUsgsAuthors":false,"publicationDate":"2025-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Rogers, Jennifer B.","contributorId":359344,"corporation":false,"usgs":false,"family":"Rogers","given":"Jennifer","middleInitial":"B.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":945153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":945154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quiñones, Rebecca M.","contributorId":359345,"corporation":false,"usgs":false,"family":"Quiñones","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":16900,"text":"Massachusetts Division of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":945155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Todd","contributorId":359346,"corporation":false,"usgs":false,"family":"Richards","given":"Todd","affiliations":[{"id":16900,"text":"Massachusetts Division of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":945156,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":945157,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269752,"text":"70269752 - 2025 - The conundrum of taxonomic uniformitarianism in planktic foraminifera","interactions":[],"lastModifiedDate":"2025-07-31T14:23:30.840961","indexId":"70269752","displayToPublicDate":"2025-07-27T09:18:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2998,"text":"Palaeontology","active":true,"publicationSubtype":{"id":10}},"title":"The conundrum of taxonomic uniformitarianism in planktic foraminifera","docAbstract":"Planktic foraminiferal species distributions in the modern ocean track environmental features like sea surface temperature (SST). Species shift their distributions as the marine environment changes, providing an analogue for past behaviour. Stationarity of species' ecological tolerances is therefore a first-order assumption of all palaeoenvironmental reconstructions based upon modern analogue methods. In this paper we test the hypothesis that planktic foraminifer species temperature preferences did not change between the Late Pliocene and present, using a dataset which contains faunal abundance data and alkenone palaeotemperature data from the same samples. Our dataset includes 463 samples from 29 localities. Pliocene relative abundances of four taxa (Globigerina bulloides, Globigerinita glutinata, Neogloboquadrina pachyderma and Neogloboquadrina incompta) are compared to SST estimates of the same age derived using the alkenone unsaturation ratio (UK'37) palaeothermometer. Core-top abundances of the same taxa were compared to pre-industrial SST. Our Pliocene data are generally concordant with previous work. Pliocene SST responses and those of the pre-industrial are similar, supporting the hypothesis that temperature preferences of planktic foraminifera have been relatively stable since the Late Pliocene. This documentation of stationarity of planktic foraminiferal species' temperature tolerances is helpful in identifying situations where environmental variables other than temperature (e.g. salinity or productivity) exhibit a first-order control on faunal diversity. Our results support the notion of taxonomic uniformitarianism and therefore provide additional confidence in using planktic foraminifera to evaluate both regional and global climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/pala.70018","usgsCitation":"Dowsett, H., Robinson, M.M., Foley, K.M., and Spivey, W., 2025, The conundrum of taxonomic uniformitarianism in planktic foraminifera: Palaeontology, v. 68, no. 4, e70018, 10 p., https://doi.org/10.1111/pala.70018.","productDescription":"e70018, 10 p.","ipdsId":"IP-172361","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":493297,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/pala.70018","text":"Publisher Index Page"},{"id":493238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":261665,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":944564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":332062,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":944565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":944566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spivey, Whittney 0000-0003-1111-3361 wspivey@usgs.gov","orcid":"https://orcid.org/0000-0003-1111-3361","contributorId":214849,"corporation":false,"usgs":true,"family":"Spivey","given":"Whittney","email":"wspivey@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":944567,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270212,"text":"70270212 - 2025 - Real-time oil spill concentration assessment through fluorescence imaging and deep learning","interactions":[],"lastModifiedDate":"2025-08-18T15:29:16.381499","indexId":"70270212","displayToPublicDate":"2025-07-27T09:15:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2331,"text":"Journal of Hazardous Materials","active":true,"publicationSubtype":{"id":10}},"title":"Real-time oil spill concentration assessment through fluorescence imaging and deep learning","docAbstract":"Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2025.139374","usgsCitation":"Poudel, B., Xie, J., Guo, C., Watt, O., Pulster, E.L., Patel, R.J., Steevens, J.A., and Xu, D., 2025, Real-time oil spill concentration assessment through fluorescence imaging and deep learning: Journal of Hazardous Materials, v. 496, 139374, 10 p., https://doi.org/10.1016/j.jhazmat.2025.139374.","productDescription":"139374, 10 p.","ipdsId":"IP-177565","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":494021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"496","noUsgsAuthors":false,"publicationDate":"2025-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Poudel, Biplab","contributorId":359506,"corporation":false,"usgs":false,"family":"Poudel","given":"Biplab","affiliations":[{"id":39687,"text":"University of Missouri, Columbia","active":true,"usgs":false}],"preferred":false,"id":945730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xie, Jiacheng","contributorId":331598,"corporation":false,"usgs":false,"family":"Xie","given":"Jiacheng","email":"","affiliations":[],"preferred":false,"id":945731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guo, Congyu","contributorId":359509,"corporation":false,"usgs":false,"family":"Guo","given":"Congyu","affiliations":[{"id":39687,"text":"University of Missouri, Columbia","active":true,"usgs":false}],"preferred":false,"id":945732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watt, Olivia","contributorId":359518,"corporation":false,"usgs":false,"family":"Watt","given":"Olivia","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":945733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pulster, Erin L. 0000-0003-4574-8613","orcid":"https://orcid.org/0000-0003-4574-8613","contributorId":300266,"corporation":false,"usgs":true,"family":"Pulster","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":945734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Patel, Rishi J.","contributorId":359520,"corporation":false,"usgs":false,"family":"Patel","given":"Rishi","middleInitial":"J.","affiliations":[{"id":16806,"text":"Missouri State University","active":true,"usgs":false}],"preferred":false,"id":945735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":945736,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Xu, Dong","contributorId":305418,"corporation":false,"usgs":false,"family":"Xu","given":"Dong","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":945737,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269656,"text":"70269656 - 2025 - A spatial analysis of the groundwater emergence flood hazard in Long Island, New York and near coastal areas surrounding Long Island Sound in New York, Connecticut, and Rhode Island","interactions":[],"lastModifiedDate":"2025-08-01T14:53:14.313529","indexId":"70269656","displayToPublicDate":"2025-07-25T09:42:32","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"A spatial analysis of the groundwater emergence flood hazard in Long Island, New York and near coastal areas surrounding Long Island Sound in New York, Connecticut, and Rhode Island","docAbstract":"Long Island, New York and near coastal areas surrounding Long Island Sound are densely populated and, like other coastal areas, are susceptible to flooding from several potential sources, including stormwater from precipitation events, tidal flooding and storm surge, and groundwater inundation or groundwater emergence flooding. The latter refers to the intersection of a rising water table with land surface or critical infrastructure. Many studies of flood drivers either neglect or only briefly discuss how shallow groundwater conditions may contribute to or exacerbate flood conditions. As part of a comprehensive study of compound flood hazards in the near coastal areas surrounding Long Island and Long Island Sound, a spatial analysis was completed, in cooperation with the Environmental Protection Agency’s Long Island Sound Study, using available regional datasets to characterize the potential hazard for groundwater emergence flooding.
The approximately 3,100 square mile study area was subdivided into 11,407 900-meter by 900-meter (approximately 3,000-feet by 3,000-feet) grid cells, for the purposes of integrating the spatial datasets to calculate and map the groundwater emergence flood hazard. The depth to the water table, hydrologic soil groups, and National Land Cover Database were harmonized to the common grid. A groundwater emergence flood hazard rank was calculated for each grid cell for current average conditions following a set of rules accounting for the depth to the water table and the percent of area within each cell with slow infiltrating soils. A higher sea level position scenario was also calculated for the Long Island part of the study area. The calculated groundwater emergence flood hazard rank was reviewed in concert with the National Land Cover Data Base to identify developed areas and associated infrastructure that may be at risk to groundwater emergence flooding.
Study results indicate that the groundwater emergence flood hazard is highest in coastal areas and near surface water where the water table is close to ground surface. Inland areas away from surface water bodies are not likely to be exposed to groundwater emergence flooding. For Long Island, under a scenario with higher sea level position, a greater groundwater emergence flood hazard is calculated in some locations closer to the coast and where land is submerged. Away from the coast and surface-water drainage, the groundwater emergence flood hazard is similar between the current average sea level condition and a higher sea level position scenario.
Robust predictions of shoreline change are critical for sustainable coastal management. Despite advancements in shoreline models, objective benchmarking remains limited. Here we present results from ShoreShop2.0, an international collaborative benchmarking workshop, where 34 groups submitted shoreline change predictions in a blind competition. Subsets of shoreline observations at an undisclosed site (BeachX) over short (5-year) and medium (50-year) periods were withheld from modelers and used for model benchmarking. Using satellite-derived shoreline datasets for calibration and evaluation, the best performing models achieved prediction accuracies on the order of 10 m, comparable to the accuracy of the satellite shoreline data, indicating that certain beaches can be modelled nearly as well as they can be remotely observed. The outcomes from this collaborative benchmarking competition critically review the present state-of-the-art in shoreline change prediction as well as reveal model limitations, facilitate improvements, and offer insights for advancing shoreline-prediction capabilities.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-025-02550-4","usgsCitation":"Mao, Y., Coco, G., Vitousek, S., Antolinez, J.A., Azorakos, G., Banno, M., Bouvier, C., Bryan, K., Cagigal, L., Calcraft, K., Castelle, B., Chen, X., D'Anna, M., de Freitas Pereira, L., de Santiago, I., Deshmukh, A., Dong, B., Elghandour, A., Gohari, A., Gomez-de la Peña, E., Harley, M.D., Ibrahim, M., Idier, D., Jaramillo Cardona, C., Lim, C., Mingo, I., O'Grady, J., Pais, D., Repina, O., Robinet, A., Roelvink, D., Simmons, J., Sogut, E., Wilson, K., and Splinter, K., 2025, Benchmarking shoreline prediction models over multi-decadal timescales: Communications Earth & Environment, v. 6, 581, 15 p., https://doi.org/10.1038/s43247-025-02550-4.","productDescription":"581, 15 p.","ipdsId":"IP-176655","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":494452,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-025-02550-4","text":"Publisher Index Page"},{"id":494255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"New South Wales","otherGeospatial":"Curl Curl Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 151.28764961958893,\n -33.740052047115455\n ],\n [\n 151.28764961958893,\n -33.78320924309755\n ],\n [\n 151.33874708018328,\n -33.78320924309755\n ],\n [\n 151.33874708018328,\n -33.740052047115455\n ],\n [\n 151.28764961958893,\n -33.740052047115455\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2025-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Mao, Yongjing","contributorId":359742,"corporation":false,"usgs":false,"family":"Mao","given":"Yongjing","affiliations":[{"id":80179,"text":"UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":946204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coco, Giovanni","contributorId":359744,"corporation":false,"usgs":false,"family":"Coco","given":"Giovanni","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":946206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":946207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Antolinez, Jose A. 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reliable estimates of demographic parameters is critical to effective wildlife conservation and management. Densities of Mojave Desert Tortoises (Gopherus agassizii) were historically derived from capture–mark–recapture surveys on small, often strategically placed demography plots, or demographic study areas, that also provided information on demographic composition and vital rates. After protection was afforded to Desert Tortoises under the US Endangered Species Act in 1990, monitoring shifted mostly to line-distance sampling across broad areas for estimating densities of primarily adult tortoises to inform long-term population trends. However, that approach is incapable of providing data about other demographic characteristics important to population growth and viability. We surveyed a previously unsampled demography plot in the western Mojave Desert, California, USA, during 2022 and applied spatial capture–recapture (SCR) models to estimate spatially explicit Desert Tortoise density and sex-by-size class compositions. Directly accounting for spatiotemporally varying survey effort in SCR models via hazard-based adjustment reduced the estimated detection rate by 91% and increased the estimated density by 17%. Estimated spatial mean Desert Tortoise density across a 2.53-km2 area was 18.53 tortoises/km2 (95% confidence interval [CI] = 12.36–27.77). The SCR model–estimated size class ratio was skewed toward prereproductive tortoises (64% prereproductive; 36% adults), whereas the adult sex ratio was female biased (61% females; 39% males). Those ratios corresponded to densities of 11.86 prereproductive tortoises/km2 (95% CI = 7.91–17.77), 4.08 adult female tortoises/km2 (95% CI = 2.72–6.11), and 2.59 adult male tortoises/km2 (95% CI = 1.73–3.89). Estimated tortoise density and demographic composition collectively support a high potential for population growth. Our study provides an illustrative example of using SCR models to directly estimate spatially explicit local Desert Tortoise densities and demographic composition that can be used for long-term monitoring and comparisons with other demography plots to inform conservation.
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We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire.
Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.
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University of Colorado Boulder. Boulder CO 80309","active":true,"usgs":false}],"preferred":false,"id":955211,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Strauss, Jens","contributorId":223674,"corporation":false,"usgs":false,"family":"Strauss","given":"Jens","email":"","affiliations":[],"preferred":false,"id":955205,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Virkkala, Anna-Maria","contributorId":366040,"corporation":false,"usgs":false,"family":"Virkkala","given":"Anna-Maria","affiliations":[{"id":87336,"text":"Woodwell Climate Research Center, Falmouth, MA 02540 USA","active":true,"usgs":false}],"preferred":false,"id":955191,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Merritt R. Turetsky","contributorId":198334,"corporation":false,"usgs":false,"family":"Merritt R. Turetsky","affiliations":[],"preferred":false,"id":955190,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70269518,"text":"70269518 - 2025 - Ice thickness regulates heat flux in permanently ice-covered lakes","interactions":[],"lastModifiedDate":"2025-09-22T15:27:55.216752","indexId":"70269518","displayToPublicDate":"2025-07-24T08:37:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Ice thickness regulates heat flux in permanently ice-covered lakes","docAbstract":"The permanently ice-covered lakes of Taylor Valley, Antarctica, are rare ecosystems where permanent ice cover and year-round vertically stable water columns provide critical redox zones for cold-adapted microorganisms. Using 30 yr of limnological data from the McMurdo Dry Valleys Long-Term Ecological Research program, we assessed the water column heat flux of four permanently ice-covered lakes in the context of global lake ice decline and lake warming. Our study reveals that heat flux in Taylor Valley lakes is driven by ice cover dynamics, both annual changes in ice thickness as well as overall ice thickness. During periods of ice thinning, like those observed from 2020 to 2023, the lakes accumulate heat. Lake Fryxell, Lake Hoare, and West Lake Bonney have repeatedly cooled and warmed over our record, with only East Lake Bonney cooling due to lake level rise. Ice thickness is largely synchronous among the four lakes, with periods of asynchronicity likely caused by lake-specific changes in surface albedo driven by changes in optical properties of the ice covers and in-ice sediment dynamics.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.70151","usgsCitation":"Dugan, H.A., Obryk, M., Gooseff, M., Doran, P., Chiuchiolo, A., Lawrence, J., and Priscu, J., 2025, Ice thickness regulates heat flux in permanently ice-covered lakes: Limnology and Oceanography, v. 70, no. 9, p. 2556-2568, https://doi.org/10.1002/lno.70151.","productDescription":"13 p.","startPage":"2556","endPage":"2568","ipdsId":"IP-175276","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":499833,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/geo_pubs/2141","text":"External Repository"},{"id":492902,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Lake Bonney, Lake Fryxell, Lake Hoare, Taylor Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 162.2,\n -77.6\n ],\n [\n 162.2,\n -77.75\n ],\n [\n 163.25,\n -77.75\n ],\n [\n 163.25,\n -77.6\n ],\n [\n 162.2,\n -77.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dugan, Hilary A. 0000-0003-4674-1149","orcid":"https://orcid.org/0000-0003-4674-1149","contributorId":300341,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","email":"","middleInitial":"A.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":943935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":943936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gooseff, Michael","contributorId":358547,"corporation":false,"usgs":false,"family":"Gooseff","given":"Michael","affiliations":[{"id":85652,"text":"Institute of Arctic and Alpine Research, University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":943937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doran, Peter","contributorId":358548,"corporation":false,"usgs":false,"family":"Doran","given":"Peter","affiliations":[{"id":85654,"text":"Department of Geology and Geophysics, Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":943938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiuchiolo, Amy","contributorId":358549,"corporation":false,"usgs":false,"family":"Chiuchiolo","given":"Amy","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":943939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Jade","contributorId":358550,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jade","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":943940,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Priscu, John","contributorId":358551,"corporation":false,"usgs":false,"family":"Priscu","given":"John","affiliations":[{"id":85656,"text":"Division of Earth and Ecosystem Sciences, Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":943941,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269547,"text":"70269547 - 2025 - The pre-maria geologic history of the Imbrium basin preserved by remnant highlands massifs","interactions":[],"lastModifiedDate":"2025-07-25T13:37:32.725623","indexId":"70269547","displayToPublicDate":"2025-07-24T08:32:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9967,"text":"JGR Planets","active":true,"publicationSubtype":{"id":10}},"title":"The pre-maria geologic history of the Imbrium basin preserved by remnant highlands massifs","docAbstract":"The Imbrium basin is one of the largest and youngest impact basins on the Moon. It has experienced multiple phases of volcanism that filled the basin with basaltic lavas, obscuring most evidence of geologic activity prior to the emplacement of mare basalts. Elevated basin ring massifs, however, can retain some of that history due to their higher topographic elevation compared to the maria. In this work, we use thermal infrared and radar data sets in conjunction with compositional data sets to establish the presence of external material that has been deposited on top of several remnant basin massifs of Imbrium. These massifs originally formed as part of the Imbrium basin ring structure, but their material properties indicate that they have since experienced modification from outside sources. In southwest Imbrium, we present evidence that Mons Vinogradov was mantled by rock-poor, glassy pyroclastic material prior to the deposition of Eratosthenian-era basalts immediately surrounding the mons. In northern Imbrium, we find that Montes Recti and Montes Teneriffe were not affected by pyroclastic volcanism but rather were mantled by rock- and glass-poor ejecta materials likely related to the Iridum basin impact. At Mons Piton in eastern Imbrium, we see weaker glass signatures than those found at Mons Vinogradov, which we suggest could be due to a thin layer of reworked or partially buried glassy pyroclastic material. These results indicate that basin ring massifs provide a mechanism for studying the geologic history of lunar impact basins.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JE008646","usgsCitation":"Byron, B., Elder, C., Pigue, L.M., and Williams, J., 2025, The pre-maria geologic history of the Imbrium basin preserved by remnant highlands massifs: JGR Planets, v. 130, no. 7, e2024JE008646, 19 p., https://doi.org/10.1029/2024JE008646.","productDescription":"e2024JE008646, 19 p.","ipdsId":"IP-160135","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":492901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Imbrium basin, Moon","volume":"130","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Byron, Ben D. 0000-0003-4435-0347","orcid":"https://orcid.org/0000-0003-4435-0347","contributorId":358634,"corporation":false,"usgs":false,"family":"Byron","given":"Ben D.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":944013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine M. 0000-0002-9993-8861","orcid":"https://orcid.org/0000-0002-9993-8861","contributorId":358637,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine M.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":944014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pigue, Lori M. 0000-0002-6675-6877","orcid":"https://orcid.org/0000-0002-6675-6877","contributorId":330994,"corporation":false,"usgs":true,"family":"Pigue","given":"Lori","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":944015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Jean-Pierre","contributorId":358640,"corporation":false,"usgs":false,"family":"Williams","given":"Jean-Pierre","affiliations":[{"id":85660,"text":"Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":944016,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268977,"text":"sir20255027 - 2025 - Development of regression equations to estimate flow durations, low-flow frequencies, and mean flows at ungaged stream sites in Connecticut using data through water year 2022","interactions":[],"lastModifiedDate":"2026-02-03T14:32:36.443118","indexId":"sir20255027","displayToPublicDate":"2025-07-23T10:10:00","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":"2025-5027","displayTitle":"Development of Regression Equations to Estimate Flow Durations, Low-Flow Frequencies, and Mean Flows at Ungaged Stream Sites in Connecticut Using Data Through Water Year 2022","title":"Development of regression equations to estimate flow durations, low-flow frequencies, and mean flows at ungaged stream sites in Connecticut using data through water year 2022","docAbstract":"To aid Federal and State regulatory agencies in the effective management of water resources, the U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection and the Connecticut Department of Transportation, updated flow statistics for 118 streamgages and developed 47 regression equations to estimate selected flow duration, low flow, and mean flow statistics for the entire State of Connecticut, for the following: 1-, 5-, 10-, 25-, 50-, 75-, 90-, 99-percent flow durations; 7-day, 10-year low-flow frequency and 30-day, 2-year low-flow frequency; and mean flow, spring mean flow, and harmonic mean flow. In addition, regression equations were developed for monthly and seasonal flow durations, ranging from 25 to 99 percent for aquatic biological processes of salmonid spawning (November), overwinter (December–February), clupeid spawning (May), resident spawning (June), and rearing and growth (July–October) periods, and for flow durations ranging from 1 to 99 percent for the habitat forming (March–April) period. Statistics were derived from daily mean streamflow data collected from streamgages with at least 10 years of data through water year 2022 in southern New England and eastern New York.
Forty streamgages in Connecticut and adjacent areas of neighboring States were used in the regression analysis. Regression methods of weighted least squares and generalized least squares were used to derive the final coefficients and measures of uncertainty for the regression equations. The equations used to estimate selected streamflow statistics were developed by relating the flow statistics to different basin characteristics (physical, land cover, and climatic) at the 40 streamgages. Nine basin characteristics served as the explanatory variables in the statewide regression equations: drainage area, percentage of area with coarse-grained stratified deposits, stream density, mean basin slope, mean basin elevation, percentage of area with hydrologic soil group A, mean monthly precipitation for November, mean seasonal precipitation in the winter (December, January, and February), and mean annual temperature. The root mean square error of the 47 equations ranged from 7.9 to 121.9 percent, with an average of 27.9 percent. The equations estimate flows most accurately near the mean (50-percent flow duration), become less accurate for low flows, and are the least accurate for extreme low flows. The root mean square error for the 50-percent flow duration is 15.1 percent, with an average of 17.6 percent across the six periods. The extreme low flow statistics of 7-day, 10-year low-flow frequency, 99-percent flow duration, and 99-percent rearing and growth period flow durations have root mean square errors of 121.9, 105.1, and 121.9 percent, respectively. The adjusted coefficient of determination of the 47 equations ranged from 73.4 to 99.5 percent, with an average of 95.1 percent.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey, the Connecticut Department of Energy and Environmental Protection, and the Connecticut Department of Transportation collaboratively updated flow statistics for 118 streamgages and developed 47 regression equations to estimate key flow statistics in Connecticut. These included various flow durations and low-flow frequencies, as well as mean flow statistics for specific aquatic biological processes. The analysis used daily mean streamflow data from 40 streamgages with at least 10 years of data and incorporated basin characteristics such as drainage area and precipitation. The equations were most accurate near the mean flow (50-percent flow duration), with an average root mean square error of 27.9 percent, while accuracy decreased for low and extreme low flows. The adjusted coefficient of determination ranged from 73.4 to 99.5 percent, averaging 95.1 percent.
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","language":"English","publisher":"Wiley","doi":"10.1002/env.70027","usgsCitation":"Yao, K., McGahan, I.P., Zhu, J., Storm, D.J., Walsh, D.P., 2025, Animal trajectory imputation and uncertainty quantification via deep learning: Environmetrics, v. 36, no. 6, e70027, 15 p., https://doi.org/10.1002/env.70027.","productDescription":"e70027, 15 p.","ipdsId":"IP-172985","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500575,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/env.70027","text":"Publisher Index Page"},{"id":500342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Yao, Kehui","contributorId":339161,"corporation":false,"usgs":false,"family":"Yao","given":"Kehui","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":956327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGahan, Ian P.","contributorId":366857,"corporation":false,"usgs":false,"family":"McGahan","given":"Ian","middleInitial":"P.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":956328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Jun","contributorId":354695,"corporation":false,"usgs":false,"family":"Zhu","given":"Jun","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":956329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storm, Daniel J.","contributorId":366860,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel","middleInitial":"J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":956330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956331,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269402,"text":"cir1553 - 2025 - The 3D National Topography Model Call for Action—Part 2: The Next Generation 3D Elevation Program","interactions":[],"lastModifiedDate":"2026-02-03T14:31:31.794807","indexId":"cir1553","displayToPublicDate":"2025-07-23T09:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1553","displayTitle":"The 3D National Topography Model Call for Action—Part 2: The Next Generation 3D Elevation Program","title":"The 3D National Topography Model Call for Action—Part 2: The Next Generation 3D Elevation Program","docAbstract":"The three-dimensional (3D) National Topography Model initiative to integrate elevation and hydrography data includes the next generation of hydrography data from the 3D Hydrography Program and the next generation of elevation data from the 3D Elevation Program (3DEP). The first-ever collection of light detection and ranging (lidar) data for the nation (IfSAR for Alaska) provides a critical baseline reference, and the addition of multiple repeat elevation mapping projects as part of the next generation of 3DEP would substantially expand analysis capabilities. As the U.S. Geological Survey (USGS) is closing in on our goal of complete coverage with 3DEP data available or in progress for 98.3 percent of the Nation at the end of fiscal year 2024, the USGS is already transitioning to the next generation of 3DEP.
Based on the 3D Nation Study results and input from a broad range of stakeholders, the USGS National Geospatial Program has finalized a new design for 3DEP that provides increased lidar quality levels and refresh rates. The new program is designed with more flexibility to meet changing user needs and take advantage of improvements in mapping technologies. The program will aim to expand the level of interagency coordination for topobathymetric lidar acquisition for inland rivers. The next generation of 3DEP will also aim to emphasize research, including advancing program design, products, and services and engaging and leveraging the evolving 3D industry. Research goals also include becoming more flexible in meeting user needs and taking advantage of evolving remote-sensing technologies. The program also plans to move from focusing on producing standard products to producing a concept of a 3D Nation Ecosystem with a variety of inputs, products, and services.
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U.S. Geological Survey
Mail Stop 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Humpback Chub (HBC) Gila cypha in Grand Canyon declined in abundance and distribution over the latter part of the 20th century but have substantially increased in abundance and distribution over the past two decades. Although previous genetic work suggested that HBC in Grand Canyon belong to one genetic group, here we evaluate the genetic structure of HBC in Grand Canyon to determine whether relic populations in western Grand Canyon may have contributed unique variation to the recent population expansion or whether differences in behavior linked to migration in eastern Grand Canyon may promote assortative mating and heretofore unrecognized population structure.
Using fin clips collected from 167 individual HBC representing four sampling sites within Grand Canyon, we extracted DNA and developed data sets consisting of approximately 20,000 anonymous genomic loci. We quantified patterns of genetic diversity, and we accounted for outlier single-nucleotide polymorphisms to ensure that our interpretations of genetic patterns were not misled by adaptive processes and did not mask adaptively important genetic variation.
Despite behavioral variation and the possibility that individuals with unique genetic variation survived in isolated warmwater sites within western Grand Canyon, HBC were not differentiated by sampling site or by differences in migratory behavior. Heterozygosity and nucleotide diversity were consistently high among sampling sites, and inbreeding coefficients were close to zero.
The HBC in Grand Canyon constitute a single genetic population. Our results do not preclude a genetic basis to migratory behavior, but our data suggest that this trait does not lead to assortative mating. Furthermore, while HBC may have survived in discontiguous warmwater refugia in western Grand Canyon during decades when the main stem was too cold for spawning, our data did not reveal any noticeable spatial variability in HBC genetics in the main stem after the recent HBC population expansion.
The three North American Rosy-Finch species (Brown-capped [Leucosticte australis], Black [L. atrata], and Gray-crowned [L. tephrocotis]) are among the most climate-threatened species in the United States. New Mexico is an important location for investigating the effects of climate change because it is the southernmost location in which Brown-capped Rosy-Finches breed and the southernmost location where all three Rosy-Finch species co-occur during winter. In the context of climate change, this range boundary is important to study because it is the first part of the range anticipated to cross a threshold of unsuitability for these species with increasing temperatures. Rosy-Finches are difficult to study during the breeding season due to the high elevation and remoteness of their breeding grounds; therefore, winter studies may lend insight into population trends and provide direction for conservation actions based on knowledge of the breeding origins of wintering birds. The goals of our study were to investigate long-term survival and migration trends from wintering Brown-capped Rosy-Finches in New Mexico and evaluate the efficacy of radio frequency identification (RFID)-equipped artificial feeders to monitor population trends. As of May 2025, we have conducted a robust design survival analysis on 22 years of mark-recapture data from a particular wintering site in New Mexico, assessed patterns in the breeding origins of individuals captured at this site using stable isotope analysis, and examined patterns in data collected via RFID. Our main findings from this study are that annual survival probability of Rosy-Finches wintering in New Mexico is low compared to that of other migratory passerines, that Brown-capped Rosy-Finches wintering in New Mexico likely originate from a variety of locations across their breeding range, and that RFID monitoring is useful in improving survival estimates in Rosy-Finches, particularly in short-term studies.
","language":"English","publisher":"New Mexico Department of Game and Fish Share with Wildlife Program","usgsCitation":"Watson, W.A., Borgman, C.C., Cox, S., and Lawson, A.J., 2025, Inferring Brown-Capped Rosy-Finch demography and breeding distribution trends from long-term wintering data in New Mexico: Final Report, 31 p.","productDescription":"31 p.","ipdsId":"IP-179262","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":495001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":494873,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.dgf.nm.gov/download/new-mexico-state-university-las-cruces-inferring-brown-capped-rosy-finch-demography-and-breeding-distribution-trends-from-long-term-wintering-data-in-new-mexico-final-report/"}],"country":"United States","state":"New 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Inc.","active":true,"usgs":false}],"preferred":false,"id":947206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":947207,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269399,"text":"sir20255044 - 2025 - Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia","interactions":[],"lastModifiedDate":"2026-02-03T14:29:52.898888","indexId":"sir20255044","displayToPublicDate":"2025-07-21T15:10:00","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":"2025-5044","displayTitle":"Factors Affecting the Distribution of Water-Bearing Fractures in the Bedrock Aquifers of West Virginia","title":"Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia","docAbstract":"Bedrock aquifers cover 23,601 square miles within the State of West Virginia and comprise 97.4 percent of the surficial area within the State; the remaining 2.6 percent (621 square miles) consists of alluvial sand-and-gravel and glacial outwash aquifers bordering the State’s major rivers. While West Virginia’s alluvial aquifers have been studied extensively, bedrock aquifers have only been characterized for studies completed in a few areas in Jefferson, McDowell, and Monroe Counties. Bedrock aquifers are water supplies for public supply, agriculture, industry, and residential homeowner use. In this study, the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management, provides a statewide assessment of the occurrence and distribution of fractures within bedrock aquifers of the State and the various topographic, physiographic, and lithologic influences controlling the occurrence and distribution of bedrock fractures. The results of this study provide an increased understanding of the distribution of fractures in bedrock aquifers in West Virginia and help to verify trends that have been suspected for many years but were never well documented or verified by data.
The results confirmed that the density of fractures and those that were determined to be water bearing decrease significantly with depth. A statistically significant difference in the density of fractures was observed at a depth of 215 feet for wells in the Appalachian Plateaus Physiographic Province’s and in the Valley and Ridge Physiographic Province’s aquifers; a higher density of fractures and water-bearing fractures were above a depth of 215 feet than below that depth. This is an important consideration when drilling wells for residential, commercial, industrial, or agricultural water supply.
Abandoned underground coal mines are commonly believed to form large pools of water in the interconnected mine entries in abandoned room and pillar coal mines. Such pools of water can and do exist in abandoned underground coal mines, but many mines lack open entries and are held up by overburden strata and pillars that can collapse and form aquifers comprised of vast interconnected rubble zones (gob), especially in older mines.
Data assessed for this study showed that shale-corrected values of effective porosity for limestone aquifers in West Virginia had a median value of 2 percent and an average value of 4 percent and generally are mineralized with low effective porosity. Argillaceous or sandy limestone has a median shale-corrected porosity of 4 percent and an average shale-corrected porosity of 5 percent. The median and average shale-corrected porosity of sandstone aquifers was estimated to be 14 percent, but the median shale-corrected porosity for argillaceous or calcareous sandstone was 5 percent and the average shale-corrected porosity for argillaceous or calcareous sandstone was 6 percent. Even though shale has a relatively high total sonic porosity compared to other lithologies, shale and siltstone had relatively low shale-corrected porosity, ranging from 0 to 2 percent.
Well yields were previously documented to be highest in valley settings, lowest on hilltops, and intermediate on hillsides. Transmissivity data provided by this study confirm this general pattern within the Appalachian Plateaus Province; however, the Valley and Ridge Province does not follow this pattern. While still lowest on hilltop settings, the highest well yields were in hillside settings. The trend for the Valley and Ridge Province was likely skewed because of 9 high-yield wells specifically targeting deeper thin limestone units, such as the Tonoloway and Helderberg Limestones, at depths with transmissivity in excess of 2,000 feet squared per day in Mineral County, West Virginia, or targeting karst aquifers in Berkeley, Jefferson, or Greenbrier Counties, West Virginia.
Finally, water-bearing fractures have been hypothesized to comprise a small number of all fractures within a typical bedrock well in West Virginia. Data collected for this study support this theory. A total of 3,403 fractures were identified during this study; 3,151 (92.6 percent) of those fractures are low-transmissive, and only 252 (7.4 percent) fractures are water-bearing. Even though a well may contain many fractures, less than 8 percent are considered water-bearing fractures.
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Virginia\",\"nation\":\"USA \"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Healthy stream networks rely on diverse fish assemblages and the mobility of fish between habitats to maintain ecosystem structure and function. Anthropogenic structures that impede fish movement (e.g., roads, dams) disrupt life cycles of migratory fishes and isolate fish populations making them more sensitive to environmental stressors. Growing interest in barrier removal is driven by the recognition that restoring fish passage improves ecosystem health and resilience at multiple trophic levels, but identifying which streams should be reconnected and which barriers to remove remains an unresolved issue. Using the state of Missouri (USA) stream network, we developed an interactive decision support tool designed to help natural resource managers identify a shortlist of stream reaches to prioritize for reconnection, barrier removal, and habitat restoration. Our aquatic connectivity decision support tool, which we call AquaConn, is aimed at managers seeking to improve connectivity within and between existing conservation areas, particularly in wadeable streams. AquaConn provides a flexible platform that allows managers to consider entire assemblages of fish or individual species across local or more regional spatial scales. While AquaConn (https://bit.ly/4kQgXK8) was built for the state of Missouri, our approach and framework can be replicated in any geographical region that has adequate fish assemblage data.
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\"}}]}","volume":"50","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Winikoff, Sarah G.","contributorId":360333,"corporation":false,"usgs":false,"family":"Winikoff","given":"Sarah","middleInitial":"G.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":946979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":268045,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sievert, Nicholas","contributorId":272500,"corporation":false,"usgs":false,"family":"Sievert","given":"Nicholas","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":946981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274005,"text":"70274005 - 2025 - Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","interactions":[],"lastModifiedDate":"2026-02-20T16:11:51.850785","indexId":"70274005","displayToPublicDate":"2025-07-21T10:05:49","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":"Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","docAbstract":"Knowledge of animal-movement patterns is a crucial component in identifying areas with high potential for human–wildlife conflict and in prioritizing associated management actions. Electrical energy infrastructure is a major source of mortality for animals worldwide, with millions of birds colliding with or being electrocuted by power lines and power-pole infrastructure each year. Movement, habitat use, and the spatial distribution of electrocution risk can vary with age, but studies of younger age classes are often hampered because these groups are difficult to observe and lack well-defined home ranges. To identify movement patterns and high-use areas of bald eagles in Arizona, USA, we analyzed global positioning system (GPS) telemetry data collected from 13 immature bald eagles (Haliaeetus leucocephalus) across Arizona between 2017 and 2023. We built multi-scale, integrated step-selection functions that evaluated eagle responses to a suite of environmental covariates. We then used these models to simulate eagle movement and predict habitat use within and surrounding Maricopa County, which contains both the Phoenix Metropolitan Area and the plurality of bald eagle breeding areas in Arizona. We provide a use case for how these simulated movements could be used by resource managers to identify high-risk areas for electrocution. Eagles avoided urban areas and selected steeper slopes, more pronounced ridges, and areas with greater water and wetland land cover. Predicted habitat use by bald eagles was greatest near waterbodies and along ridges and steep slopes, and indicated where power infrastructure may pose greater electrocution risk. We show how integrated step-selection analyses and movement path simulation may be used for subadult animals lacking stable home ranges to predict high-use areas and identify locations with greater potential for negative human–wildlife interactions.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70061","usgsCitation":"Cappello, C. ., Jacobson, K.V., Driscoll, J.T., McCarty, K.M., Bauder, J.M., 2025, Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species: Journal of Wildlife Management, v. 89, no. 7, e70061, 19 p., https://doi.org/10.1002/jwmg.70061.","productDescription":"e70061, 19 p.","ipdsId":"IP-178672","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.5,\n 34.1\n ],\n [\n -113.5,\n 32.5\n ],\n [\n -111,\n 32.5\n ],\n [\n -111,\n 34.1\n ],\n [\n -113.5,\n 34.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Cappello, Caroline D.","contributorId":366625,"corporation":false,"usgs":false,"family":"Cappello","given":"Caroline","middleInitial":" D.","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":956103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Kenneth V.","contributorId":366626,"corporation":false,"usgs":false,"family":"Jacobson","given":"Kenneth","middleInitial":"V.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, James T.","contributorId":366627,"corporation":false,"usgs":false,"family":"Driscoll","given":"James","middleInitial":"T.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Kyle M.","contributorId":366629,"corporation":false,"usgs":false,"family":"McCarty","given":"Kyle","middleInitial":"M.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269455,"text":"70269455 - 2025 - A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","interactions":[],"lastModifiedDate":"2025-07-23T14:18:18.596644","indexId":"70269455","displayToPublicDate":"2025-07-19T09:12:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","docAbstract":"Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub-watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5-m stream sub-reach across 426 sub-watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub-watersheds that contained training data and decreased to 0.67 for sub-watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040478","usgsCitation":"Burnett, J., Jaeger, K.L., Johnson, S.L., Wondzell, S., Dunham, J., Barker, M., Heaston, E.D., Chelgren, N., Wing, M., Staab, B., and Brown, M., 2025, A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation: Water Resources Research, v. 61, no. 7, e2025WR040478, 29 p., https://doi.org/10.1029/2025WR040478.","productDescription":"e2025WR040478, 29 p.","ipdsId":"IP-166720","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040478","text":"Publisher Index 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Lock and Dam","docAbstract":"The management of invasive Silver Carp Hypophthalmichthys molitrix in the Tennessee River basin focuses on removal, and there is interest in extending removal efforts to the tailwater environments of high-head locks and dams along the Tennessee River, such as Kentucky Dam. We used acoustic telemetry data from Silver Carp to understand important ecological associations underlying their residence in the Kentucky Dam tailwater, measured by daily fish counts and mean residence time.
We used time-series-informed regression models, variance partitioning, and cross-correlation function analysis to associate six predictors, including lock and dam operations (total, spill gate, and turbine discharge and number of lockages), hydrology (tailwater elevation), and water temperature, with two measures of Silver Carp residency (daily counts and mean residence time).
We found that spill-induced hydrology (total discharge + spill discharge + tailwater elevation) was negatively associated with daily counts but not with residence time, whereas temperature was positively associated with counts and negatively associated with residence times. Variance partitioning indicated that nearly all the variance in counts and residence times was jointly explained by temporal effects, lock and dam operations (discharge, tailwater elevation, and lockages), and temperature. The cross-correlations indicated that the counts were lagged by all predictors, sometimes up to 5 d, whereas residence times were lagged by both total and spill discharge and number of lockages.
We found that discharge and water temperature were principally associated with residency of Silver Carp in the Kentucky Dam tailwater. However, these associations were entirely temporally constrained, which can affect how strongly and how quickly Silver Carp respond to changing environmental conditions across different time scales. Managers can leverage these associations to plan removal periods where daily tailwater conditions/dam operations are favorable to invasive carp residence (e.g., >10°C and <2,500 m3/s) and adjust fishing effort to optimize removal rates in response to changing conditions.
DDiel activity rhythms, representing the behavioral pattern of the sleep–wake cycle, may be adjusted by wildlife in response to changes in environmental conditions. An increase in nocturnality is typically recognized as an adaptive strategy to segregate from humans and mitigate heat stress. Numerous studies have investigated spatial patterns and habitat use of large carnivores in human-modified landscapes, but little research has examined their activity rhythms. We compiled Global Positioning System data (2004–2022) for 139 brown bears Ursus arctos from six populations across Europe, representing a human-modified landscape, and the Greater Yellowstone Ecosystem, U.S.A., representing a landscape with limited human impact, which we used to calculate hourly movement rates as an activity proxy. Using a Bayesian approach to model the temporal autocorrelation of activity data, we tested if the extent of nocturnality in brown bears is modulated by intensity of human encroachment, accounting for primary productivity and maximum ambient temperature. All bear populations exhibited a predominantly bimodal, crepuscular pattern of activity, although Yellowstone bears were proportionally more crepuscular and diurnal. Whereas the effect of primary productivity was variable, all European populations became more nocturnal in response to higher human encroachment and reduced diurnal and crepuscular activity at higher summer temperatures, decreasing overall diel activity levels. Yellowstone bears displayed the greatest shift towards nocturnality among all populations in response to increasing human encroachment, and increased nocturnal activity to compensate for lower diurnal and crepuscular activity at higher summer temperatures. Our research indicates that European bears in human-modified landscapes may be reaching a limit in the behavioral plasticity they can manifest in their activity patterns, being already constrained into increased nocturnality. Our findings enhance the understanding of brown bear adaptive capacity to accommodate future changes, such as urbanization and increasing temperatures, to the ecosystems they inhabit.
","language":"English","publisher":"Wiley","doi":"10.1002/ecog.07979","usgsCitation":"Donatelli, A., Ćirović, D., Haroldson, M.A., Huber, Đ., Kindberg, J., Kojola, I., Kusak, J., Mastrantonio, G., Ordiz, A., Reljić, S., Santini, L., van Manen, F.T., and Ciucci, P., 2025, The diel niche of brown bears: Constraints on adaptive capacity in human-modified landscapes: Ecography, v. 2025, no. 10, e07979, 15 p., https://doi.org/10.1002/ecog.07979.","productDescription":"e07979, 15 p.","ipdsId":"IP-174846","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":493787,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecog.07979","text":"Publisher Index Page"},{"id":492607,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Croatia, Finland, Italy, Russia, Serbia, Sweden, United States","geographicExtents":"{\n \"type\": 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