Freshwater mussels are critical to the health of freshwater systems, but their populations are declining dramatically throughout the world. The limited resources available for freshwater mussel conservation necessitates the geographic prioritization of conservation-related actions. However, lack of knowledge about freshwater mussel spatial distributions hinders decision making in this context. In this study, we assessed the distribution of twelve native freshwater mussel species across six Northeastern states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine) in the United States using data collected from lentic and lotic environments by eight state agencies. We first modeled individual distributions using a maximum entropy (MaxEnt) model and then compiled distribution models to assess the distribution of freshwater mussel species richness. We also determined geographic prioritization for three conservation-related actions: species surveys, land protection, and population restoration of species of high conservation concern. We found that the percent of catchments predicted to have species occurrence (based on a probability threshold) varied across species, with Elliptio complanata (Eastern elliptio) predicted to occur in the greatest percent of available catchments (33.92%) and Alasmidonta heterodon (Dwarf wedgemussel) expected in the smallest percent (5.30%). The predicted overall species richness within our modeled catchments ranged from zero to all twelve species, with an average of two species per catchment. Although conservation priorities vary depending on the conservation action of interest, we found some areas of consistent importance including much of Maine and the southern reaches of the Connecticut River. An improved understanding of freshwater mussel distribution in a landscape framework will enable managers to implement more precise and efficient conservation interventions for these essential aquatic species.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0324387","usgsCitation":"O’Brien, R.S., DiRenzo, G.V., Roy, A.H., Carmignani, J., Quinones, R.M., Rogers, J.B., and Swartz, B.I., 2025, Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling: PLoS ONE, v. 20, no. 9, e0324387, 20 p., https://doi.org/10.1371/journal.pone.0324387.","productDescription":"e0324387, 20 p.","ipdsId":"IP-175157","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497699,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0324387","text":"Publisher Index Page"},{"id":497466,"rank":1,"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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zone","interactions":[],"lastModifiedDate":"2025-11-20T16:23:06.555018","indexId":"70272284","displayToPublicDate":"2025-09-08T09:17:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone","docAbstract":"Temporal patterns in chemistry of headwater streams reflect responses of water and elemental cycles to perturbations occurring at local to global scales. We evaluated multi-scale temporal patterns in up to 32 y of monthly observations of stream chemistry (ammonium, calcium, dissolved organic carbon, nitrate, total dissolved phosphorus, and sulfate) in 22 reference catchments within the northern temperate zone of North America. Multivariate autoregressive state-space (MARSS) models were applied to quantify patterns at multi-decadal, seasonal, and shorter intervals during a period that encompassed warming climate, seasonal changes in precipitation, and regional declines in atmospheric deposition. Significant long-term trends in solute concentrations within a subset of the catchments were consistent with recovery from atmospheric deposition (e.g., calcium, nitrate, sulfate) and increased precipitation (e.g., dissolved organic carbon). Lack of evidence for multi-decadal trends in most catchments suggests resilience of northern temperate ecosystems or that subtle net effects of simultaneous changes in climate and disturbance regimes do not result in directional trends. Synchronous seasonal oscillations of solute concentrations occurred across many catchments, reflecting shared climate and biotic drivers of seasonality within the northern temperate zone. Despite shared patterns among catchments at a seasonal scale, multi-scale temporal patterns were statistically distinct among even adjacent headwater catchments, implying that local attributes of headwater catchments modify the signals imparted by atmospheric phenomena and regional disturbances. To effectively characterize hydrologic and biogeochemical responses to changing climate and disturbance regimes, catchment monitoring programs could include multiple streams with contributing areas that encompass regional heterogeneity in vegetation, topography, and elevation. Overall, detection of long-term patterns and trends requires monitoring multiple catchments at a frequency that captures periodic variation (e.g., seasonality) and a duration encompassing the perturbations of interest.
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Leveraging recent advances in image-based particle tracking, we conducted wind tunnel experiments using high-speed imaging and Particle Tracking Velocimetry to quantify sand grain trajectories in saturated saltation clouds over both flat and rippled beds. Our open-source PTV workflow resolved particle motions within millimeters of the bed across a range of wind speeds. Supporting previous results, we find that mean particle velocities do not scale linearly with wind speed; instead, changes in particle velocity distributions—including skewness and kurtosis—emerge as wind strength and sediment flux increase. At higher transport rates, distinctions among saltation, reptation, and creep within the particle distribution become more smoothed, suggesting a continuum spectrum of particle behavior rather than discrete transport modes. Our new dataset of particle trajectories over an active rippled bed shows distinctions in particle speed across the aspects. On ripple stoss slopes, fast saltating grains co-occur with slow creeping particles, while lee slopes are depleted of slower grains, consistent with shadowing effects. These observations support a feedback between ripple morphology and near-bed particle trajectories, with implications for how splash events redistribute sediment momentum. This study contributes new high-resolution empirical data that illuminate how saltation cloud structure evolves with wind forcing and bedform development, advancing our understanding of aeolian sediment transport under complex, dynamic conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2025.100996","usgsCitation":"Kelley, M., Walker, I.J., Schmeeckle, M.W., Swann, C., Dorn, R., Roberts, M., and O'Brien, P., 2025, Changes in aeolian saltation cloud properties with wind speed and ripples: Aeolian Research, v. 74, 100996, 16 p., https://doi.org/10.1016/j.aeolia.2025.100996.","productDescription":"100996, 16 p.","ipdsId":"IP-171990","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Madeline Margaret 0009-0003-6406-2307","orcid":"https://orcid.org/0009-0003-6406-2307","contributorId":353253,"corporation":false,"usgs":true,"family":"Kelley","given":"Madeline Margaret","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Ian J. 0000-0001-5719-5310","orcid":"https://orcid.org/0000-0001-5719-5310","contributorId":361056,"corporation":false,"usgs":false,"family":"Walker","given":"Ian","middleInitial":"J.","affiliations":[{"id":86173,"text":"Department of Geography, UC Santa Barbara, Santa Barbara, CA 93106-4060, USA","active":true,"usgs":false}],"preferred":false,"id":948200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmeeckle, Mark W.","contributorId":178432,"corporation":false,"usgs":false,"family":"Schmeeckle","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":948201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swann, Christy","contributorId":258305,"corporation":false,"usgs":false,"family":"Swann","given":"Christy","email":"","affiliations":[{"id":40754,"text":"Naval Research Lab","active":true,"usgs":false}],"preferred":false,"id":948202,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dorn, Ron 0000-0003-1343-4556","orcid":"https://orcid.org/0000-0003-1343-4556","contributorId":361057,"corporation":false,"usgs":false,"family":"Dorn","given":"Ron","affiliations":[{"id":86175,"text":"School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, U.S.A","active":true,"usgs":false}],"preferred":false,"id":948203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, Michaela","contributorId":361058,"corporation":false,"usgs":false,"family":"Roberts","given":"Michaela","affiliations":[{"id":86175,"text":"School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, U.S.A","active":true,"usgs":false}],"preferred":false,"id":948204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Brien, Patrick 0000-0002-8956-2741","orcid":"https://orcid.org/0000-0002-8956-2741","contributorId":361059,"corporation":false,"usgs":false,"family":"O'Brien","given":"Patrick","affiliations":[{"id":86177,"text":"School of the Environment, Trent University, Peterborough, ON, K9L 0G2, Canada","active":true,"usgs":false}],"preferred":false,"id":948205,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274105,"text":"70274105 - 2025 - Impacts of onshore wind energy production on biodiversity","interactions":[],"lastModifiedDate":"2026-02-25T15:11:33.524949","indexId":"70274105","displayToPublicDate":"2025-09-08T08:04:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23309,"text":"Nature Biodiversity Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of onshore wind energy production on biodiversity","docAbstract":"Wind is increasingly used as a renewable source of energy worldwide. However, harvesting wind energy can have negative consequences for biodiversity. In this Review, we summarize the growth of onshore wind power, its impacts on species and ecosystems, and how those impacts are assessed and mitigated. Across the construction, operation and decommissioning stages, wind facilities are associated with wildlife fatality and behavioural change as well as alteration, loss and fragmentation of terrestrial and aerial habitat. These negative consequences can be mitigated by avoiding construction of wind turbines at sensitive sites, detecting and deterring wildlife, curtailing turbines to reduce fatalities, and replacing lost habitats. Uncertainty about wildlife populations and their demographic parameters, the rate and extent of build-out of onshore wind energy, and best practices for mitigation, as well as variability in regulatory requirements by country or region, all contribute to the difficulty of predicting the consequences of this technology for biodiversity. Scenario-based modelling that incorporates population- and community-level consequences to biodiversity from varying degrees of wind energy development — including the cumulative effects of multiple facilities — is key to addressing this uncertainty.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s44358-025-00078-1","usgsCitation":"Katzner, T., Nelson, D.M., Marques, A.T., Voigt, C.C., Lambertucci, S.A., Rebolo, N., Bernard, E., Diehl, R.H., Murgatroyd, M., 2025, Impacts of onshore wind energy production on biodiversity: Nature Biodiversity Reviews, no. 1, p. 567-580, https://doi.org/10.1038/s44358-025-00078-1.","productDescription":"14 p.","startPage":"567","endPage":"580","ipdsId":"IP-174500","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"1","noUsgsAuthors":false,"publicationDate":"2025-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":956551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":956552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marques, Ana Teresa","contributorId":366998,"corporation":false,"usgs":false,"family":"Marques","given":"Ana","middleInitial":"Teresa","affiliations":[{"id":87526,"text":"Campus de Vairão, Portugal","active":true,"usgs":false}],"preferred":false,"id":956553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voigt, Christian C.","contributorId":366999,"corporation":false,"usgs":false,"family":"Voigt","given":"Christian","middleInitial":"C.","affiliations":[{"id":87527,"text":"Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":956554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lambertucci, Sergio A","contributorId":292399,"corporation":false,"usgs":false,"family":"Lambertucci","given":"Sergio","email":"","middleInitial":"A","affiliations":[{"id":62895,"text":"National Scientific and Technical Research Council","active":true,"usgs":false}],"preferred":false,"id":956555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rebolo, Natalia","contributorId":367000,"corporation":false,"usgs":false,"family":"Rebolo","given":"Natalia","affiliations":[{"id":87528,"text":"INIBIOMA Universidad Nacional del Comahue—CONICET, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":956556,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bernard, Enrico","contributorId":367001,"corporation":false,"usgs":false,"family":"Bernard","given":"Enrico","affiliations":[{"id":87528,"text":"INIBIOMA Universidad Nacional del Comahue—CONICET, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":956557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":956558,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murgatroyd, Megan","contributorId":367002,"corporation":false,"usgs":false,"family":"Murgatroyd","given":"Megan","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":956559,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70271463,"text":"70271463 - 2025 - Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","interactions":[],"lastModifiedDate":"2025-09-17T14:00:53.292778","indexId":"70271463","displayToPublicDate":"2025-09-08T07:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","docAbstract":"The Miocene provides an excellent climatic analogue for near-future runaway anthropogenic warming, with atmospheric CO2 concentrations and global average temperatures similar to those projected for the coming century under extreme-emissions scenarios. However, the magnitude of Miocene Arctic warming remains unclear due to the scarcity of reliable proxy data. Here we use stable oxygen isotope and trace element analyses, alongside clumped isotope and fluid inclusion palaeothermometry of speleothems to reconstruct palaeo-environmental conditions near the Siberian Arctic coast during the Tortonian (8.68 ± 0.09 Ma). Stable oxygen isotope records suggest warmer-than-present temperatures. This is supported by temperature estimates based on clumped isotopes and fluid inclusions giving mean annual air temperatures between +6.6 and +11.1 °C, compared with −12.3 °C today. Trace elements records reveal a highly seasonal hydrological environment.
Our estimate of > 18 °C of Arctic warming supports the wider consensus of a warmer-than-present Miocene and provides a rare palaeo-analogue for future Arctic amplification under high-emissions scenarios. The reconstructed increase in mean surface temperature far exceeds temperatures projected in fully coupled global climate models, even under extreme-emissions scenarios. Given that climate models have consistently underestimated the extent of recent Arctic amplification, our proxy data suggest Arctic warming may exceed current projections.
An unknown occurrence of oil was detected near Avak Creek on Native lands on the North Slope of Alaska. Determining the source of oil was imperative for allowing stakeholders (Federal, State, and local government agencies and the landowner, an Alaska Native corporation) to make timely and informed decisions and mount a mitigation response, if required. The regional and local geological framework of the Avak Creek site was constructed using seismic surveys, well data, and basin modeling results, to identify local petroleum systems, map structural geometry and faults, define source rock thermal maturity distributions, and infer likely oil-migration pathways. Molecular hydrocarbon fingerprints (biomarkers, diamondoids, compound-specific isotopes) of the oil were compared to those of local and regional oil seeps, exploration well tests, and produced oils. Biomarker acid distributions characterized the history and extent of petroleum biodegradation. Integrating subsurface and geochemical parameters, the oil is interpreted to be a natural seep generated locally, predominantly from the Brookian Lower Cretaceous Hue Shale/gamma-ray zone, rather than an anthropogenic source of pollution. Results highlight sophisticated analytical technologies used to characterize complex, compositionally altered hydrocarbons. Results also advance our understanding of Brookian source rock distribution, subsurface petroleum migration pathways, and Arctic Alaska petroleum systems.
","conferenceTitle":"32nd International Meeting on Organic Geochemistry (IMOG) 2025","conferenceDate":"September 7-11, 2025","conferenceLocation":"Porto, Portugal","language":"English","publisher":"European Association of Geoscientists & Engineers","doi":"10.3997/2214-4609.202533156","usgsCitation":"Botterell, P.J., Houseknecht, D.W., Wycech, J.B., Moldowan, J.M., Lillis, P.G., Smith, R.A., and Maher, K., 2025, Avak Creek oil occurrence, North Slope, Alaska: Newly discovered oil seep on Native lands, near village of Utqiagvik, 32nd International Meeting on Organic Geochemistry (IMOG) 2025, v. 2025, Porto, Portugal, September 7-11, 2025, 2 p., https://doi.org/10.3997/2214-4609.202533156.","productDescription":"2 p.","ipdsId":"IP-175494","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":495630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495609,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.earthdoc.org/content/papers/10.3997/2214-4609.202533156","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","city":"Utqiagvik","volume":"2025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, David W 0000-0002-9633-6910","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":361485,"corporation":false,"usgs":false,"family":"Houseknecht","given":"David","middleInitial":"W","affiliations":[{"id":86299,"text":"USGS Geology, Energy & Minerals Science Center (RET)","active":true,"usgs":false}],"preferred":false,"id":948886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wycech, Jody Brae 0000-0002-7073-3037","orcid":"https://orcid.org/0000-0002-7073-3037","contributorId":303104,"corporation":false,"usgs":true,"family":"Wycech","given":"Jody","email":"","middleInitial":"Brae","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moldowan, J. Mike","contributorId":361486,"corporation":false,"usgs":false,"family":"Moldowan","given":"J.","middleInitial":"Mike","affiliations":[{"id":50465,"text":"Biomarker Technologies, Inc.","active":true,"usgs":false}],"preferred":false,"id":948888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948889,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Rebecca A. 0000-0002-9823-706X rsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9823-706X","contributorId":201349,"corporation":false,"usgs":true,"family":"Smith","given":"Rebecca","email":"rsmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948890,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Kimberley","contributorId":361487,"corporation":false,"usgs":false,"family":"Maher","given":"Kimberley","affiliations":[{"id":86300,"text":"Alaska Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":948891,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272292,"text":"70272292 - 2025 - Simple bagged movement models for telemetry data","interactions":[],"lastModifiedDate":"2025-11-20T16:07:50.517031","indexId":"70272292","displayToPublicDate":"2025-09-07T09:05:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Simple bagged movement models for telemetry data","docAbstract":"Determining which statistical methods are appropriate for data is both user and data dependent and prone to change as new methodology becomes available. This process encompasses model ideation, model selection, and determining appropriate use of statistical methods. Literature on models for animal movement emerging in the past two decades has yielded a rich collection of statistical methods garnering much deserved positive attention. Among such efforts, there is limited investigation of the broader place for simple machine learning methodology in animal movement modeling. We propose a bagged (i.e., bootstrap aggregated) animal movement model using simple, off-the-shelf machine learning algorithms. The model is intuitive, retains statistical inference about characteristics of animal movement (i.e., estimated from model-based summary statistics), and only requires knowledge of elementary statistical and machine learning analysis to understand. We show by simulation that our model can provide unbiased estimates of pertinent characteristics of animal movement (e.g., daily displacement) in the presence of large and realistic location error. We believe that increasing accessible literature on simple machine learning animal movement models provides valuable pedagogical and practical support for researchers using statistical models to study animal movement.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72060","usgsCitation":"Whetten, A.B., Hefley, T.J., Haukos, D.A., and Brewer, D.E., 2025, Simple bagged movement models for telemetry data: Ecology and Evolution, v. 15, no. 9, e72060, 14 p., https://doi.org/10.1002/ece3.72060.","productDescription":"e72060, 14 p.","ipdsId":"IP-178248","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72060","text":"Publisher Index Page"},{"id":496692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Whetten, Andrew B.","contributorId":362668,"corporation":false,"usgs":false,"family":"Whetten","given":"Andrew","middleInitial":"B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":950708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hefley, Trevor J.","contributorId":362671,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":950709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, Dustin E.","contributorId":362674,"corporation":false,"usgs":false,"family":"Brewer","given":"Dustin","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":950711,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271907,"text":"70271907 - 2025 - Mitigating flood risks in urban estuaries: Tidal dynamics, shoreline hardening, nature-based solutions, and floodgates in San Francisco Bay","interactions":[],"lastModifiedDate":"2025-09-24T15:53:03.924386","indexId":"70271907","displayToPublicDate":"2025-09-05T08:45:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8957,"text":"Journal of Waterway, Port, Coastal, and Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating flood risks in urban estuaries: Tidal dynamics, shoreline hardening, nature-based solutions, and floodgates in San Francisco Bay","docAbstract":"Hydrodynamic models are valuable tools for understanding the primary factors influencing daily and peak water levels and for guiding discussions on potential adaptation strategies for managing flood risk in coastal areas. This analysis uses the Delft3D San Francisco Bay-Delta Community Model to simulate water levels and incorporates the effects of a number of adaptation measures in the urban San Francisco Bay estuary, California. In particular, we examine the influence of shoreline hardening, nature-based solutions, and subregional floodgates on regional water levels. The result shows that under present conditions, tidal amplification is responsible for generating a wide distribution of extreme water levels across San Francisco Bay. Tidal amplification is found to decrease under sea level rise, thereby producing a relative damping effect on extremes. A comparison of different shoreline scenarios demonstrates that hard frontal shorelines result in higher tidal amplification, whereas restored (soft) shorelines lower amplification. The current shoreline configuration has both hard and soft characteristics and results in an intermediate tidal response. In some areas, wetland restoration reduces extreme water levels by as much as 20 cm, whereas hard-shoreline addition elevates them by as much as 10 cm for 1.5 m of sea level rise. Furthermore, local floodgates can significantly reduce high water levels without major adverse effects elsewhere in San Francisco Bay. These findings point toward the justification for a range of adaptive measures across political boundaries, weighing hard and soft options in addressing the mounting danger of sea level rise.
","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/JWPED5.WWENG-2342","usgsCitation":"Nederhoff, K., Saleh, R., Barnard, P., and Stacey, M.T., 2025, Mitigating flood risks in urban estuaries: Tidal dynamics, shoreline hardening, nature-based solutions, and floodgates in San Francisco Bay: Journal of Waterway, Port, Coastal, and Ocean Engineering, v. 151, no. 6, 04025031, 19 p., https://doi.org/10.1061/JWPED5.WWENG-2342.","productDescription":"04025031, 19 p.","ipdsId":"IP-176674","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jwped5.wweng-2342","text":"Publisher Index Page"},{"id":496022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.71980135286915,\n 38.31126858304765\n ],\n [\n -122.71980135286915,\n 37.4059191605038\n ],\n [\n -121.71348182307679,\n 37.4059191605038\n ],\n [\n -121.71348182307679,\n 38.31126858304765\n ],\n [\n -122.71980135286915,\n 38.31126858304765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"151","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":949331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Rohin","contributorId":265891,"corporation":false,"usgs":false,"family":"Saleh","given":"Rohin","email":"","affiliations":[{"id":54818,"text":"Alameda Flood Control District","active":true,"usgs":false}],"preferred":false,"id":949332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stacey, Mark T.","contributorId":360868,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark","middleInitial":"T.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":949334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271315,"text":"dr1215 - 2025 - Framework developed for geomorphic mapping of Fern Ridge Lake, Oregon, 2023","interactions":[],"lastModifiedDate":"2026-02-03T15:20:52.051701","indexId":"dr1215","displayToPublicDate":"2025-09-04T09:21:48","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1215","displayTitle":"Framework Developed for Geomorphic Mapping of Fern Ridge Lake, Oregon, 2023","title":"Framework developed for geomorphic mapping of Fern Ridge Lake, Oregon, 2023","docAbstract":"The construction and operation of large reservoirs in the Willamette River Basin, Oregon, influences important cultural, biological, and other natural or economic resources in affected river corridors. The present-day landforms and cover within the reservoirs have been shaped by a variety of processes, including the pre-dam valley setting and geomorphic processes related to dam operations. Maps of reservoir geomorphic process domains, landforms, and cover provide a foundation for understanding how erosion and deposition processes in or near the reservoirs may affect cultural resources. Detailed geomorphic mapping of Fern Ridge Lake in 2023 provides a basis for evaluating geomorphic processes and patterns of sediment transfer within the reservoir. These processes are related to geomorphic and hydroclimatic conditions as well as annual lake level fluctuation for seasonal flood-control operations. This geomorphic mapping also provides an inventory of existing landforms from which to evaluate the spatial and temporal geomorphic change over time. Digital maps based on high-resolution digital surface models and orthophotographs acquired during low-pool conditions in 2023 extend over an area of about 30 square kilometers (km) upstream of the Fern Ridge Dam. The mapping framework has 3 main components consisting of several subtypes: 5 process domains, 18 landforms, and 7 cover categories. The overarching classification structure is tied to the process domains, which correspond to dissimilar regions of the reservoir that have distinct landforms and broadly similar suites of geomorphic processes. This document describes the geomorphic mapping framework for the reservoir at Fern Ridge Lake and provides mapping unit descriptions including delineation criteria, hypothesized formation processes inferred from remote-sensing and field observations and the literature, and relevance during drawdown operations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1215","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Keith, M.K., and Bervid, H.D., 2025, Framework developed for geomorphic mapping of Fern Ridge Lake, Oregon, 2023: U.S. Geological Survey Data Report 1215, 33 p., https://doi.org/10.3133/dr1215.","productDescription":"Report: viii, 33 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-160706","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":496027,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118829.htm","linkFileType":{"id":5,"text":"html"}},{"id":495173,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1215/dr1215.XML"},{"id":495168,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1215/coverthb.jpg"},{"id":495169,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1215/dr1215.pdf","text":"Report","size":"9.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1215"},{"id":495170,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1215/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1215"},{"id":495171,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13MHC5P","text":"USGS data release","description":"USGS data release","linkHelpText":"Geomorphic Mapping of Fern Ridge Lake, Oregon, 2023"},{"id":495172,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1215/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Fern Ridge Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.36193413601275,\n 44.13431042059929\n ],\n [\n -123.36193413601275,\n 44.0351205618081\n ],\n [\n -123.23640004823704,\n 44.0351205618081\n ],\n [\n -123.23640004823704,\n 44.13431042059929\n ],\n [\n -123.36193413601275,\n 44.13431042059929\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
Invasive bigheaded carps (Bighead Carp Hypophthalmichthys nobilis, Silver Carp Hypophthalmichthys molitrix, and their hybrids Hypophthalmichthys spp.) currently infest the Mississippi River Basin. Bigheaded carps can outcompete native species in invaded waters and can also transform the surrounding environment. Currently, resource managers seek to limit the population abundance of bigheaded carps and their range expansion into additional regions of the Upper Mississippi River (UMR) but lack a tool to evaluate different control strategies. Here, we present an application of a Silver Carp spatial population model in the UMR to fill this gap. We used the model to explore how simulated control strategies could affect Silver Carp metapopulation dynamics. More specifically, we assessed and compared the importance of movement deterrents, removal locations, and recruitment areas on Silver Carp population abundances across the UMR. Strategies that included a combination of removal efforts and deterrents resulted in the largest decreases in Silver Carp abundance in the upper pools of the UMR. Furthermore, scenarios that targeted source populations of Silver Carp rather than sink populations resulted in larger decreases in Silver Carp abundance at the invasion front. The effectiveness of these combined simulated strategies also depended on the location of Silver Carp recruitment. Our work suggests that an understanding of Silver Carp metapopulation dynamics may be important for control efforts and could help to inform the management of Silver Carp in the UMR.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70101","usgsCitation":"Frame, K., Sandland, G.J., Labuzzetta, C.J., Loppnow, G.L., Stanton, J.C., Kao, Y., and Erickson, R.A., 2025, Exploring the importance of metapopulation dynamics with population control strategies for invasive silver carp in the upper Mississippi River: Journal of Wildlife Management, v. 89, no. 8, e70101, 19 p., https://doi.org/10.1002/jwmg.70101.","productDescription":"e70101, 19 p.","ipdsId":"IP-169626","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.42515752205935,\n 44.547455467183056\n ],\n [\n -92.42515752205935,\n 39.31069113760515\n ],\n [\n -89.49821279072381,\n 39.31069113760515\n ],\n [\n -89.49821279072381,\n 44.547455467183056\n ],\n [\n -92.42515752205935,\n 44.547455467183056\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Frame, Kassidy","contributorId":362254,"corporation":false,"usgs":false,"family":"Frame","given":"Kassidy","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":950246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory J. 0000-0002-9716-0232","orcid":"https://orcid.org/0000-0002-9716-0232","contributorId":362255,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","middleInitial":"J.","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":950247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Labuzzetta, Charles J. 0000-0002-6027-0120","orcid":"https://orcid.org/0000-0002-6027-0120","contributorId":332055,"corporation":false,"usgs":true,"family":"Labuzzetta","given":"Charles","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loppnow, Grace L.","contributorId":362256,"corporation":false,"usgs":false,"family":"Loppnow","given":"Grace","middleInitial":"L.","affiliations":[{"id":86499,"text":"Minnesota Department of Natural Resources, Ecological and Water Resources, Saint Paul, MN","active":true,"usgs":false}],"preferred":false,"id":950249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kao, Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":950251,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950252,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271347,"text":"70271347 - 2025 - An integrated sensor network and data driven approach to satellite remote sensing of dissolved organic matter","interactions":[],"lastModifiedDate":"2025-09-09T13:55:03.276031","indexId":"70271347","displayToPublicDate":"2025-09-03T08:50:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"An integrated sensor network and data driven approach to satellite remote sensing of dissolved organic matter","docAbstract":"Traditional remote sensing retrieval models for water quality have historically relied on limited, localized data sets due to the prohibitive costs of extensive field campaigns and logistical challenges of collecting match-up data with satellite overpasses. As a result, these models often lack generalizability across seasons, tides, and sites. Furthermore, small field data sets limit the utility of modern machine learning techniques to advance remote sensing retrieval models. In situ optical sensors deployed in a sensor network to continuously monitor larger water bodies can drastically increase the number of measurements, providing the opportunity to develop new approaches for building robust remote sensing retrieval models by leveraging both remote sensing data and in situ networks as an integrated monitoring system. This study leverages a large “ground-to-space” sensor network that combines an in situ optical sensor network with satellite-based remote sensing to overcome these limitations. Utilizing a large-scale data set from the U.S. Geological Survey's Sacramento—San Joaquin River Delta monitoring network, of dissolved organic matter fluorescence measurements, and remote sensing data from the European Space Agency's Sentinel-2A and -2B satellites, this study implemented a data driven approach for dissolved organic matter models. The data set, consisting of 982 samples collected between 2018 and 2021 was used to train and validate a random forest model (R2 = 0.76, RMSE = 6.1 Quinine Sulfate Equivalents), with demonstrated applicability across diverse site conditions, tidal stages, and seasons. This work provides a scalable solution to address critical challenges in water quality monitoring and offers a replicable framework for global water quality management.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024EA004048","usgsCitation":"Avouris, D., Hestir, E.L., Fleck, J., Hansen, J.A., and Bergamaschi, B.A., 2025, An integrated sensor network and data driven approach to satellite remote sensing of dissolved organic matter: Earth and Space Science, v. 12, no. 12, e2024EA004048, 19 p., https://doi.org/10.1029/2024EA004048.","productDescription":"e2024EA004048, 19 p.","ipdsId":"IP-172592","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":495389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024ea004048","text":"Publisher Index Page"},{"id":495247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Calfornia","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.34190472520478,\n 37.92367880802452\n ],\n [\n -121.34190472520478,\n 38.5486708617789\n ],\n [\n -121.98676504474714,\n 38.5486708617789\n ],\n [\n -121.98676504474714,\n 37.92367880802452\n ],\n [\n -121.34190472520478,\n 37.92367880802452\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Avouris, Dulcinea Marie 0000-0001-5797-3960","orcid":"https://orcid.org/0000-0001-5797-3960","contributorId":335170,"corporation":false,"usgs":true,"family":"Avouris","given":"Dulcinea Marie","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hestir, Erin L","contributorId":361027,"corporation":false,"usgs":false,"family":"Hestir","given":"Erin","middleInitial":"L","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":948142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Jeffrey A. 0000-0002-2185-1686","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":205441,"corporation":false,"usgs":true,"family":"Hansen","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948145,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271333,"text":"70271333 - 2025 - Impacts of lake elevation decline on spawning habitat of a critical, native forage species","interactions":[],"lastModifiedDate":"2025-12-01T16:30:30.860959","indexId":"70271333","displayToPublicDate":"2025-09-03T08:18:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of lake elevation decline on spawning habitat of a critical, native forage species","docAbstract":"Objective
Lake elevation decline is a global phenomenon with pronounced effects in arid regions that changes the characteristics of nearshore habitat area available to lacustrine spawners, potentially impacting recruitment and whole-lake food web dynamics. Our objective was to understand the potential effects of lake elevation decline on spawning habitat for the Tui Chub Siphateles bicolor, a lacustrine spawner and critical component of the native food web in Pyramid Lake, Nevada.
Methods
We explored the distribution of ripe Tui Chub in nearshore habitat by associating habitat characteristics to ripe Tui Chub CPUE from a custom gill-net configuration, with data analyzed using generalized linear mixed-effects models. We then explored potential spawning habitat availability at all potential lake elevations using an elevation-explicit model of the basin that we developed based on several bathymetric and geospatial data sets and the knowledge of spawner distribution gained in the first component of the study.
Results
Ripe Tui Chub catch was primarily predicted by temperature, reaching a maximum between 14.2°C and 24.8°C found at less than 15 m of depth in Pyramid Lake throughout the summer spawning period. We estimated that with a contemporary decline in lake elevation of 8 m, Pyramid Lake will host the minimum area of spawning habitat based on morphometry alone at a 40% decrease from a theoretical maximum.
Conclusions
A decrease in lake elevation or an increase in lake temperatures—both of which are probable events based on future climate scenarios and estimates of water extraction upstream of Pyramid Lake—is likely to further restrict Tui Chub spawning habitat area. Our results have important implications for ecological water demand in Pyramid Lake and provide managers with information facilitating a science-based approach to managing the fish community.
","language":"English","publisher":"American Fisheries Society","doi":"10.1093/tafafs/vnaf034","usgsCitation":"Barnes, S., Al-Chokhachy, R., and Budy, P., 2025, Impacts of lake elevation decline on spawning habitat of a critical, native forage species: Transactions of the American Fisheries Society, v. 154, no. 6, p. 640-656, https://doi.org/10.1093/tafafs/vnaf034.","productDescription":"17 p.","startPage":"640","endPage":"656","ipdsId":"IP-161347","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":495220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Pyramid Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.72328588180102,\n 40.234157713420586\n ],\n [\n -119.72328588180102,\n 39.842701658708876\n ],\n [\n -119.32079294757592,\n 39.842701658708876\n ],\n [\n -119.32079294757592,\n 40.234157713420586\n ],\n [\n -119.72328588180102,\n 40.234157713420586\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"154","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnes, Sarah","contributorId":360982,"corporation":false,"usgs":false,"family":"Barnes","given":"Sarah","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":948072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216140,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":948073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":948074,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270764,"text":"sir20255064 - 2025 - Grammar to graph—An approach for semantic transformation of annotations to triples","interactions":[],"lastModifiedDate":"2026-02-03T15:19:08.178992","indexId":"sir20255064","displayToPublicDate":"2025-09-02T11:30:00","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":"2025-5064","displayTitle":"Grammar to Graph—An Approach for Semantic Transformation of Annotations to Triples","title":"Grammar to graph—An approach for semantic transformation of annotations to triples","docAbstract":"Data annotation is the process of labeling data to show the outcome that a related data model should predict. In this study, annotation data were transformed into semantic graph triples, mainly for use with the Resource Description Framework (RDF), a type of entity-relationship-attribute data model for graph databases. The transformation of annotation data to semantic graph triples provides complex linguistic meaning with data handling advantages such as reduced data storage needs, improved logical specification of relations between objects, and reusable classes and properties that support logic and inference. A grammar-based framework in graph form supports user questions and queries.
The words defining approximately 334 topographic feature types compiled by the U.S. Geological Survey were tokenized as units of analysis and grouped by part of speech. Their dependency relations were identified for this study using natural language processing libraries. Dependency concepts are used as structured semantic relations among part-of-speech classes. Tokens, units equivalent to words, form instances of classes and were quantified within a tabular output format using PostgreSQL data storage software. Table data were logically aligned as triples following a mapping file and stored with an ontology file using Ontop virtual triplestore software. A grammar ontology schema for the data was synchronized to match queries whose results validated the graph’s structure. The text analysis produced 8 part-of-speech classes of content words for object representations and 4 classes of function words for operational applications. Dependency relations formed 27 ontology properties for topographic subgraph structures. Token occurrences shaped overall ontology salience and formed a lexicon of syntactic terms for subgraph objects and properties. The schema ontology of class and property population shapes formed the lexicon of English terms. SPARQL Protocol and RDF Query Language (SPARQL) was used with the lexicon to conform data to RDF guidelines.
This study confirms the hypothesis that although linguistic logic varies from description logic, its approximation applies to ontology design. Property and query use case patterns extracted from the analysis support queries concerning complex topographic relations and patterns normally embedded within text definitions. The method used in this study could be applied to text forms in other domains, such as survey notes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255064","programNote":"National Geospatial Program","usgsCitation":"Varanka, D.E., and Abbott, E., 2025, Grammar to graph—An approach for semantic transformation of annotations to triples: U.S. Geological Survey Scientific Investigations Report 2025–5064, 20 p., https://doi.org/10.3133/sir20255064.","productDescription":"Report: vi, 20 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150174","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":494546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5064/sir20255064.pdf","text":"Report","size":"3.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5064"},{"id":494604,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5064/sir20255064.xml"},{"id":494603,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5064/images"},{"id":494547,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1BDPXKZ","text":"USGS data release","description":"Data release associated with SIR 2025-5064","linkHelpText":"Grammar transformations of topographic feature type annotations of the U.S. to structured graph data"},{"id":494545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5064/coverthb.jpg","text":"Report"},{"id":495126,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255064/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5064"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
Box 25046, Mail Stop 510
Denver, Colorado 80225-0046
Clear Lake volcanic field (CLVF) is the northernmost and youngest (~2.2 Ma to 8 ka) of the volcanic centers distributed along the San Andreas transform fault in western California. The initial phase of CLVF volcanism (interval one) occurred between ~2.2 and 1.3 Ma and extends ~35 km southeast of Clear Lake, forming a semi-continuous upland plateau capped by lava flows, with isolated volcanic remnants on the periphery. This volcanism is broadly characterized by geochemically primitive compositions that reflect three source compositions and conditions of melt generation. (1) Partial melting of upwelling asthenospheric mantle lherzolite at moderate pressures (1.2–1.4 GPa) and temperatures (1297–1329 °C) produced high-CaO (9.8–11.3 wt %) basalts with high Al2O3 (16.8–17.6 wt %), Mg#s (66–70), MgO (8–10 wt %), Ni (103–262 μg/g), and Cr (284–609 μg/g). These high-CaO basalts contain olivine (Fo87–91) phenocrysts with Cr-spinel inclusions ± subordinate plagioclase and crop out only in the southern part of the CLVF. (2) Partial melting of depleted sub-continental lithospheric mantle harzburgite at variable pressures (0.7–1.5 GPa) and temperatures (1097–1299 °C) produced a compositional continuum of med-K2O, calc-alkaline, high-MgO basalts through high-MgO andesites with high Mg#s (67–77), MgO (8–14 wt %) and high Ni and Cr abundances (154–439 and 340–1124 μg/g, respectively). Mineral assemblages are olivine (Fo88–93) with Cr-spinel inclusions ± subordinate clinopyroxene, orthopyroxene and plagioclase. Small (<2.5 cm) mantle harzburgite xenoliths and mantle olivine xenocrysts are also found in several of these samples. These high-MgO basalts through andesites represent the largest volume of primitive compositions and have erupted predominantly along the main, fault-controlled northwest-southeast trending axis of volcanism with peripheral outcrops to the north, west, and east. (3) Partial melting of the Gorda eclogite slab edge produced adakitic silicic slab melts with strong depletion in the heavy rare earth elements (Yb = 0.6 μg/g). Subsequent reaction of those melts with depleted ultramafic rocks during ascent imprinted the adakitic dacites with high Mg#s (65–78) and elevated Ni (117–210 μg/g) and Cr (191–283 μg/g). Phenocrysts of orthopyroxene (En87–94) with spinel inclusions (Cr# = 80–88) and extremely Ni-rich (9483 μg/g) olivine cores (Fo84–93) record those reactions. Small-volume outcrops of the adakites on the eastern periphery of the CLVF track the passing slab edge. The trio of melting sources recorded by early CLVF magmatism reflect the tectonically complex environment and the hot (1097–1329 °C), shallow (0.7–1.5 GPa) melting conditions for these primitive compositions and provide estimates of the heat delivered to the crust. Over time, this flux led to maturation of the CLVF magmatic system toward the more voluminous and silicic volcanism that characterizes the balance of its subsequent volcanic history and maintains the present-day anomalously high heat flow in the region. The current interval (interval four) of volcanic activity at CLVF is characterized by low-volume, fault-controlled eruptions of basaltic andesite and andesite suggestive of mantle magma and heat delivery to the crust, similar to interval one. This analogous activity provides motivation for the current study and begs the question of whether the system is undergoing thermal priming for renewed silicic volcanism.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egaf077","usgsCitation":"Blatter, D.L., and Burgess, S.D., 2025, Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California: Journal of Petrology, v. 66, no. 9, egaf077, 43 p., https://doi.org/10.1093/petrology/egaf077.","productDescription":"egaf077, 43 p.","ipdsId":"IP-173749","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.9635380144356,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 39.14844575495471\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Blatter, Dawnika L. 0000-0002-7161-6844 dblatter@usgs.gov","orcid":"https://orcid.org/0000-0002-7161-6844","contributorId":4899,"corporation":false,"usgs":true,"family":"Blatter","given":"Dawnika","email":"dblatter@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgess, Seth D. 0000-0002-2128-9144","orcid":"https://orcid.org/0000-0002-2128-9144","contributorId":362359,"corporation":false,"usgs":true,"family":"Burgess","given":"Seth","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950371,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271905,"text":"70271905 - 2025 - A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","interactions":[],"lastModifiedDate":"2025-09-24T15:03:35.249606","indexId":"70271905","displayToPublicDate":"2025-09-01T07:53:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","docAbstract":"Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels.
Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below.
■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events.
■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin.
■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest.
■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats.
■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin.
■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea.
Several historical events stand out because of their catastrophic impacts.
■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005).
■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982).
■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023).
■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024).
■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011).
More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis.
This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.
","language":"English","publisher":"FEMA","collaboration":"NOAA","usgsCitation":"Sheehan, A., Zuzak, C., Wood, N.J., Bausch, D., Yeager, C.G., and McDougall, A., 2025, Estimated average annualized tsunami losses for the United States, xiv, 158 p.","productDescription":"xiv, 158 p.","startPage":"158","ipdsId":"IP-178510","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":496895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496887,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fema.gov/sites/default/files/documents/fema_hazus_p-2426_estimated-average-annualized-tsunami-losses-united-states_092025.pdf"}],"country":"Commonwealth of the Northern Marianas Islands, United States","state":"Alaska, California, Hawaii Oregon, Washington","otherGeospatial":"American Samoa, Guam, Puerto Rico, U.S. West Coast, U.S. Virgin Islands","geographicExtents":"{\n \"type\": 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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sheehan, Anne","contributorId":330480,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zuzak, Casey","contributorId":287432,"corporation":false,"usgs":false,"family":"Zuzak","given":"Casey","affiliations":[{"id":61582,"text":"FEMA Risk Mgmt Directorate","active":true,"usgs":false}],"preferred":false,"id":951002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bausch, Doug","contributorId":195191,"corporation":false,"usgs":false,"family":"Bausch","given":"Doug","email":"","affiliations":[{"id":34169,"text":"Pacific Disaster Center","active":true,"usgs":false}],"preferred":false,"id":951004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yeager, Cadie Goulette 0009-0002-6966-1811","orcid":"https://orcid.org/0009-0002-6966-1811","contributorId":361919,"corporation":false,"usgs":false,"family":"Yeager","given":"Cadie","middleInitial":"Goulette","affiliations":[{"id":86387,"text":"Niyam IT","active":true,"usgs":false}],"preferred":false,"id":951005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDougall, Alice","contributorId":363052,"corporation":false,"usgs":false,"family":"McDougall","given":"Alice","affiliations":[{"id":86600,"text":"FACTOR","active":true,"usgs":false}],"preferred":false,"id":951006,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273980,"text":"70273980 - 2025 - 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","interactions":[],"lastModifiedDate":"2026-02-24T14:58:17.527534","indexId":"70273980","displayToPublicDate":"2025-09-01T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","docAbstract":"The ongoing degradation of coral reef habitats is widely acknowledged to have adverse effects on the abundance and diversity of reef fish populations, yet the direct effects on ecosystem functions remain uncertain. This study used a quantitative approach to determine the mechanistic links between fish assemblages and ecological function. We investigated the effects of 3D habitat structure and coral morphology on the ecological, behavioral, and morphological functional traits of reef fish within a protected marine national park. Fish traits such as Gregariousness, Water Column Position, and Body Shape were identified to be highly influential in shaping the multidimensional fish functional space, which was categorized into 10 Fish Functional Groups (FFG). Furthermore, habitat complexity and coral morphology significantly explained the abundances of eight out of 10 FFG. Notably, the habitat complexity metrics of Slope and Surface Complexity, along with coral morphologies of Branching and Mounding types, emerged as the most influential habitat features across FFG. Pairing Compressiform species and Schooling Short/Deep species, for example, significantly increased in abundance on substrate with higher Slopes and increased percentages of branching coral cover. Additionally, Cryptic and Nocturnal species exhibited statistically significant associations with all coral morphologies and substrates with high trait values of Slope and Curvature. Elucidating ecological drivers of specific functional groups of reef fish is critical for determining how changes in reef composition and structure will alter fish assemblages. Broad scale patterns were also detected, suggesting that although structural complexity is important, live coral morphologies have a greater positive impact on reef fish functional groups. These findings have direct implications for conservation and monitoring efforts, offering valuable insights for predicting the impacts of environmental change on community dynamics and ecosystem functioning.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71992","usgsCitation":"Ferreira, S.B., Burns, J.H., Fukunaga, A., Raz, L., McKenna, S.A., Annandale, K., Monello, R.J., 2025, 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park: Ecology and Evolution, v. 15, no. 9, e71992, 16 p., https://doi.org/10.1002/ece3.71992.","productDescription":"e71992, 16 p.","ipdsId":"IP-174520","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500601,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71992","text":"Publisher Index Page"},{"id":500436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","city":"Kailua-Kona","otherGeospatial":"Kaloko-Honokohau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.0727322749224,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.716285054970754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferreira, Sofia B.","contributorId":366488,"corporation":false,"usgs":false,"family":"Ferreira","given":"Sofia","middleInitial":"B.","affiliations":[],"preferred":false,"id":955983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, John H.R.","contributorId":366489,"corporation":false,"usgs":false,"family":"Burns","given":"John","middleInitial":"H.R.","affiliations":[],"preferred":false,"id":955984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fukunaga, Atsuko","contributorId":366490,"corporation":false,"usgs":false,"family":"Fukunaga","given":"Atsuko","affiliations":[],"preferred":false,"id":955985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raz, Lillian Joy Tuttle 0000-0002-5009-8080","orcid":"https://orcid.org/0000-0002-5009-8080","contributorId":354940,"corporation":false,"usgs":true,"family":"Raz","given":"Lillian Joy Tuttle","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenna, Sheila A.","contributorId":366491,"corporation":false,"usgs":false,"family":"McKenna","given":"Sheila","middleInitial":"A.","affiliations":[],"preferred":false,"id":955987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Annandale, Kailea","contributorId":366492,"corporation":false,"usgs":false,"family":"Annandale","given":"Kailea","affiliations":[],"preferred":false,"id":955988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monello, Ryan J.","contributorId":366493,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","middleInitial":"J.","affiliations":[],"preferred":false,"id":955989,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270765,"text":"sir20255077 - 2025 - Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","interactions":[],"lastModifiedDate":"2026-02-03T15:17:46.175988","indexId":"sir20255077","displayToPublicDate":"2025-08-29T11:03:01","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":"2025-5077","displayTitle":"Fluvial Sediment Dynamics in the Shoshone River and Tributaries Around Willwood Dam, Park County, Wyoming","title":"Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","docAbstract":"Sedimentation affects many of the aging reservoirs in the United States. Dams and water diversions from rivers have been central elements of infrastructure supporting agricultural irrigation in the arid and semiarid regions of the Western United States for more than a century. The Willwood Irrigation District diversion dam (hereafter referred to as “Willwood Dam”) in Park County, Wyoming, is approximately 12 miles northeast of Cody, Wyo.; has a structural height of 70 feet; and impounds the Shoshone River for diversion into the Willwood Canal. Willwood Dam is part of a larger irrigation scheme supported by water storage in the much larger Buffalo Bill Dam, which is approximately 20 miles upstream. In October 2016, renovation construction activities at Willwood Dam and the Willwood Canal caused an unplanned evacuation of nearly 96,000 cubic yards of fine sediment.
The fine sediment release in 2016 raised concerns that ongoing sediment management at Willwood Dam could impose limits on the long-term health of the aquatic ecosystem and fish populations. The U.S. Geological Survey, in cooperation with Wyoming Department of Environmental Quality and Willwood Work Groups 2 and 3, initiated an investigation of the dynamics of sediment transport in the Shoshone River and selected tributaries between Buffalo Bill Dam and Willwood Dam. The goal of the study was to quantify sediment transport into and out of Willwood Dam on an annual, seasonal, and event basis to better understand the relative quantities of sediment coming from natural sources and human activities on the landscape. The study ran from March 2019 through October 2021 and used observations of streamflow, turbidity, and acoustic backscatter collected at streamgages upstream and downstream from Willwood Dam to quantify suspended-sediment loads into and out of the dam during irrigation and fallow seasons, precipitation-runoff events, and deliberate sediment releases. Each tributary’s relative contribution to the sediment load upstream from Willwood Dam was examined using discrete measurements of suspended-sediment concentration and bedload during irrigation and fallow seasons, precipitation events, and stable conditions.
Analysis of daily precipitation and temperature data indicated that conditions in the study area during the 2019 agricultural year were wetter and colder than period of record normal, and drier and near normal temperatures for the 2020 and 2021 agricultural years. Not all sediment load records between 2019 and 2021 are complete because of rejected observations (outliers), instrument failures or fouling, and instrument removal for calibrations.
Statistical modeling of suspended-sediment concentration using paired values of turbidity and acoustic backscatter produced four models that, after refinement, had coefficients of determination indicating that more than 84 percent of the variance was explained by either turbidity or acoustic backscatter. A system of rules was developed to select the model predictions based on the seasonal operations of Willwood Dam, assumptions about the grain sizes mobilized during these operations, and assumed accuracy of the models at the downstream streamgage (Shoshone River below Willwood Dam, near Ralston, Wyo. [streamgage 06284010]) under different operational conditions. The sediment budget between upstream and downstream estimates of loads was interpreted using the mean predicted values bound by their respective model prediction intervals. When mean predicted loads of one streamgage were contained in the prediction intervals of the other streamgage, and vice-versa, difference in the sediment budget were interpreted as “indeterminate.”
Modeled sediment load balances demonstrated the depositional and erosional behaviors expected from the conceptual model of dam operations whereby sediment tends to accumulate during irrigation seasons when the dam is spilling over the top, and sediment tends to evacuate during the fallow seasons when it is flowing through the sluice gates at the base of the dam. The sediment load calculations using the rules-based model criteria indicated that between 14,200 and 380,000 tons of suspended sediment moved through the Shoshone River around Willwood Dam during the irrigation seasons of 2019, 2020, and 2021; 380,000 tons of suspended sediment were transported during the cool, wet year of 2019, and 14,200 tons of suspended sediment were transported in 2020, which was relatively dry. During fallow seasons 2019, 2020, and 2021, which had fewer complete records, between 1,140 and 106,000 tons of suspended sediment was estimated to have moved through the river.
For all seasons except fallow season 2022, the models estimated that more sediment was released from the dam than entered the dam, but the modeled mean loads at each streamgage were nearly always within the prediction intervals of each other, making the sediment balance indeterminant. Examination of suspended-sediment loads during irrigation seasons indicated that between 65 and 85 percent of fine sediment was transported during annual high flows and storm events, with the remainder transported during steady, lower streamflows. Examination of suspended loads during fallow seasons indicated that deliberate sediment releases through Willwood Dam accounted for between 39 and 67 percent of the total sediment moved during the fallow seasons. Deliberate sediment releases from Willwood Dam had estimated net exports of between 1,360 and 22,400 tons.
Between August 2017 and July 2023, suspended-sediment concentration and bedload sediment samples were collected from 9 tributaries to the Shoshone River during 137 sampling events, including stable and precipitation-runoff conditions. During irrigation season precipitation events, the mean total sediment yields ranged from 0.33 to 9.51 tons per day per square mile; during fallow season precipitation events, the mean total yields ranged from 0.04 to 0.95 ton per day per square mile. The mean total sediment yield per unit area across all samples at each tributary site ranged from 0.26 to 3.08 tons per day per square mile. Bedload was a minor fraction of the total load, constituting a mean of 4 percent across all samples; 3 and 6 percent for events and nonevents, respectively, during irrigation season; and 3 and 1 percent for events and nonevents, respectively, during the fallow season. With the exception of one tributary, Dry Creek, these mean yield values were within the range of watershed-scale background sediment yield values estimated from reservoir surveys and previous suspended-sediment studies.
Imagery from irrigation seasons 2012, 2015, 2017, 2019, and 2022 was used to determine the planimetric backwater extent of the pool area in the Shoshone River behind Willwood Dam to identify any changes in sediment storage. Active river channel widths in the Shoshone River upstream from Willwood Dam were all similar between years except 2015, which was determined to be statistically different from all other years. Bathymetric data taken in the pool behind Willwood Dam during three different surveys between November 2017 and April 2022 indicated no statistically significant differences in bed elevations between the years. Results from the planimetric and bathymetric survey data provide multiple lines of evidence indicating that sediment did not accumulate behind the dam within the error of the methods used.
Examination of how precipitation affects sediment transport in the Shoshone River upstream from Willwood Dam indicated that accumulated rainfall from the natural runoff events captured during the study period varied from a trace to as much as 4.26 inches, with associated predicted suspended-sediment loads varying from 112 to 232,000 tons of suspended sediment. The behavior of the sediment loads relative to accumulated precipitation did not appear to change depending on irrigation or fallow season. A model of suspended-sediment concentrations relative to the 2-day accumulated precipitation indicated that suspended-sediment concentrations in the Shoshone River upstream from Willwood Dam increased exponentially for accumulations of 0.3 inch or more; such storms accounted for 10 percent or less of precipitation events observed during the 1981 to 2018 period of record.
The gaps in records, precision of the instrumentation, and large variation in grain sizes in suspended-sediment mixtures downstream from the dam made closing the sediment budgets for most seasons unattainable. The biggest recent change in sediment storage measured using the planimetric area of deposits behind Willwood Dam took place between 2015 and 2017. The main event between these two measurements was the installation of new Willwood Canal gates in October 2016, which resulted in the large unplanned sediment release. Because the sediment budgets were nearly always indeterminate and the planimetric and bathymetric data indicated little change in the bed and bank material, it is likely that the change in sediment storage behind the dam during the study period was small relative to the precision of the statistical models and other uncertainties.
This body of evidence suggests that, averaged during the 3-year study period, no major changes in storage took place, and that the current operations may be keeping storage at near-equilibrium. This condition could have been initiated because the middle sluice gate has now been operational since 2014, and the sediment release in October 2016 evacuated a large amount of legacy sediment from storage. Although the uncertainties are large, sluicing events allow for controlled releases of sediment that contributed to the near equilibrium conditions observed over an annual basis during this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255077","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Alexander, J.S., Brown, H., Eddy-Miller, C.A., Burckhardt, J., Burckhardt, L., Ellison, C., McIntyre, C., Moger, T., Patterson, L., Tavelli, C., Waterstreet, D., and Williams, M., 2025, Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2025–5077, 70 p., https://doi.org/10.3133/sir20255077.","productDescription":"Report: x, 70 p.; Data Release; Dataset","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164415","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":494651,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255077/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5077"},{"id":494674,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":494673,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VHDRG","text":"USGS data release","linkHelpText":"Shapefiles of digitized backwater extent behind Willwood Dam on the Shoshone River, near Cody, Wyoming, derived from 2012, 2015, 2017, 2019, and 2022 National Agriculture Imagery Program imagery"},{"id":494652,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5077/images"},{"id":494654,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.XML","linkFileType":{"id":8,"text":"xml"}},{"id":494650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.pdf","text":"Report","size":"9.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5077"},{"id":494649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5077/coverthb.jpg"}],"country":"United States","state":"Wyoming","county":"Park County","otherGeospatial":"Shoshone River and tributaries around Willwood Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.66170194279013,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.80967182289373\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO3−), magnesium (Mg2+) and calcium (Ca2+). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO3−, 0.65 for Ca2+, and 0.79 for Mg2+. Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180286","usgsCitation":"Green, C., Hirsch, R.M., Essaid, H., and Sanford, W.E., 2025, Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin: Science of the Total Environment, v. 999, 180286, 14 p., https://doi.org/10.1016/j.scitotenv.2025.180286.","productDescription":"180286, 14 p.","ipdsId":"IP-159069","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":496136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180286","text":"Publisher Index Page"},{"id":495782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79788517502844,\n 39.713218235332164\n ],\n [\n -75.44918608740714,\n 38.663983307614814\n ],\n [\n -74.82016028228699,\n 38.99952921670035\n ],\n [\n -74.61504317192174,\n 39.81307746348011\n ],\n [\n -74.15695069541222,\n 41.998596289750736\n ],\n [\n -74.9227212407762,\n 42.30779251171998\n ],\n [\n -75.65430560107949,\n 41.9782683665571\n ],\n [\n -76.07821429583441,\n 41.159834427011475\n ],\n [\n -76.03035363674925,\n 40.632678412780365\n ],\n [\n -75.79788517502844,\n 39.713218235332164\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"999","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":949040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":949041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essaid, Hedeff 0000-0003-0154-8628","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":361587,"corporation":false,"usgs":false,"family":"Essaid","given":"Hedeff","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":949042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271299,"text":"70271299 - 2025 - Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","interactions":[],"lastModifiedDate":"2025-09-03T15:29:49.125047","indexId":"70271299","displayToPublicDate":"2025-08-29T08:20:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","docAbstract":"Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications (i.e., road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride (i.e., hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14485-6","usgsCitation":"Fanelli, R.M., Morency, M., Fleming, B.J., Moore, J., Hardesty, D., and Shoda, M.E., 2025, Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA: Environmental Monitoring and Assessment, no. 197, 1056, 25 p., https://doi.org/10.1007/s10661-025-14485-6.","productDescription":"1056, 25 p.","ipdsId":"IP-175501","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":495182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-14485-6","text":"Publisher Index Page"},{"id":495151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79184558063025,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 41.902372822441464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"197","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":341844,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morency, Michelle 0009-0000-9027-7561","orcid":"https://orcid.org/0009-0000-9027-7561","contributorId":345367,"corporation":false,"usgs":false,"family":"Morency","given":"Michelle","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":947887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Joel","contributorId":49034,"corporation":false,"usgs":false,"family":"Moore","given":"Joel","affiliations":[],"preferred":false,"id":947889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardesty, Deanna 0000-0002-4924-2233","orcid":"https://orcid.org/0000-0002-4924-2233","contributorId":341845,"corporation":false,"usgs":true,"family":"Hardesty","given":"Deanna","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947890,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":947891,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271296,"text":"70271296 - 2025 - Dispersal and survival of sea lamprey in Lake Erie and connected waterways","interactions":[],"lastModifiedDate":"2026-01-05T16:40:02.610528","indexId":"70271296","displayToPublicDate":"2025-08-29T07:47:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Dispersal and survival of sea lamprey in Lake Erie and connected waterways","docAbstract":"Invasive sea lamprey inhabiting the North American Laurentian Great Lakes are the target of the world’s longest running vertebrate invasive species control program. However, metapopulation dynamics comprising survival and dispersal during the sea lampreys’ lake-resident life stages are poorly understood. We applied acoustic telemetry and continuous-time multistate capture-recapture modeling to address this knowledge gap in Lake Erie. We acoustic-tagged sea lamprey (n = 619) and deployed acoustic receivers into all known connected waterways containing larval sea lamprey rearing habitat (n = 23), including the Detroit River (connecting Lake Erie to Lake Huron) and distributaries to Lake Ontario. Distribution of tagged sea lamprey to putative spawning waterways was shaped by heterogeneous stream attractiveness and distance-limited dispersal. Using parameter estimates from our capture-recapture model and simulation, we predicted survival and dispersal outcomes for a hypothetical sea lamprey population evenly distributed throughout Lake Erie at the beginning of January (34% pre-spawn mortality, 45% dispersal into Lake Erie tributaries, 19% dispersal into the Detroit River, and 2% dispersal into Lake Ontario). The methodology we applied may be widely useful for investigating dispersal and survival of aquatic organisms.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0103","usgsCitation":"Lewandoski, S.A., and Holbrook, C., 2025, Dispersal and survival of sea lamprey in Lake Erie and connected waterways: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-13, https://doi.org/10.1139/cjfas-2025-0103.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-181833","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495148,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496372,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2025-0103","text":"Publisher Index Page"}],"country":"Canada, United States","otherGeospatial":"Lake Erie, Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.70617488623432,\n 42.02384024551296\n ],\n [\n -83.62185164386733,\n 41.22531282546535\n ],\n [\n -80.95581262939565,\n 41.614162157533514\n ],\n [\n -78.44800562562105,\n 42.65436741270719\n ],\n [\n -78.07746378748234,\n 44.06396277336654\n ],\n [\n -79.76290535037472,\n 43.86046169412299\n ],\n [\n -83.70617488623432,\n 42.02384024551296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewandoski, Sean Alois 0000-0002-6801-5861","orcid":"https://orcid.org/0000-0002-6801-5861","contributorId":340324,"corporation":false,"usgs":true,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"Alois","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947885,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271378,"text":"70271378 - 2025 - Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","interactions":[],"lastModifiedDate":"2025-09-10T14:44:00.057371","indexId":"70271378","displayToPublicDate":"2025-08-29T07:38:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","docAbstract":"The Palila (Loxioides bailleui), the last member of the once speciose finch-billed Hawaiian honeycreeper clade (Drepanidinae) in the main Hawaiian Islands, faces critical conservation challenges as an endangered species. Understanding the drivers of its decline is essential for effective management. We used additive decomposition models to examine temporal trends in climatic variables (temperature, precipitation, drought) and Normalized Difference Vegetation Index (NDVI), a vegetation health metric hypothesized to be associated with long-term trends in Palila abundance at landscape (250 m) scales on the Island of Hawai'i. A breakpoint analysis identified 2005–2009 as critical years of Palila decline. Vegetation health metrics at the 250 m scale lined up well both spatially and temporally with trends in Palila declines, with a significant browning from January 2004 to January 2014. Given the strong correlation between vegetation health and drought metrics at the landscape scale (r = 0.75, p < 0.001), NDVI changes appeared driven by drought. To enable the future projection of habitat quality in this area, we explored a stepwise linear regression to explain the variation in MODIS NDVI in recent years. We found that 87 % of the variability in NDVI can be explained by wet season precipitation and vapor pressure deficit from the previous dry season. The model is largely driven by a strong positive correlation between wet season precipitation and NDVI (r = 0.72, adjusted p < 0.001). Areas that maintained a low likelihood of NDVI decline throughout the time series and experienced increases in predicted Palila count represent potential drought microrefugia for the species. This higher elevation microrefugia is likely resilient against decreases in wet season precipitation through supplemental water retention from fog drip. While NDVI rebounded after 2014, Palila have not recovered. Our analysis highlights the importance of trend decomposition for monitoring endangered species with limited rebound potential due to small population dynamics and indicate continued warm, dry conditions may prevent Palila recovery without intervention.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03831","usgsCitation":"Gallerani, E.M., Camp, R.J., Banko, P.C., Madson, A., Dong, C., Fortini, L., Ma, Z., and Gillespie, T.W., 2025, Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper: Global Ecology and Conservation, v. 62, e03831, 14 p., https://doi.org/10.1016/j.gecco.2025.e03831.","productDescription":"e03831, 14 p.","ipdsId":"IP-166687","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":495392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03831","text":"Publisher Index Page"},{"id":495277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.6511297931527,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.916012794249554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gallerani, Erica M.","contributorId":361171,"corporation":false,"usgs":false,"family":"Gallerani","given":"Erica","middleInitial":"M.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":948319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":948320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madson, Austin","contributorId":304629,"corporation":false,"usgs":false,"family":"Madson","given":"Austin","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":948321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dong, Chunyu","contributorId":304633,"corporation":false,"usgs":false,"family":"Dong","given":"Chunyu","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":948323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ma, Zhimin","contributorId":304634,"corporation":false,"usgs":false,"family":"Ma","given":"Zhimin","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948324,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gillespie, Thomas W.","contributorId":361172,"corporation":false,"usgs":false,"family":"Gillespie","given":"Thomas","middleInitial":"W.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948325,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70270434,"text":"sir20255069 - 2025 - Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","interactions":[],"lastModifiedDate":"2026-02-03T15:15:45.219139","indexId":"sir20255069","displayToPublicDate":"2025-08-27T11:06:10","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":"2025-5069","displayTitle":"Streamflow Extents and Hydraulic Characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","title":"Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","docAbstract":"The former Stuart Ranch, now managed by the Bureau of Land Management, is transected by Meadow Valley Wash, where 4,600 feet of perennial stream and adjacent riparian vegetation provide critical habitat for several wildlife and aquatic species protected under the Endangered Species Act. The stream has been altered by prior construction of irrigation diversions, gravel mining, and removal of riparian vegetation, resulting in the loss of instream and riparian vegetation and disconnected floodplains. The stream alteration has also resulted in the loss of native species and increased non-native invasive species and changes in ecological cycles. With the goal of improving habitat extent and quality for native threatened and endangered species, the Bureau of Land Management (BLM) is considering establishing perennial streams through braided side channels by constructing beaver dam analogs, excavating side channel connectors, and grading an irrigation reservoir berm on the floodplain. The U.S. Geological Survey (USGS) provided hydraulic modeling to assist the BLM in evaluating how possible restoration modifications could affect the extent of aquatic, riparian, and other habitat types. Three two-dimensional (2-D) hydraulic models were developed to simulate 2021 conditions (when most of the topographic data were collected), minor restoration modifications (one excavated side channel and a beaver dam analog), and major restoration modifications (three excavated side channels, a beaver dam analog, and an excavated and graded area to remove the irrigation reservoir) to determine streamflow-inundation extents and hydraulic characteristics (depth and velocity) for base flow and various flood (50-, 20-, 10-, 4-, 2-, and 1-percent annual exceedance probability [AEP]) scenarios. An average summer base flow of 0.92 cubic feet per second was estimated based on data from a USGS streamgage in the study area. The 50-, 20-, 10-, 4-, 2-, and 1-percent AEP streamflows were estimated based on a flood-frequency analysis of data from the streamgage. The base flow and AEP floods were combined with surveyed topographic data to create a 2-D unsteady hydraulic model. The hydraulic model was used to simulate the base flow and flood-inundation extents and hydraulic characteristics under 2021 conditions and with two possible restoration modification scenarios. Under 2021 conditions, flow remains in a single channel until the most downstream end of the modeled reach, where flow then expands into slower velocity pools. During floods, streamflow begins to enter the side channels at the 50-percent flood, expands into the east floodplain at 20-percent flood, and flows in the irrigation reservoir at 4-percent flood. Compared to 2021 conditions with no terrain modification, base flow under the possible restoration modifications enters and remains in the side channels, thus increasing the likelihood of expanding riparian habitat. Additionally, during floods under the major restoration modifications, streamflow expands into the modified terrain surrounding the irrigation reservoir at 10-percent AEP, as opposed to 4-percent AEP under 2021 conditions. For all modeled streamflow scenarios, streamflow is deepest in the center of the main and side channels, as well as the downstream pooled areas. Streamflow is fastest in the narrow sections of the channels, especially in the upper 1,220 feet of the modeled reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255069","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Resources Mission Area","usgsCitation":"Dye, L.A., Morris, C.M., and Childres, H.K., 2025, Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada: U.S. Geological Survey Scientific Investigations Report 2025–5069, 24 p., https://doi.org/10.3133/sir20255069.","productDescription":"Report: vi, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124818","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":494320,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5069/images"},{"id":494319,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HQ6F7","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data, flood-frequency analysis, and surface-water model archive for streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada"},{"id":494317,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5069"},{"id":494316,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5069/coverthb.jpg"},{"id":494318,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5069"},{"id":494321,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.XML"}],"country":"United States","state":"Nevada","city":"Rox","otherGeospatial":"Meadow Valley Wash at Stuart Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.6611,\n 36.84\n ],\n [\n -114.6611,\n 36.8278\n ],\n [\n -114.65,\n 36.8278\n ],\n [\n -114.65,\n 36.84\n ],\n [\n -114.6611,\n 36.84\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road, Suite 3
Carson City, Nevada 89701