{"pageNumber":"3","pageRowStart":"50","pageSize":"25","recordCount":40754,"records":[{"id":70274118,"text":"70274118 - 2026 - Evaluating evidence of changing regional occupancy of four bat species in response to forest management practices","interactions":[],"lastModifiedDate":"2026-02-26T16:36:43.114128","indexId":"70274118","displayToPublicDate":"2026-02-23T09:23:39","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating evidence of changing regional occupancy of four bat species in response to forest management practices","docAbstract":"

Coordinated, regional strategies to guide effective management and conservation of forests can be used to balance conservation with management for other objectives such as timber, scenic viewsheds, and fire. A key part of these regional strategies is incorporating knowledge of how management actions may affect certain species, especially those that are sensitive or are of concern. However, knowledge of how management actions may affect species is inferred from studies conducted across small areas where the species’ behavior and forest conditions are easily assessed. Here, we examine how occupancy of four bat species responds to forest management across the eastern United States at regional scales. We used range-wide capture and stationary acoustic surveys from the North American Bat Monitoring Program from 2010 to 2020 to estimate yearly summer occupancy for four bat species of conservation concern identified in the U.S. Department of Agriculture Forest Service (USFS) Southern and Eastern Regions Bat Conservation Strategy: little brown bat (Myotis lucifugus), northern long-eared bat (Myotis septentrionalis), Indiana bat (Myotis sodalis), and tricolored bat (Perimyotis subflavus), and assessed the degree to which occupancy of each species changed after different vegetation management actions were implemented on USFS lands. We identified 78 different management actions that were hypothesized to influence summer bat occupancy at two spatial scales (5-km and 10-km) across the eastern United States from the Forest Service Activity Tracking System and grouped these management actions into four vegetation management types: clear-cutting, fire, thinning, and ground vegetation management. To evaluate potential effects of these vegetation management types on bat occupancy, we created a yearly management metric representing the average number of years that had passed since any one of the included management actions in each management type had been implemented in each 5-km or 10-km grid cell, weighted by the proportion of the grid cell covered by the management treatment history. We chose these metrics to ask if more management or management done recently had a larger effect on bat occupancy than less management or management done long-ago. We then fit Bayesian hierarchical multi-scale occupancy models for each species to assess how occupancy changed in response to the amount and time since implementation of each vegetation management type. Using the estimated relationships between the yearly metrics of management and bat occupancy, we created predictions for how bat occupancy responded at 1- and 5- years after implementation. We found substantial differences in the response of the four species to the four vegetation management types. Ground vegetation management provided the greatest increase in expected occupancy at 1 year after implementation for little brown bat, long-eared bat, and tricolored bat, while fire provided the greatest increase in expected occupancy for Indiana bat. Thinning provided increases for all species at 1 year after implementation, but even greater increases at 5 years after implementation. Clear-cutting, on the other hand, tended to result in decreased occupancy at both 1- and 5-years after implementation for each species and had the greatest effect on tricolored bat at 1 year after implementation. Clear evidence for how management types like these may be affecting bat populations can be used at regional scales to help private and public forest managers achieve their strategic goals.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2026.123639","usgsCitation":"Inman, R.D., Udell, B.J., Wray, A.K., Straw, B.R., Schuhmann, A.N., Davis, H.T., Sawyer, S.C., Reichert, B.E., 2026, Evaluating evidence of changing regional occupancy of four bat species in response to forest management practices: Forest Ecology and Management, v. 609, 123639, 18 p., https://doi.org/10.1016/j.foreco.2026.123639.","productDescription":"123639, 18 p.","ipdsId":"IP-175875","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":500610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2026.123639","text":"Publisher Index Page"},{"id":500544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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Center","active":true,"usgs":true}],"preferred":true,"id":956583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wray, Amy Kristine 0000-0001-9685-8308","orcid":"https://orcid.org/0000-0001-9685-8308","contributorId":334941,"corporation":false,"usgs":true,"family":"Wray","given":"Amy","email":"","middleInitial":"Kristine","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Straw, Bethany R. 0000-0001-9086-4600","orcid":"https://orcid.org/0000-0001-9086-4600","contributorId":271020,"corporation":false,"usgs":true,"family":"Straw","given":"Bethany","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schuhmann, Andrea Nichole 0009-0005-8244-4303","orcid":"https://orcid.org/0009-0005-8244-4303","contributorId":329059,"corporation":false,"usgs":true,"family":"Schuhmann","given":"Andrea","email":"","middleInitial":"Nichole","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Helen Trice 0000-0001-5449-4331","orcid":"https://orcid.org/0000-0001-5449-4331","contributorId":336752,"corporation":false,"usgs":true,"family":"Davis","given":"Helen","middleInitial":"Trice","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956587,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sawyer, Sarah C.","contributorId":367020,"corporation":false,"usgs":false,"family":"Sawyer","given":"Sarah","middleInitial":"C.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":956588,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956589,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274083,"text":"70274083 - 2026 - Site response models based on geometric parameters for southern California sedimentary basins","interactions":[],"lastModifiedDate":"2026-03-09T14:56:34.655448","indexId":"70274083","displayToPublicDate":"2026-02-23T08:23:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Site response models based on geometric parameters for southern California sedimentary basins","docAbstract":"

Site response in sedimentary basins is influenced by complex three-dimensional (3D) features, including trapping of seismic waves, focusing of seismic energy and basin resonance. Current ground motion models (GMMs) incorporate basin effects using one-dimensional parameters like VS30 and shear wave velocity isosurface depths, which are limited in capturing lateral and 3D effects. To address these limitations, we develop seismic site response models based on novel parameters that represent multi-dimensional properties of the Los Angeles Basin (LAB) geometry and shear wave velocity. We define a basin shape for the LAB using depth to subsurface geologic interfaces associated with the oldest sedimentary deposits (depth to a particular shear wave velocity horizon, i.e., 1.5 km/s - z1.5) and the depth to the crystalline basement (zcb) which are determined using geologic cross sections and community seismic velocity model profiles. We explore a suite of geometric descriptors computed for the LAB and southern California, from which three parameters with the greatest predictive potential are selected and evaluated using empirical ground motion residual analyses in combination with the Boore et al. GMM. The results demonstrate that the zonal heterogeneity index (\"mathematical), standard deviation of the absolute difference between z1.5 and zcb (\"mathematical) and standard deviation of zcb (\"mathematical) each provide a reduction in site-to-site variability (ϕS2S) of empirical GMMs. The reduction in ϕS2S is period-dependent, with average decreases of 3%, 26% and 6% for \"mathematical, \"mathematical, and \"mathematical, respectively. Although these reductions are modest from an engineering application perspective, they are statistically significant, underscoring the inherent difficulty in fully characterising complex basin effects. Collectively, these findings indicate that the inclusion of basin-specific geometric parameters yields measurable, albeit incremental, improvements in site response prediction and establishes a framework for the progressive refinement of seismic hazard characterisation within sedimentary basins.

","language":"English","publisher":"Wiley","doi":"10.1002/esp4.70027","usgsCitation":"Shams, R., Nweke, C.C., and Parker, G.A., 2026, Site response models based on geometric parameters for southern California sedimentary basins: Earthquake Spectra, v. 42, no. 1, e70027, 27 p., https://doi.org/10.1002/esp4.70027.","productDescription":"e70027, 27 p.","ipdsId":"IP-171681","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501101,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp4.70027","text":"Publisher Index Page"},{"id":500479,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"southern California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.53506621436776,\n 35.21356617300536\n ],\n [\n -120.79600361096189,\n 34.90448000088518\n ],\n [\n -120.75474337287181,\n 34.34368243947756\n ],\n [\n -118.73627556859424,\n 33.915392671441865\n ],\n [\n -118.45980648687038,\n 34.843303775362216\n ],\n [\n -120.53506621436776,\n 35.21356617300536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Shams, Rashid","contributorId":366973,"corporation":false,"usgs":false,"family":"Shams","given":"Rashid","affiliations":[{"id":47795,"text":"USC","active":true,"usgs":false}],"preferred":false,"id":956491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nweke, Chukwuebuka C.","contributorId":366974,"corporation":false,"usgs":false,"family":"Nweke","given":"Chukwuebuka","middleInitial":"C.","affiliations":[{"id":47795,"text":"USC","active":true,"usgs":false}],"preferred":false,"id":956492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956493,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274153,"text":"70274153 - 2026 - Multireservoir allocation framework considering societal and ecological needs in a time-frequency domain","interactions":[],"lastModifiedDate":"2026-03-03T14:23:51.443064","indexId":"70274153","displayToPublicDate":"2026-02-23T07:44:23","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2501,"text":"Journal of Water Resources Planning and Management","active":true,"publicationSubtype":{"id":10}},"title":"Multireservoir allocation framework considering societal and ecological needs in a time-frequency domain","docAbstract":"

Existing reservoir management frameworks traditionally consider historical (predam) flow conditions to deliver environmental flows. Such frameworks may not be feasible because current demand and/or climate could be different from predam conditions. Hence, we developed a multireservoir framework that explicitly considers both human water demands and environmental flow requirements to minimize deviations under current hydroclimatic conditions and demand patterns. The multireservoir framework, Generalized Reservoir Analyses using Probabilistic Streamflow (GRAPS), was modified and implemented to solve the problem of minimizing the flow deviations using feasible sequential quadratic programming for three reservoirs in the Chattahoochee River Basin, Southeastern United States, which is known for its imperiled native biodiversity and productive estuarine ecosystem. Our results show that downstream reservoirs in the cascade system are less influenced by upstream reservoirs’ regulation because the downstream reservoirs receive a significant amount of natural flows. By comparing the average wavelet power spectrum at different periodicities between natural flows and downstream releases, we found that the current release policy and modified releases resulted in highly altered flows under shorter periodicities (e.g., less than 2 months) but synchronized flow variance between natural flow and downstream releases at longer periodicities (e.g., greater than 3 years). This framework of linking the multireservoir allocation model through the time–frequency analysis using wavelet power spectrum could not only advance sustainable water management policies to meet water for human and environmental needs but can also add additional value in meeting the downstream environmental demand at desired periodicities.

","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/JWRMD5.WRENG-7006","usgsCitation":"Chalise, D.R., Ford, L., Mahinthakumar, K., Ranjithan, R., Eaton, M.J., and Sankarasubramanian, A., 2026, Multireservoir allocation framework considering societal and ecological needs in a time-frequency domain: Journal of Water Resources Planning and Management, v. 152, no. 5, 04026007, 17 p., https://doi.org/10.1061/JWRMD5.WRENG-7006.","productDescription":"04026007, 17 p.","ipdsId":"IP-167436","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500668,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Chattahoochee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.6901375420256,\n 34.842920854432904\n ],\n [\n -85.6563734170193,\n 32.17035099082393\n ],\n [\n -85.36681091699252,\n 29.6298014571195\n ],\n [\n -84.66969319706918,\n 29.670744490356427\n ],\n [\n -84.5477651592313,\n 30.701515393857616\n ],\n [\n -83.81773860252564,\n 31.585948009453666\n ],\n [\n -83.63233065888338,\n 34.78148617202561\n ],\n [\n -84.6901375420256,\n 34.842920854432904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"152","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chalise, Dol Raj","contributorId":367072,"corporation":false,"usgs":false,"family":"Chalise","given":"Dol","middleInitial":"Raj","affiliations":[{"id":87532,"text":"Mesa Associates Inc; NC State Univ.","active":true,"usgs":false}],"preferred":false,"id":956699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, Lucas","contributorId":367073,"corporation":false,"usgs":false,"family":"Ford","given":"Lucas","affiliations":[{"id":87533,"text":"NC State Univ","active":true,"usgs":false}],"preferred":false,"id":956700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahinthakumar, Kumar","contributorId":367074,"corporation":false,"usgs":false,"family":"Mahinthakumar","given":"Kumar","affiliations":[{"id":87533,"text":"NC State Univ","active":true,"usgs":false}],"preferred":false,"id":956701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ranjithan, Ranji","contributorId":367075,"corporation":false,"usgs":false,"family":"Ranjithan","given":"Ranji","affiliations":[{"id":87534,"text":"NC State Unive","active":true,"usgs":false}],"preferred":false,"id":956702,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":956703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankarasubramanian, A. 0000-0002-7668-1311","orcid":"https://orcid.org/0000-0002-7668-1311","contributorId":241034,"corporation":false,"usgs":false,"family":"Sankarasubramanian","given":"A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":956704,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274079,"text":"70274079 - 2026 - Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software","interactions":[],"lastModifiedDate":"2026-02-24T14:51:38.936114","indexId":"70274079","displayToPublicDate":"2026-02-23T07:42:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software","docAbstract":"

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes Mw ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 Mw 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the Mw 8.3 Illapel earthquake example here.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250055","usgsCitation":"Goldberg, D.E., Hunsinger, H., Koch, P., Haynie, K.L., Melgar, D., Riquelme, S., 2026, Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software: Seismological Research Letters, 17 p., https://doi.org/10.1785/0220250055.","productDescription":"17 p.","ipdsId":"IP-183439","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":500754,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14RVF65","text":"USGS data release","linkHelpText":"Wavelet Inversion for SliP (WISP)"},{"id":500598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250055","text":"Publisher Index Page"},{"id":500475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.2915060047295,\n -27.438162221295535\n ],\n [\n -73.2915060047295,\n -36.968704795768254\n ],\n [\n -70.94626168478015,\n -36.968704795768254\n ],\n [\n -70.94626168478015,\n -27.438162221295535\n ],\n [\n -73.2915060047295,\n -27.438162221295535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":956480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunsinger, Heather Elizabeth 0000-0001-7700-9087","orcid":"https://orcid.org/0000-0001-7700-9087","contributorId":352844,"corporation":false,"usgs":true,"family":"Hunsinger","given":"Heather Elizabeth","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":956481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Pablo","contributorId":294680,"corporation":false,"usgs":false,"family":"Koch","given":"Pablo","email":"","affiliations":[{"id":63624,"text":"National Seismological Center, University of Chile","active":true,"usgs":false}],"preferred":false,"id":956482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haynie, Kirstie Lafon 0000-0001-9930-6736","orcid":"https://orcid.org/0000-0001-9930-6736","contributorId":289894,"corporation":false,"usgs":true,"family":"Haynie","given":"Kirstie","email":"","middleInitial":"Lafon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":956483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melgar, Diego","contributorId":341315,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":956484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riquelme, Sebastian","contributorId":193028,"corporation":false,"usgs":false,"family":"Riquelme","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":956485,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274555,"text":"70274555 - 2026 - Detecting volcanic deformation in Hawaii using trustworthy multimodal deep learning techniques","interactions":[],"lastModifiedDate":"2026-04-01T21:01:29.164156","indexId":"70274555","displayToPublicDate":"2026-02-21T13:51:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Detecting volcanic deformation in Hawaii using trustworthy multimodal deep learning techniques","docAbstract":"

Monitoring volcanoes involves a variety of data sources and methods to maintain complete continuity of coverage. Global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) are commonly used complementary methods to assess the deformation state of a volcano as magma migrates beneath the surface. The amount of data these methods produce, however, is growing rapidly beyond human analysis capabilities and is becoming difficult to manage. Here, we create a novel multimodal deep learning framework to ingest InSAR and GNSS data simultaneously and classify the deformation state of the system. We apply this methodology to Mauna Loa, Hawai‘i given its wealth of InSAR and GNSS data as well as its propensity to deform on multiple timescales. Our model performs with high accuracy and is able to identify both slow and fast deformation from 2015 to 2023. The multimodal nature of our model also allows us to identify the presence of atmospheric noise in InSAR data. Furthermore, we employ explainability algorithms to show that our model is making decisions for the right reasons and to connect complex black-box machine learning mappings to current real-world geodetic interpretations of the Mauna Loa magmatic system.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-026-01950-4","usgsCitation":"Paladino, T.G., Montgomery-Brown, E.K., Bagnardi, M., Poland, M., and Lee, R.L., 2026, Detecting volcanic deformation in Hawaii using trustworthy multimodal deep learning techniques: Bulletin of Volcanology, v. 88, 28, 22 p., https://doi.org/10.1007/s00445-026-01950-4.","productDescription":"28, 22 p.","ipdsId":"IP-182889","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":502055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-026-01950-4","text":"Publisher Index Page"},{"id":501966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.65407582020632,\n 19.593816099063176\n ],\n [\n -155.65407582020632,\n 19.422897333729793\n ],\n [\n -155.4098890103293,\n 19.422897333729793\n ],\n [\n -155.4098890103293,\n 19.593816099063176\n ],\n [\n -155.65407582020632,\n 19.593816099063176\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","noUsgsAuthors":false,"publicationDate":"2026-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Paladino, Tyler Grant 0000-0002-5443-8046","orcid":"https://orcid.org/0000-0002-5443-8046","contributorId":364568,"corporation":false,"usgs":true,"family":"Paladino","given":"Tyler","middleInitial":"Grant","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":958277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":958278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagnardi, Marco 0000-0002-4315-0944","orcid":"https://orcid.org/0000-0002-4315-0944","contributorId":335933,"corporation":false,"usgs":true,"family":"Bagnardi","given":"Marco","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":958279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":958280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, R. Lopaka 0000-0002-6352-0340","orcid":"https://orcid.org/0000-0002-6352-0340","contributorId":223777,"corporation":false,"usgs":true,"family":"Lee","given":"R.","email":"","middleInitial":"Lopaka","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":958281,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274234,"text":"70274234 - 2026 - Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)","interactions":[],"lastModifiedDate":"2026-03-23T14:22:57.40506","indexId":"70274234","displayToPublicDate":"2026-02-20T14:04:35","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)","title":"Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)","docAbstract":"

Crayfish are critical functional components of aquatic ecosystems. Previous research has documented adverse effects of mineral extraction on crayfish. Here, we characterize potential risks of mining-derived waterborne nickel (Ni) to crayfish by documenting the effects of dissolved Ni on growth and food consumption of juvenile virile crayfish (Faxonius virilis) in a 28-day chronic laboratory exposure. Nominal Ni concentrations ranged from 31.25 to 500 micrograms per liter (µg/L; pH = 7.96 ± 0.20, hardness = 150 ± 1 milligrams per liter as calcium carbonate). Crayfish survival, carapace length, and wet weight were measured. After 28 days of exposure, a 24-h feeding trial was performed to determine differences in food consumption. During the growth trial, 99% of crayfish survived. Change in wet weight and final wet weight were the most sensitive endpoints, with 20% effect concentrations of 24.8 and 22.6 µg/L Ni, respectively. Crayfish exposed to an average of 438 µg/L Ni consumed 41% less, and weighed 65.1% less, than control crayfish. These results suggest chronic, sublethal exposure to waterborne Ni may have negative effects on crayfish growth. Reduced growth and consumption rates in crayfish could have wide-ranging consequences throughout aquatic ecosystems since crayfish are consumers, prey, keystone trophic regulators, and ecosystem engineers. Finally, these results could inform bioenergetics and may be coupled with population models to predict potential changes in population sizes of native and invasive crayfishes.

","language":"English","publisher":"Springer","doi":"10.1007/s10646-026-03036-5","usgsCitation":"Moore, A.P., Wildhaber, M.L., Beaman, Z.D., Bennett, K.R., Ditter, K.K., Cleveland, D.M., Blanton, J., and Grant, T.J., 2026, Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis): Ecotoxicology, v. 35, 64, https://doi.org/10.1007/s10646-026-03036-5.","productDescription":"64","ipdsId":"IP-179855","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":501386,"rank":4,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274234/full"},{"id":501385,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274234/images/"},{"id":501384,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274234/70274234.XML"},{"id":501228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2026-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Adrian Parr 0000-0001-9277-6399","orcid":"https://orcid.org/0000-0001-9277-6399","contributorId":298590,"corporation":false,"usgs":true,"family":"Moore","given":"Adrian","email":"","middleInitial":"Parr","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beaman, Zachary D 0000-0001-9649-1585","orcid":"https://orcid.org/0000-0001-9649-1585","contributorId":312457,"corporation":false,"usgs":true,"family":"Beaman","given":"Zachary","email":"","middleInitial":"D","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Kendell Ray 0000-0001-6081-7002","orcid":"https://orcid.org/0000-0001-6081-7002","contributorId":334116,"corporation":false,"usgs":true,"family":"Bennett","given":"Kendell","email":"","middleInitial":"Ray","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ditter, Karlie K 0000-0001-8970-2022","orcid":"https://orcid.org/0000-0001-8970-2022","contributorId":312455,"corporation":false,"usgs":true,"family":"Ditter","given":"Karlie","email":"","middleInitial":"K","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":957114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blanton, J.","contributorId":89345,"corporation":false,"usgs":true,"family":"Blanton","given":"J.","email":"","affiliations":[],"preferred":false,"id":957115,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grant, Tyler J.","contributorId":149938,"corporation":false,"usgs":false,"family":"Grant","given":"Tyler","email":"","middleInitial":"J.","affiliations":[{"id":17858,"text":"Iowa State U, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":957116,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274574,"text":"70274574 - 2026 - Trust-building as a keystone activity in beaver-related restoration practice","interactions":[],"lastModifiedDate":"2026-04-01T16:37:12.595073","indexId":"70274574","displayToPublicDate":"2026-02-20T09:28:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Trust-building as a keystone activity in beaver-related restoration practice","docAbstract":"

North American beavers (Castor canadensis) are increasingly being used to achieve restoration goals, prompting practitioners to engage with private landowners in efforts to promote beaver coexistence. Through 23 semi-structured interviews with restoration practitioners in Oregon, USA, we explored how practitioners from government agencies, non-governmental organizations (NGOs), service organizations, and private businesses communicate with private landowners about nonlethal beaver management and habitat creation. Using abductive analysis, we identified trust-building as an essential element of restoration practice. Practitioners described 60 tactics for building trust, which we organized using the Shared Foundations model of trust and distrust and the adaptive management cycle to bridge theory with field-based experience. Practitioners also reported navigating tensions between tactics and adapting their approaches to individual landowners and contexts. We argue that trust-building is a craft that can be mastered, propose a potential progression from novice to master trust-builder, and highlight the need for greater attention to trust, relationships, and trust repair in environmental management. Our findings offer a theoretically grounded yet practitioner-informed framework for understanding and improving trust-building efforts in restoration practice.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00267-026-02400-9","usgsCitation":"Erickson, B.D., and Jones, M.S., 2026, Trust-building as a keystone activity in beaver-related restoration practice: Environmental Management, v. 76, 110, 16 p., https://doi.org/10.1007/s00267-026-02400-9.","productDescription":"110, 16 p.","ipdsId":"IP-184779","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-026-02400-9","text":"Publisher Index Page"},{"id":501952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.23853076911831,\n 46.240570035688165\n ],\n [\n -124.67829678787554,\n 42.66685258151891\n ],\n [\n -124.39381012914876,\n 41.995038024510364\n ],\n [\n -117.01230604375972,\n 41.97025659471865\n ],\n [\n -117.06282012339243,\n 44.48762153969409\n ],\n [\n -116.30658335589958,\n 45.585850866979015\n ],\n [\n -116.59266632544107,\n 46.0641293518556\n ],\n [\n -124.23853076911831,\n 46.240570035688165\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"76","noUsgsAuthors":false,"publicationDate":"2026-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Brian D.","contributorId":369042,"corporation":false,"usgs":false,"family":"Erickson","given":"Brian","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958344,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274039,"text":"70274039 - 2026 - American kestrel population trends and vital rates at the continental scale","interactions":[],"lastModifiedDate":"2026-02-23T17:22:11.732582","indexId":"70274039","displayToPublicDate":"2026-02-19T11:16:41","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"American kestrel population trends and vital rates at the continental scale","docAbstract":"

The American kestrel (Falco sparverius, hereafter referred to as kestrel) has declined across much of its North American range since at least the mid-1960s. Kestrel population dynamics have been explored through a multitude of local studies and two broad reviews of available data. Across large geographic extents, however, the demographic cause(s) of kestrel population declines remain(s) largely unknown. As part of a collaborative effort to elucidate the drivers of kestrel population declines, we developed a continental-scale integrated population model using band-recovery data, productivity data, and Breeding Bird Survey indices from 1986 to 2019 to estimate indices of annual population sizes, survival, and productivity rates across the continental United States. We detected a decline in population size of ~1%–2% per year. Overall estimates of population growth from 1986 to 2019 suggest a 29% decline in population size (95% CI = −34% to −23%). There was little evidence of a trend in brood size. However, survival of juvenile birds (mean = −0.015, SD = 0.008 and mean = −0.024, SD = 0.010 for females and males, respectively) and adult males (mean = −0.016, SD = 0.010) in the summer declined, suggesting that these vital rates could be contributing to declines in populations over time. Winter adult survival rates (mean = −0.004, SD = 0.009 and mean = −0.009, SD = 0.010 for females and males, respectively) also declined but to a lesser extent than summer survival. For juvenile birds, winter survival increased (mean = 0.006, SD = 0.008 and mean = 0.002, SD = 0.009 for females and males, respectively); however, this was not enough to offset declines in summer survival and annual survival rates declined over the time series. Annual adult survival was also low relative to previous research on kestrel survival rates. Given the importance of survival to population trends, our findings provide support for several previously proposed broad classes of factors potentially contributing to observed population declines: declines in arthropod prey, second-generation rodenticides, neonicotinoid insecticides, and predation.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70526","usgsCitation":"Howell, P.E., Lawson, A.J., Davis Kristin P., Zimmerman, G.S., Robinson, O.J., Boggie, M.A., Eaton, M.J., Abadi, F., Brown, J.L., Heath, J.A., Smallwood, J.A., Steenhof, K., Swem, T., Rolek, B.W., McClure, C.J., Therrien, J., Miller, K.E., Milsap, B.A., 2026, American kestrel population trends and vital rates at the continental scale: Ecosphere, v. 17, no. 2, e70526, 18 p., https://doi.org/10.1002/ecs2.70526.","productDescription":"e70526, 18 p.","ipdsId":"IP-166530","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500756,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FDMI2L","text":"USGS data release","linkHelpText":"A continental-scale integrated population model for the American 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Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

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Artificial intelligence (AI) can offer opportunities to enhance the science, science delivery, and business operations of the U.S. Geological Survey (USGS). Although USGS staff have proactively adopted AI into our workflows for many years, a comprehensive USGS strategy for AI has not previously been developed. The strategy described here is motivated by the acceleration of AI technological development, the benefits of increased AI adoption to USGS mission delivery as anticipated by USGS staff, rising public concern about the implications and trustworthiness of AI, and emerging Federal directives and guidance about AI. The USGS vision is to continue integrating AI to deliver valuable science for the public good while maintaining high ethical standards, scientific quality and integrity, and compliance with Federal and U.S. Department of the Interior requirements. To realize this vision, the USGS can take steps to (1) develop a strong AI workforce, (2) adapt our organizational approaches to include AI governance and communication, (3) ensure responsible and trustworthy use of AI, (4) modernize our computing and data infrastructure to support AI, and (5) accelerate AI adoption and innovation in the Bureau.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1562","usgsCitation":"Gordon, J.M., Appling, A.P., Aretxabaleta, A., Bechtell, J.F., Burley, T.E., Carter, J.M., Esselman, P.C., Fisher, J.C., Lederer, G.W., Mitchell, J.M., Pastick, N.J., Weltzin, J., and Woods, T., 2026, Artificial intelligence strategy for the U.S. Geological Survey: U.S. Geological Survey Circular 1562, 14 p., https://doi.org/10.3133/cir1562.","productDescription":"iv, 14 p.","onlineOnly":"Y","ipdsId":"IP-173214","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":500162,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1562/cir1562.xml"},{"id":500469,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1562/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1562"},{"id":499803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1562/cir1562.pdf","text":"Report","size":"2.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1562"},{"id":499802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1562/coverthb2.jpg"},{"id":500161,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1562/images"}],"contact":"

Director, Science Analytics and Synthesis Program
U.S. Geological Survey
2P.O. Box 25046, Mail Stop 302
Denver, CO 80225

","tableOfContents":"","publishedDate":"2026-02-18","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Gordon, Janice M. 0000-0001-9729-863X","orcid":"https://orcid.org/0000-0001-9729-863X","contributorId":350521,"corporation":false,"usgs":true,"family":"Gordon","given":"Janice","middleInitial":"M.","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":955419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":955420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":955421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bechtell, John F. 0009-0009-4237-3386","orcid":"https://orcid.org/0009-0009-4237-3386","contributorId":366205,"corporation":false,"usgs":false,"family":"Bechtell","given":"John","middleInitial":"F.","affiliations":[{"id":87382,"text":"Department of the Interior, Office of the Chief Information Officer (OCIO)","active":true,"usgs":false}],"preferred":false,"id":955422,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burley, Thomas E. 0000-0002-2235-8092","orcid":"https://orcid.org/0000-0002-2235-8092","contributorId":366206,"corporation":false,"usgs":false,"family":"Burley","given":"Thomas","middleInitial":"E.","affiliations":[{"id":87382,"text":"Department of the Interior, Office of the Chief Information Officer (OCIO)","active":true,"usgs":false}],"preferred":false,"id":955423,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carter, Janet M. 0000-0002-6376-3473","orcid":"https://orcid.org/0000-0002-6376-3473","contributorId":366207,"corporation":false,"usgs":false,"family":"Carter","given":"Janet","middleInitial":"M.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":955424,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955425,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955426,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":955427,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mitchell, James M. 0009-0008-7949-0466","orcid":"https://orcid.org/0009-0008-7949-0466","contributorId":366208,"corporation":false,"usgs":true,"family":"Mitchell","given":"James","middleInitial":"M.","affiliations":[{"id":87383,"text":"Office of the AD Administration and Enterprise Information","active":true,"usgs":true}],"preferred":true,"id":955428,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pastick, Neal J. 0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":267275,"corporation":false,"usgs":false,"family":"Pastick","given":"Neal","middleInitial":"J.","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":955429,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Weltzin, Jake 0000-0001-8641-6645","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":365438,"corporation":false,"usgs":false,"family":"Weltzin","given":"Jake","affiliations":[{"id":87138,"text":"formerly Senior Science Advisor, EMA, USGS, now retired.","active":true,"usgs":false}],"preferred":false,"id":955430,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Woods, Tim 0009-0005-0291-1902","orcid":"https://orcid.org/0009-0005-0291-1902","contributorId":366209,"corporation":false,"usgs":false,"family":"Woods","given":"Tim","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":955431,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70273927,"text":"sir20265114 - 2026 - Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study","interactions":[],"lastModifiedDate":"2026-03-18T21:13:34.944932","indexId":"sir20265114","displayToPublicDate":"2026-02-18T12:45:00","publicationYear":"2026","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":"2026-5114","displayTitle":"Assessing Natural Recharge in Indian Wells Valley, California: A Basin Characterization Model Case Study","title":"Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study","docAbstract":"

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm3) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot- wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265114","collaboration":"Prepared in cooperation with Kern County, California","programNote":"Water Availability and Use Science Program","usgsCitation":"Saleh, D., Flint, L., and Stern, M., 2026, Assessing natural recharge in Indian Wells Valley, California—A Basin Characterization Model case study (ver. 1.1, March 2026): U.S. Geological Survey Scientific Investigations Report 2026–5114, 34 p., https://doi.org/10.3133/sir20265114.","productDescription":"vi, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-104255","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":501283,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119214.htm","linkFileType":{"id":5,"text":"html"}},{"id":501282,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2026/5114/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2026-5114 Version History"},{"id":501281,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5114/images"},{"id":501278,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5114 PDF"},{"id":501279,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265114/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5114 HTML"},{"id":501280,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5114/sir20265114.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5114 XML"},{"id":500366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5114/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Indian Wells Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.5,\n 36.5\n ],\n [\n -118.5,\n 35\n ],\n [\n -117,\n 35\n ],\n [\n -117,\n 36.5\n ],\n [\n -118.5,\n 36.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: February 18, 2026; Version 1.1: March 18, 2026","contact":"

Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2026-02-18","revisedDate":"2026-03-18","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Saleh, Dina 0000-0002-1406-9303 dsaleh@usgs.gov","orcid":"https://orcid.org/0000-0002-1406-9303","contributorId":939,"corporation":false,"usgs":true,"family":"Saleh","given":"Dina","email":"dsaleh@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":306090,"corporation":false,"usgs":false,"family":"Flint","given":"Lorraine","email":"","middleInitial":"E.","affiliations":[{"id":66369,"text":"Earth Knowledge, Inc.","active":true,"usgs":false}],"preferred":false,"id":955784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955785,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273951,"text":"70273951 - 2026 - A comparison of non-contact methods for measuring turbidity in the Colorado River","interactions":[],"lastModifiedDate":"2026-02-19T15:20:49.499432","indexId":"70273951","displayToPublicDate":"2026-02-18T09:13:10","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of non-contact methods for measuring turbidity in the Colorado River","docAbstract":"

Monitoring suspended-sediment concentration (SSC) is essential to better understand how sediment transport could adversely affect water availability for human communities and ecosystems. Aquatic remote sensing methods are increasingly utilized to estimate SSC and turbidity in rivers; however, an evaluation of their quantitative performance is limited. This study evaluates the performance of three multispectral sensors, which vary in resolution and ease of deployment, to estimate turbidity in the Colorado River: the Multispectral Instrument (MSI) on board the European Space Agency’s Sentinel-2 satellite, an industrial-grade 10-band dual camera system mounted on a cable car, and a consumer-grade 6-band dual camera system positioned on the riverbank. We use multivariate linear regression to compare in situ turbidity measurements with concurrent spectral reflectance data from each sensor. Models for all three sensors selected similar spectral information and resulted in mean errors <35% in predicting turbidity. A cross-sensor comparison showed that little accuracy is lost when applying models developed for satellite-based systems to ground-based systems, and vice versa. Transferability of satellite-based models to ground-based systems could support continuous water-quality monitoring between satellite overpasses and avoid issues associated with cloud interference. Conversely, continuously operating ground-based systems could be used to rapidly establish datasets and models for application in satellite imagery, thus accelerating remote sensing applications. The encouraging performance of the consumer-grade system indicates that SSC could be monitored for low cost.

","language":"English","publisher":"MDPI","doi":"10.3390/rs18040638","usgsCitation":"Day, N.K., King, T.V., and Mosbrucker, A.R., 2026, A comparison of non-contact methods for measuring turbidity in the Colorado River: Remote Sensing, v. 18, no. 4, 638, 26 p., https://doi.org/10.3390/rs18040638.","productDescription":"638, 26 p.","ipdsId":"IP-177709","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":500256,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18040638","text":"Publisher Index Page"},{"id":500184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Cameo","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.22,\n 39.26\n ],\n [\n -108.5833,\n 39.26\n ],\n [\n -108.5833,\n 39\n ],\n [\n -108.22,\n 39\n ],\n [\n -108.22,\n 39.26\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":292424,"corporation":false,"usgs":true,"family":"King","given":"Tyler","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":955901,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274549,"text":"70274549 - 2026 - Channel change and sediment transport in the Puyallup River watershed through 2022","interactions":[],"lastModifiedDate":"2026-03-31T13:38:43.216394","indexId":"70274549","displayToPublicDate":"2026-02-18T08:35:50","publicationYear":"2026","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Channel change and sediment transport in the Puyallup River watershed through 2022","docAbstract":"

The Puyallup River drains a 990 square mile watershed in western Washington, with headwaters on the glacier-covered flanks of Mount Rainier. Major tributaries include the White, Carbon, and Mowich Rivers. In the levee-confined reaches of the lower watershed, loss of flood conveyance due to sand and gravel deposition has been a chronic issue. Over much of the 20th century, flood conveyance was maintained through sediment removal, but this practice ended in the late 1990s. Flood hazard management activities since the 1990s have primarily involved levee removal or setback projects. Assessments of 1984-2009 repeat cross sections suggested that sediment deposition rates were particularly high in reaches with recent levee setbacks. However, there have been no assessments of recent deposition rates since the 2009 surveys. There are also concerns that intensifying flood hydrology or increased sediment delivery from Mount Rainier may exacerbate deposition. However, assessment of those risks has been hindered by limited understanding of watershed-scale sediment delivery and routing, particularly for coarse sand and gravel.

The U.S. Geological Survey, in cooperation with Pierce County, initiated this study to improve understanding of sediment deposition in the lower Puyallup River watershed. This work is primarily based on differencing of multiple aerial lidar datasets collected during 2002–2022, supplemented by early 1990 photogrammetric elevation datasets, geomorphic assessments of streamgage data, historical topographic surveys from 1907, and previously collected sediment transport measurements. Analyses cover the Puyallup, Carbon, and Mowich Rivers, but do not include the White River.

During 2004–2020, repeat aerial lidar indicates that 1.3 ± 0.3 million yd3 of sediment accumulated in the lower 20 valley miles (VMs) of the Puyallup River, averaging 80,000 ± 20,000 cubic yards per year (yd3/yr). Deposition was observed during both 2004–11 and 2011–20 lidar differencing intervals. This continued a long-term depositional trend that extends back to at least 1977. From 2004 to 2011, deposition rates along the Soldiers Home levee setback reach, the only setback project downstream of VM 20 completed prior to 2011, were approximately four times higher than in adjacent unmodified reaches. From 2011 to 2020, two additional setback projects were completed; volumetric deposition rates over all three setback reaches were similar to adjacent unmodified reaches, suggesting elevated setback deposition in the 2004–11 interval may have been influenced by an extreme flood in November 2006. These levee setback projects increased the local cross-sectional area of the floodway, used as a rough proxy for relative flood conveyance, by 50 to 200 percent above 2004 conditions. If deposition continued at recent rates, cross-sectional area over the levee setback reaches would be reduced back to 2004 values by 2050-90.

Deposition also occurred over the lower six VMs of the Carbon River during 2004–20, though volumes (0.15 ± 0.09 million yd3) were an order of magnitude lower than along the Puyallup River. Relatively lower deposition rates in the Carbon River are most likely the combined result of modestly lower incoming sediment loads, modestly steeper channel slope, and the additional sediment transport capacity provided by two large non-glacial tributaries that enter the Carbon River near VM 5.

Upstream of the depositional reaches described above, 2002–22 sediment storage trends along the Puyallup, Carbon, and Mowich Rivers were predominately negative (net erosion) up to the Mount Rainier National Park boundary. Net erosion was the result of bank and bluff erosion exceeding deposition across wetted channel and bare gravel areas, as opposed to uniform vertical downcutting. Net erosion along these river valleys delivered 3.4 ± 0.6 million yd3 to the river system, equivalent to 190,000 ± 35,000 yd3/yr. Most of that volume was supplied by erosion of relatively low (4–10 ft) surfaces along the Puyallup and Mowich Rivers and tall (300 ft) glacial bluffs along the lower Carbon River. Substantial aggradation from 1984 to 2009 reported by Czuba and others (2010) along reaches of the Puyallup River (VM 19–22) where levee confinement has recently been removed was most likely an artifact of methodologic bias.

The Puyallup, Mowich, and Carbon Rivers drain five distinct glaciated watersheds on the flanks of Mount Rainier, four of which were assessed in this study. All four watersheds were impacted by an extreme November 2006 rainstorm. Between 2002 and 2008, debris flows occurred in all four headwater areas, collectively eroding at least 2.1 million yd3 of sediment. These debris flows formed distinct deposits one to two miles downstream of source areas, depositing 30-50 percent of the material eroded upstream. From 2008 to 2022, no headwater debris flows were observed and overall rates of geomorphic change in the headwaters were low. Rivers eroded into debris flow deposits emplaced over the 2002–08 interval, but re-deposited equivalent volumes of material within a half mile downstream.

Stage-discharge relations at five streamgages on upland rivers draining Mount Rainier show either net channel incision or dynamic variability with no long-term trend over the past 60–100 years. Observations of pervasive river valley erosion and stable or incising trends at long-term streamgages in the upper watershed do not support prior claims of widespread and accelerating aggradation of upland rivers draining Mount Rainier.

Erosion and deposition volumes estimated in this report were combined with sediment transport estimates from limited suspended sediment and bedload measurements, estimates of sub-glacial erosion rates, and sediment delivery from non-glacial tributaries to construct watershed-scale sediment budgets for the Puyallup River watershed. During 2004–20, the estimated sediment load entering the depositional lowlands was well balanced by estimated inputs from, in order of relative magnitude, subglacial erosion (33–60 percent of total sediment load), erosion along the major river valleys (25–45 percent), erosion in recently deglaciated headwater areas (7–17 percent) and non-glacial tributaries (3–9 percent). These results are specific to the study period and represent total sediment loads, most of which is fine material carried in suspension. The relative sourcing of sand and gravel may be different than implied by this sediment budget.

Downstream of VM 12, comparison of 1907 and 2009 channel surveys show net lowering of the channel thalweg of 4–12 ft. A long-term gage near VM 22 shows lowering of 4–5 ft through the 1960s. Lowering at both locations was inferred to be a channel response to the substantial straightening, and so steepening, of the river during major phases of levee construction through the early and mid-20th century.

Application of a simple empirical bedload-discharge power-law relation to an ensemble of model-estimated daily mean discharge records in the lower Puyallup River between 1977 and 2100 projects that annual bedload transport capacity in the lower Puyallup River will increase by 20–60 percent by the middle of the 21st century. Actual changes in bedload transport and deposition rates will depend on concurrent changes in sediment supply and local hydraulics governing deposition.

This report presents several key conclusions. First, the persistence and spatial patterns of sand and gravel deposition along the lower Puyallup River support prior claims that deposition is fundamentally caused by decreases in channel slope moving downstream. Given this underlying cause and the abundance of sand and gravel available to be transported downstream, deposition is likely to continue for the foreseeable future. Second, despite continued sediment deposition, recent levee setback projects in the lower Puyallup River will likely provide several decades of flood conveyance benefits relative to a no-action alternative. Third, while the rivers linking Mount Rainier to the Puget Sound lowlands have often been discussed as conduits that either pass or accumulate sediment from Mount Rainier, observations from 2002–22 show these river valleys acting as substantial sediment sources, delivering three times more sediment than recently deglaciated headwater areas on Mount Rainier. While the persistence and underlying cause of recent river valley erosion remain unknown, sediment storage dynamics along these river valleys are likely to be a major control on sand and gravel delivery to the lower watershed.

","language":"English","publisher":"EarthArXiv","doi":"10.31223/X5HR0N","usgsCitation":"Anderson, S.W., 2026, Channel change and sediment transport in the Puyallup River watershed through 2022: EarthArXiv, preprint posted February 18, 2026, https://doi.org/10.31223/X5HR0N.","productDescription":"189 p.","ipdsId":"IP-180215","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":501853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958251,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273944,"text":"70273944 - 2026 - Decreased water transparency of nearshore Laurentian Great Lakes habitats is driven by increased dissolved organic carbon.","interactions":[],"lastModifiedDate":"2026-02-19T15:40:54.381085","indexId":"70273944","displayToPublicDate":"2026-02-18T08:33:12","publicationYear":"2026","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":"Decreased water transparency of nearshore Laurentian Great Lakes habitats is driven by increased dissolved organic carbon.","docAbstract":"

Little is understood of lake browning (due to increased dissolved organic carbon; DOC) in large lakes such as the Laurentian Great Lakes. Lake browning can alter whole lake ecosystems, including decreasing exposure to damaging ultraviolet radiation (UV-B) which is strongly and selectively attenuated by DOC more so than photosynthetically active radiation (PAR). We compared the changes in UV-B and PAR transparency to DOC data collected during the ice-free seasons from 62 nearshore sites in four of the five Great Lakes from 2002 to 2022 using linear mixed effects regression models based on backwards selected Bayesian information criteria. Regionally, DOC significantly increased from 2002 to 2022 by 0.5% per year on average. DOC strongly and inversely explained the variability of UV-B and PAR transparencies, as did seasons and offshore influence on these habitats. We provide regional evidence of lake browning within the nearshore habitats of the Great Lakes as a strong contrast to the well-documented increased offshore water transparency associated with the spread of invasive dreissenid mussels.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0407","usgsCitation":"Berry, N., Bunnell, D.B., Fisher, T., Overholt, E., Mette, E., Howell, T., and Williamson, C.E., 2026, Decreased water transparency of nearshore Laurentian Great Lakes habitats is driven by increased dissolved organic carbon.: Canadian Journal of Fisheries and Aquatic Sciences, v. 83, p. 1-9, https://doi.org/10.1139/cjfas-2024-0407.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-170502","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":500258,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0407","text":"Publisher Index Page"},{"id":500189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.84751857840234,\n 49.471311017762645\n ],\n [\n -92.81669615927237,\n 46.920316633964475\n ],\n [\n -91.56012545582533,\n 46.18295137477036\n ],\n [\n -87.0507208161673,\n 46.41933841908485\n ],\n [\n -88.74219710454639,\n 43.914354385501326\n ],\n [\n -87.95935986459418,\n 41.59912997740622\n ],\n [\n -83.9720223229704,\n 41.37139907143079\n ],\n [\n -81.15069356336562,\n 40.86644441718417\n ],\n [\n -78.58068940433992,\n 42.033414801353516\n ],\n [\n -75.56437638284248,\n 43.19976943418763\n ],\n [\n -76.07811679933005,\n 44.5165607788128\n ],\n [\n -79.06374555874787,\n 44.2536538155133\n ],\n [\n -79.2312465353583,\n 46.384270370895024\n ],\n [\n -83.12440166219844,\n 46.77820657483097\n ],\n [\n -84.46202674663817,\n 48.73561539687698\n ],\n [\n -88.84751857840234,\n 49.471311017762645\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Nicole Lynn 0000-0002-7889-197X","orcid":"https://orcid.org/0000-0002-7889-197X","contributorId":347450,"corporation":false,"usgs":true,"family":"Berry","given":"Nicole Lynn","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216540,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Thomas J. 0000-0001-5885-7646","orcid":"https://orcid.org/0000-0001-5885-7646","contributorId":347464,"corporation":false,"usgs":false,"family":"Fisher","given":"Thomas J.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Overholt, Erin P. 0000-0001-9078-7086","orcid":"https://orcid.org/0000-0001-9078-7086","contributorId":347452,"corporation":false,"usgs":false,"family":"Overholt","given":"Erin P.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mette, Elizabeth M. 0009-0007-9622-1260","orcid":"https://orcid.org/0009-0007-9622-1260","contributorId":347466,"corporation":false,"usgs":false,"family":"Mette","given":"Elizabeth M.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howell, Todd","contributorId":294685,"corporation":false,"usgs":false,"family":"Howell","given":"Todd","affiliations":[{"id":63627,"text":"Ontario Ministry of Environment and Climate Change","active":true,"usgs":false}],"preferred":false,"id":955882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williamson, Craig E. 0000-0001-7350-1912","orcid":"https://orcid.org/0000-0001-7350-1912","contributorId":347472,"corporation":false,"usgs":false,"family":"Williamson","given":"Craig","middleInitial":"E.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":955883,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274031,"text":"70274031 - 2026 - Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections","interactions":[],"lastModifiedDate":"2026-02-20T15:05:09.255266","indexId":"70274031","displayToPublicDate":"2026-02-18T07:59:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23303,"text":"ESA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections","docAbstract":"The increasing uncertainty with global change often stifles action and results in calls for more data before moving beyond status quo environmental decisions (Mahapatra & Ratha 2017; Ripple et al. 2017; Montefalcone et al. 2025). Advancing science and collecting more data is crucial; however, science alone (i.e., “western” or “positivist” science, as described in Fuller, 2001; Reid et al. 2020) may be insufficient to reduce uncertainty to a comfortable level for decision making. Therefore, increasing personal and collective capacity to make proactive decisions may require decision makers to recognize that their own understanding of the world, and therefore interpretation of scientific data, is influenced by all Four Realms of human perception: Physical, Mental, Emotional, and Transcendental (Wolf 2017; Dukes et al. 2021; Clifford et al. 2022).\nIn the ESA Special Session, Action in Uncertainty, we introduced four questions to help participants increase cognitive awareness of how all Four Realms may affect their understanding in uncertain environmental decision contexts:\n\n1. Physical: How do I observe uncertainty through the five senses (feel, see, hear, taste, smell)?\nThe physical realm is what people observe, including ecological data observations and\nexperimentation.\n\n2. Mental: How do I think about uncertainty using logic, reason, and language-based\nunderstanding? The mental realm is how people think about the world, including scientific\ntheory, modeling, and decision frameworks.\n\n3. Emotional: How do I feel in uncertainty? The emotional realm is a person’s subjective emotional state, such as fear, curiosity, defensiveness, and awe.\n\n4. Transcendental: How do I connect to something greater than myself in uncertainty? The\ntranscendental realm includes people’s sense of purpose, responsibility for others, or moral\ncode.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/bes2.70071","usgsCitation":"Ward, N.K., Guilbeau, K.G., Sesser, A.L., Lynch, A.J., 2026, Action in uncertainty: Data-driven decisions that acknowledge emotional responses and transcendental connections: ESA Bulletin, e70071, 10 p., https://doi.org/10.1002/bes2.70071.","productDescription":"e70071, 10 p.","ipdsId":"IP-183744","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500826,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/bes2.70071","text":"Publisher Index Page"},{"id":500338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Nicole K.","contributorId":366783,"corporation":false,"usgs":false,"family":"Ward","given":"Nicole","middleInitial":"K.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":956220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guilbeau, Kelly G.","contributorId":366784,"corporation":false,"usgs":false,"family":"Guilbeau","given":"Kelly","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":956221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesser, Amanda L.","contributorId":366785,"corporation":false,"usgs":false,"family":"Sesser","given":"Amanda","middleInitial":"L.","affiliations":[{"id":62402,"text":"Prescott College","active":true,"usgs":false}],"preferred":false,"id":956222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":956223,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273963,"text":"70273963 - 2026 - Rising atmospheric CO2 reduces nitrogen availability in boreal forests","interactions":[],"lastModifiedDate":"2026-02-23T14:14:56.466551","indexId":"70273963","displayToPublicDate":"2026-02-18T07:44:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rising atmospheric CO2 reduces nitrogen availability in boreal forests","title":"Rising atmospheric CO2 reduces nitrogen availability in boreal forests","docAbstract":"

Anthropogenic nitrogen (N) pollution has been emphasized as a cause of eutrophication globally. However, several recent datasets have suggested widespread oligotrophication may be occurring in some ecosystems, which is suggested to be a response to rising atmospheric carbon dioxide (eCO2). Plant δ15N chronologies have served as primary evidence for oligotrophication, however, there has been wide disagreement whether eCO2 or temporal changes in N deposition explain these patterns. We constructed δ15N tree ring chronologies across Sweden’s 23.5 million hectare productive forest area from the 1950s to 2010s. The study area spans a 1500 km latitudinal distance where N deposition varies four-fold, but where eCO2 is spatially uniform. Our data revealed negative δ15N chronologies throughout Sweden, including forests in the far north where atmospheric N deposition rates are very low. Linear mixed effects models showed that eCO2 was by far the strongest predictor of δ15N values, whereas N deposition variables, temperature, and forest basal area had much lower explanatory power. Our results clarify debates on the interpretation of previous δ15N chronologies, and provide clear evidence that eCO2 is causing oligotrophication in boreal forests, which has implications for predicting their future role as sinks in the global carbon cycle.

","language":"English","publisher":"Springer Nature","doi":"10.1038/s41586-025-10039-5","usgsCitation":"Bassett, K.R., Hupperts, S.F., Jämtgård, S., Östlund, L., Fridman, J., Perakis, S.S., and Gundale, M.J., 2026, Rising atmospheric CO2 intensifies nitrogen limitation in boreal forests: Nature, no. 650, p. 629-635, https://doi.org/10.1038/s41586-025-10039-5.","productDescription":"7 p.","startPage":"629","endPage":"635","ipdsId":"IP-173383","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500187,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500257,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-025-10039-5","text":"Publisher Index Page"}],"country":"Sweden","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 14.63346302221828,\n 66.95808924222021\n ],\n [\n 11.816628950923374,\n 62.8816235388625\n ],\n [\n 10.714598292419112,\n 55.39166409191142\n ],\n [\n 12.399827072155716,\n 54.583535462334794\n ],\n [\n 15.194165810541499,\n 55.5418316669677\n ],\n [\n 18.56862330588048,\n 56.05323191584169\n ],\n [\n 20.49382747838886,\n 62.91560998030781\n ],\n [\n 24.239407941016225,\n 65.83107952726502\n ],\n [\n 23.93671762466677,\n 67.79623029566048\n ],\n [\n 20.84193122924367,\n 68.85442260744358\n ],\n [\n 17.380981641240524,\n 68.36281881641594\n ],\n [\n 14.63346302221828,\n 66.95808924222021\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"650","noUsgsAuthors":false,"publicationDate":"2026-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bassett, Kelley R.","contributorId":366455,"corporation":false,"usgs":false,"family":"Bassett","given":"Kelley","middleInitial":"R.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hupperts, Stefan F.","contributorId":366456,"corporation":false,"usgs":false,"family":"Hupperts","given":"Stefan","middleInitial":"F.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jämtgård, Sandra","contributorId":366457,"corporation":false,"usgs":false,"family":"Jämtgård","given":"Sandra","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Östlund, Lars","contributorId":366458,"corporation":false,"usgs":false,"family":"Östlund","given":"Lars","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fridman, Jonas","contributorId":366459,"corporation":false,"usgs":false,"family":"Fridman","given":"Jonas","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":955932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gundale, Michael J.","contributorId":299675,"corporation":false,"usgs":false,"family":"Gundale","given":"Michael","middleInitial":"J.","affiliations":[{"id":64928,"text":"SLU","active":true,"usgs":false}],"preferred":false,"id":955934,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274186,"text":"70274186 - 2026 - A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries","interactions":[],"lastModifiedDate":"2026-03-09T15:01:06.104632","indexId":"70274186","displayToPublicDate":"2026-02-17T15:04:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7176,"text":"Hydrologic Processes","active":true,"publicationSubtype":{"id":10}},"title":"A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries","docAbstract":"

The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70459","usgsCitation":"Woda, J., Terry, N., Kelley, D.J., Finkelstein, J., Gazoorian, C.L., and McKenna, J., 2026, A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries: Hydrologic Processes, v. 40, e70459, 16 p., https://doi.org/10.1002/hyp.70459.","productDescription":"e70459, 16 p.","ipdsId":"IP-176833","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":501102,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70459","text":"Publisher Index Page"},{"id":500774,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.34397142741707,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 42.83906785974037\n ],\n [\n -75.35823758327766,\n 44.03795020350384\n ],\n [\n -80.34397142741707,\n 44.03795020350384\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2026-03-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Woda, Joshua 0000-0002-2932-8013","orcid":"https://orcid.org/0000-0002-2932-8013","contributorId":290172,"corporation":false,"usgs":true,"family":"Woda","given":"Joshua","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":956840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, David J 0000-0002-0143-0956","orcid":"https://orcid.org/0000-0002-0143-0956","contributorId":367137,"corporation":false,"usgs":true,"family":"Kelley","given":"David","middleInitial":"J","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":190798,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":956844,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273863,"text":"ofr20261062 - 2026 - Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont","interactions":[],"lastModifiedDate":"2026-02-20T18:15:51.013573","indexId":"ofr20261062","displayToPublicDate":"2026-02-17T13:05:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-1062","displayTitle":"Preliminary Bedrock Geologic Map of the Port Henry Quadrangle, Essex County, New York, and Addison County, Vermont","title":"Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont","docAbstract":"

Introduction 

The bedrock geology of the 7.5-minute Port Henry quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of an anorthosite-mangerite-charnockite-granite (AMCG) suite, now exposed mostly as orthogneiss, at approximately 1.18–1.15 Ga (giga-annum). In the Port Henry quadrangle, the AMCG metaigneous rocks (Yhg, Ygb, Yanw) intruded older, mostly metasedimentary rocks of the Grenville Complex during the middle to late Shawinigan orogeny (~1,160–1,150 Ma [mega-annum]). All rocks were subsequently metamorphosed to upper amphibolite to granulite facies conditions during the 1,080–1,050 Ma Ottawan orogeny. New mapping reveals four periods of deformation: (1) D1 produced rarely preserved isoclinal folds in the paragneiss and marble and predates AMCG magmatism. (2) Subsequent D2 deformation produced the dominant gneissic fabric preserved in the rock, recumbent folding, and deformed all the Proterozoic units in the map area. Syn- to late-D2 felsic magmatism resulted in the regionally extensive Lyon Mountain Granite Gneiss, which hosts numerous magnetite ore bodies. (3) Mylonitic extensional shear zones and core complex formation marked the beginning of D3 deformation. Protracted D3 deformation resulted in F3 upright folding, dome and basin formation, pegmatite intrusion, reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron-ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. (4) D4 created northeast- and northwest-trending local high-grade ductile shear zones and boudinage, northwest-trending regional kilometer (km)-wide ductile shear zones, and crosscutting granitic pegmatite dikes. The development of the late-stage regional shear zones (D4) was likely due to the continuation of extensional doming and uplift from upper amphibolite facies conditions at the end of the Ottawan orogeny. The majority of iron-ore deposits in the Port Henry and adjacent Witherbee quadrangles are in the hanging wall of these extensional shear zones. In the Port Henry quadrangle, the km-wide Cheney Mountain shear zone is the result of D4 deformation. Kilometer-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician carbonate bank on the ancient margin of Laurentia. The approximately 1-km-thick Cambrian to Ordovician stratigraphy records a transition from synrift clastics to passive-margin peritidal carbonate buildups to gradually deeper-water subtidal- to shelf-carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations.

This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Open-File Report includes a bedrock geologic map; a description of map units; a correlation of map units; and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261062","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey and the State of New York, Department of Education, New York Geological Survey","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Valley, P.M., Parker, M., Walsh, G.J., Orndorff, R.C., Walton, M.S., Jr., and Crider, E.A., Jr., 2026, Preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Open-File Report 2026–1062, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20261062.","productDescription":"1 Sheet: 63.17 x 30.58 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158945","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":500360,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119212.htm","linkFileType":{"id":5,"text":"html"}},{"id":499704,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13HYFPM","text":"USGS data release","linkHelpText":"Database for the preliminary bedrock geologic map of the Port Henry quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":499702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1062/coverthb4.jpg"},{"id":499703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1062/ofr20261062.pdf","text":"Sheet","size":"5.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1062 PDF"}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Port Henry quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44.125\n ],\n [\n -73.5,\n 44\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.375,\n 44.125\n ],\n [\n -73.5,\n 44.125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2026-02-17","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":955309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Mercer 0000-0001-6683-6458 mercerparker@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-6458","contributorId":203174,"corporation":false,"usgs":true,"family":"Parker","given":"Mercer","email":"mercerparker@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":955310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":355444,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":955311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":955312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walton, Matt S. Jr.","contributorId":33335,"corporation":false,"usgs":true,"family":"Walton","given":"Matt","suffix":"Jr.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":955314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crider,, E. Allen Jr. 0000-0003-2393-5290 ecrider@usgs.gov","orcid":"https://orcid.org/0000-0003-2393-5290","contributorId":203507,"corporation":false,"usgs":true,"family":"Crider,","given":"E. Allen","suffix":"Jr.","email":"ecrider@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":955313,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273931,"text":"70273931 - 2026 - Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","interactions":[],"lastModifiedDate":"2026-02-18T15:39:30.672299","indexId":"70273931","displayToPublicDate":"2026-02-17T09:31:36","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","title":"Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae)","docAbstract":"

Aim

Aims of the study are to examine patterns of range-wide genetic differentiation and population structure in a headwater obligate salamander living in a geologically rich region, to identify genetically distinct populations and areas of gene flow between them.

Location

Oregon and Washington in the Pacific Northwest, United States of America.

Time Period

Tissue samples were collected in 2022 and 2023.

Major Taxa Studied

The Cascade torrent salamander Rhyacotriton cascadae.

Methods

Utilisation of a genome-wide single nucleotide polymorphism (SNP) dataset from across the species range to conduct a principal components analysis (PCA), Bayesian model of population structure, co-ancestry matrix, phylogenetic tree and estimate genetic diversity.

Results

There are extensive levels of population structure within R. cascadae, including a previously unknown and highly differentiated clade. Structure is characterised by an island-like pattern wherein the species is comprised of six populations that function as independent demographic units, with gene flow largely constrained within populations.

Main Conclusions

Our findings reveal cryptic population structure within R. cascadae, identifying six distinct populations across the range. The northernmost population in the northwest of the species range in Washington is surprisingly highly divergent from the other five populations, and the divergence was not previously known to science. While major rivers act as phylogeographic boundaries between some populations, these boundaries appear to not always be complete.

","language":"English","publisher":"Wiley","doi":"10.1111/jbi.70167","collaboration":"Co-authors: Oregon State University, USFS","usgsCitation":"Cousins, C.D., Olson, D.H., Millward, L.S., Adams, M.J., Pearl, C., Rowe, J., and Garcia, T.S., 2026, Genomics reveals extensive population structure and undescribed phylogenetic relationships in the Cascade torrent salamander (Rhyacotriton cascadae): Journal of Biogeography, v. 53, no. 2, e70167, 15 p., https://doi.org/10.1111/jbi.70167.","productDescription":"e70167, 15 p.","ipdsId":"IP-182783","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 47.03638131106257\n ],\n [\n -123,\n 43.52402382935975\n ],\n [\n -121.5,\n 43.52402382935975\n ],\n [\n -121.5,\n 47.03638131106257\n ],\n [\n -123,\n 47.03638131106257\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cousins, Christopher D","contributorId":366385,"corporation":false,"usgs":false,"family":"Cousins","given":"Christopher","middleInitial":"D","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, Deanna H","contributorId":366386,"corporation":false,"usgs":false,"family":"Olson","given":"Deanna","middleInitial":"H","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":955800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millward, Lindsay S","contributorId":366387,"corporation":false,"usgs":false,"family":"Millward","given":"Lindsay","middleInitial":"S","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearl, Christopher 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":172669,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rowe, Jennifer 0000-0002-5253-2223 jrowe@usgs.gov","orcid":"https://orcid.org/0000-0002-5253-2223","contributorId":172670,"corporation":false,"usgs":true,"family":"Rowe","given":"Jennifer","email":"jrowe@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":955804,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garcia, Tiffany S","contributorId":366394,"corporation":false,"usgs":false,"family":"Garcia","given":"Tiffany","middleInitial":"S","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955805,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273939,"text":"70273939 - 2026 - Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","interactions":[],"lastModifiedDate":"2026-02-18T15:12:53.887851","indexId":"70273939","displayToPublicDate":"2026-02-17T07:57:49","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics","docAbstract":"

Due to a lack of management operations data, hydrological models may represent reservoirs as natural lakes, leading to poor discharge predictions in regulated basins. To parse seasonal operational signatures, we compare the dynamics of natural lake and reservoir systems across North America using Surface Water and Ocean Topography (SWOT) satellite observations and derived discharge estimates. Overall, reservoirs and their adjacent river reaches exhibit significantly greater variability (in standard deviation) than their natural counterparts across almost all SWOT observed (e.g. water surface elevation) and inferred (e.g. discharge) variables. Natural lakes show strong same-day correlations between inflow and outflow discharge (median Spearman R = 0.8), whereas 76% of reservoirs exhibit maximum correlation when outflow is lagged, suggesting operations buffer seasonal flow variability. Our findings indicate operations not only affect reservoir dynamics themselves but also have upstream and downstream consequences, which, when integrated into models, will offer more realistic hydrologic conditions.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ae436e","usgsCitation":"Riggs, R.M., Dickinson, J.E., Brinkerhoff, C.B., Sikder, M.S., Wang, J., Gao, H., and Allen, G.H., 2026, Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics: Environmental Research Letters, v. 21, 044008, 11 p., https://doi.org/10.1088/1748-9326/ae436e.","productDescription":"044008, 11 p.","ipdsId":"IP-177052","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":500251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ae436e","text":"Publisher Index Page"},{"id":500137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -165.20917200792005,\n 72.32481180155446\n ],\n [\n -116.99838105786625,\n 14.863773568551608\n ],\n [\n -87.70978967120412,\n 18.449041713609518\n ],\n [\n 1.251170353917047,\n 74.7933097957411\n ],\n [\n -165.20917200792005,\n 72.32481180155446\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","noUsgsAuthors":false,"publicationDate":"2026-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Riggs, Ryan Matthew 0000-0001-6834-9469","orcid":"https://orcid.org/0000-0001-6834-9469","contributorId":359717,"corporation":false,"usgs":true,"family":"Riggs","given":"Ryan","middleInitial":"Matthew","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":955826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinkerhoff, Craig B. 0000-0001-6701-4835","orcid":"https://orcid.org/0000-0001-6701-4835","contributorId":345546,"corporation":false,"usgs":false,"family":"Brinkerhoff","given":"Craig","middleInitial":"B.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":955828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sikder, Md. Safat 0000-0002-1910-1800","orcid":"https://orcid.org/0000-0002-1910-1800","contributorId":359718,"corporation":false,"usgs":false,"family":"Sikder","given":"Md.","middleInitial":"Safat","affiliations":[{"id":85904,"text":"Department of Geography and Geographic Information Science, University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jida","contributorId":333531,"corporation":false,"usgs":false,"family":"Wang","given":"Jida","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":955830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gao, Huilin 0000-0001-7009-8005","orcid":"https://orcid.org/0000-0001-7009-8005","contributorId":359721,"corporation":false,"usgs":false,"family":"Gao","given":"Huilin","affiliations":[{"id":51860,"text":"Department of Civil Engineering, Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":955831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allen, George H. 0000-0001-8301-5301","orcid":"https://orcid.org/0000-0001-8301-5301","contributorId":225161,"corporation":false,"usgs":false,"family":"Allen","given":"George","middleInitial":"H.","affiliations":[{"id":41057,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":955832,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274640,"text":"70274640 - 2026 - Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","interactions":[],"lastModifiedDate":"2026-04-02T18:30:01.828215","indexId":"70274640","displayToPublicDate":"2026-02-16T11:24:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes","docAbstract":"

Freshwater fishes are among the most threatened taxa, yet conservation assessments remain incomplete for many species. Freshwater fishes provide essential ecosystem services such as food security, recreational opportunities, and cultural significance. Despite heavy alterations to freshwater ecosystems, the reasons for species’ sensitivity and resistance to imperilment are unclear. To address this need, we develop a machine learning framework to predict global imperilment status for 10,631 freshwater fish species using a comprehensive set of environmental, socioeconomic, and intrinsic species-level predictors. Using updated IUCN Red List data, we train and validate Random Forest classifiers to distinguish imperiled (Vulnerable, Endangered, Critically Endangered) from non-imperiled species. We examine the relative influence of 52 variables derived from 12 global sources describing extrinsic environmental and socioeconomic factors and intrinsic species-specific characteristics. Our models achieve higher accuracy for non-imperiled species (90.1%) compared to imperiled species (81.8%), reflecting the greater heterogeneity of threats and conditions driving imperilment. Across models, key predictors include habitat variables, taxonomic order, hydrological characteristics, and disturbance indicators, underscoring the interplay between ecology, geography, and human pressures. This integrative, reproducible approach demonstrates the utility of machine learning for guiding proactive conservation and provides a scalable framework for global biodiversity risk assessment.

","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-025-68154-w","usgsCitation":"Murphy, C.A., Olivos, J.A., Arismendi, I., García-Berthou, E., Johnson, S.L., and Dunham, J., 2026, Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes: Nature Communications, v. 17, 1661, 11 p., https://doi.org/10.1038/s41467-025-68154-w.","productDescription":"1661, 11 p.","ipdsId":"IP-170109","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-68154-w","text":"Publisher Index Page"},{"id":502030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivos, J. Andres","contributorId":369132,"corporation":false,"usgs":false,"family":"Olivos","given":"J.","middleInitial":"Andres","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":958524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"García-Berthou, Emili","contributorId":6293,"corporation":false,"usgs":false,"family":"García-Berthou","given":"Emili","affiliations":[],"preferred":false,"id":958525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Sherri L.","contributorId":369137,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":958526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":958527,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273930,"text":"70273930 - 2026 - Effects of groundwater withdrawals for water bottling and municipal use, Wards Brook Valley, Maine and New Hampshire","interactions":[],"lastModifiedDate":"2026-02-18T15:14:50.497171","indexId":"70273930","displayToPublicDate":"2026-02-13T09:08:06","publicationYear":"2026","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Effects of groundwater withdrawals for water bottling and municipal use, Wards Brook Valley, Maine and New Hampshire","docAbstract":"

Hydrologic models for the Wards Brook valley near Fryeburg, Maine were developed for historical (2016 – 2021) and hypothetical future conditions (2046 – 2065 and 2080 – 2099) to understand the effects of groundwater withdrawals for bottled water and municipal use on hydrologic conditions (stream base flows and groundwater levels). Analyses showed that the simulated base flows in Wards Brook were reduced because of pumping for both municipal water supplies and for water bottling, and about half of the total pumping impact on the base flows in Wards Brook was from the bottled water extraction. Simulated flows were greater than the minimum recommended streamflow of 2,180 cubic meters per day (400 gallons per minute) throughout the historical period. Simulated groundwater levels at two of three nearby ponds (Round Pond and Davis Pond) were minimally affected by pumping conditions, and effects were primarily from the municipal well closest to the ponds.

Several estimates of future projected recharge were used to understand the potential effects of groundwater withdrawals on hydrologic conditions under multiple hypothetical climate conditions. Annual projected recharge rates in the mid- and late-21st century from two climate scenarios (stabilized greenhouse-gas emissions and high greenhouse-gas emissions) were similar to rates for 2016 – 2021. However, monthly recharge patterns for the future periods shifted toward more recharge in the winter months (December, January, and February) and less recharge in April, May, and October relative to 2016 – 2021.

The lowest mean monthly base flows from the future emission scenarios all remain larger than the minimum recommended streamflow and indicate no long-term declines in flow relative to historical conditions. However, simulated base flows during hypothetical 3-year drought scenarios declined below minimum recommended streamflow during the summer months in the stabilized- and high-emission scenarios in the mid-21st century. Although water is generally plentiful in the Wards Brook valley, reduced pumping may be needed to maintain streamflows in Wards Brook under future climate conditions similar to modeled drought scenarios.

","language":"English","publisher":"EarthArXiv","doi":"10.31223/X5KN1M","usgsCitation":"Mullaney, J.R., Barclay, J.R., Stanton, J.S., Carlson, C.S., and Holland, M., 2026, Effects of groundwater withdrawals for water bottling and municipal use, Wards Brook Valley, Maine and New Hampshire: EarthArXiv, preprint posted February 13, 2026, https://doi.org/10.31223/X5KN1M.","productDescription":"104 p.","ipdsId":"IP-183461","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":500138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2026-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Mullaney, John R 0000-0003-4936-5046","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":366383,"corporation":false,"usgs":false,"family":"Mullaney","given":"John","middleInitial":"R","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":955794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanton, Jennifer S. 0000-0002-2520-753X jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Carl S 0000-0001-7142-3519","orcid":"https://orcid.org/0000-0001-7142-3519","contributorId":366384,"corporation":false,"usgs":false,"family":"Carlson","given":"Carl","middleInitial":"S","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":955797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holland, Madeleine 0000-0002-2369-0767","orcid":"https://orcid.org/0000-0002-2369-0767","contributorId":344542,"corporation":false,"usgs":false,"family":"Holland","given":"Madeleine","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":955798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274036,"text":"70274036 - 2026 - Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.","interactions":[],"lastModifiedDate":"2026-02-23T18:10:39.262997","indexId":"70274036","displayToPublicDate":"2026-02-12T11:03:31","publicationYear":"2026","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":"Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.","docAbstract":"

We sought to assess bridle shiner (Notropis bifrenatus) habitat associations at local and regional scales across southern Maine and New Hampshire. We used local habitat data at 95 Maine sites to predict occupancy with classification and regression trees (CART). We then used ensemble species distribution models (SDMs) to model the historical (1898–2008) and current (2009–2022) ranges of the species. We used the BIOMOD platform to model the association between 35 environmental variables and bridle shiner presence during both time periods and at fine (pseudo-HUC14) and coarse (HUC12) spatial scales. We then calculated the change in predicted occupied drainages to estimate the change in the species' distribution at both scales. Within a site, bridle shiners were associated with submerged aquatic vegetation, organic substrate, and watermilfoil (Myriophyllum spp.). SDMs revealed an association with Appalachian (Hemlock-)Northern Hardwood Forest, sand substrate, and low-elevation terrain (at both spatial scales). Ensemble fine-scale SDMs suggest a substantial loss of historical bridle shiner habitat in both Maine (36% of drainages) and New Hampshire (16%), with comparable described losses (of 21% and 14%) at a coarse scale. Our local and regional models may be used to focus surveys on areas with high predicted habitat suitability or to inform habitat restoration efforts.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72413","usgsCitation":"Katz, L.S., Coghlan, S.M., Carpenter, M.A., Kinnison, M.T., Zydlewski, J.D., 2026, Habitat-based predictions of bridle shiner (Notropis bifrenatus) in the northeastern U.S.: Ecology and Evolution, v. 16, no. 1, e72413, 19 p., https://doi.org/10.1002/ece3.72413.","productDescription":"e72413, 19 p.","ipdsId":"IP-158442","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72413","text":"Publisher Index Page"},{"id":500439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, New Hampshire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -69.25429976691849,\n 47.475434309112075\n ],\n [\n -71.47637622335257,\n 45.210844648573726\n ],\n [\n -72.2134392335759,\n 43.872712909182994\n ],\n [\n -72.54074189044374,\n 42.739662976646855\n ],\n [\n -71.15118191830072,\n 42.68091951244142\n ],\n [\n -69.70815322174685,\n 43.6220110458515\n ],\n [\n -66.83114905877525,\n 44.72524582330068\n ],\n [\n -67.67285260858687,\n 45.844248966240016\n ],\n [\n -67.78415740622219,\n 47.198837764366964\n ],\n [\n -68.11347172586534,\n 47.38520895041782\n ],\n [\n -69.25429976691849,\n 47.475434309112075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2026-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Katz, Lara S.","contributorId":366795,"corporation":false,"usgs":false,"family":"Katz","given":"Lara","middleInitial":"S.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":956239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":366796,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","middleInitial":"M.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":956240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpenter, Matthew A.","contributorId":366797,"corporation":false,"usgs":false,"family":"Carpenter","given":"Matthew","middleInitial":"A.","affiliations":[{"id":56597,"text":"New Hampshire Fish and Game Department","active":true,"usgs":false}],"preferred":false,"id":956241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kinnison, Michael T.","contributorId":366798,"corporation":false,"usgs":false,"family":"Kinnison","given":"Michael","middleInitial":"T.","affiliations":[{"id":87507,"text":"Maine Center for Genetics in the Environment","active":true,"usgs":false}],"preferred":false,"id":956242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":956243,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274539,"text":"70274539 - 2026 - Experimental translocation of a rare Hawaiian tree reveals disparity between remnant and potential habitat","interactions":[],"lastModifiedDate":"2026-04-01T14:51:54.648551","indexId":"70274539","displayToPublicDate":"2026-02-12T09:45:37","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Experimental translocation of a rare Hawaiian tree reveals disparity between remnant and potential habitat","docAbstract":"

Translocation is implemented worldwide as a conservation strategy for rare and endangered plant species, yet the factors that influence long-term success remain poorly understood. Remnant wild populations are often used as indicators to model habitat preference and select translocation sites, but such populations may be refugia from past biological or anthropogenic stressors and represent sub-optimal habitat conditions for focal taxa. To test assumptions about habitat preferences of rare species, we conducted a four-year experimental translocation of the Critically Endangered Hawaiian tree, ‘ohe mauka, Polyscias bisattenuata (Araliaceae), planting 3,700 saplings across eleven sites spanning diverse environmental conditions both within and beyond the species’ extant range. We measured seventeen predictor variables at the site and individual plant level in categories of climate, surrounding vegetation, soil chemistry, and genetic provenance. We used linear mixed effects models to assess relative effects of predictors on translocated plant survival, growth, and vigor. The factors which influenced plant performance shifted across ontogeny. The height of surrounding vegetation showed an initial negative relationship with two-year survival, but later showed a positive relationship with four-year growth. Four-year growth demonstrated a strong positive relationship with site annual mean temperature. Successful translocation sites were lower in elevation and warmer in temperature than conditions represented by remnant wild populations. Results demonstrate that basing translocation sites solely on limited extant wild occurrences can lead to suboptimal restoration practices, and experimental outplanting across broad conditions may help identify rare species' contemporary habitat preferences.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.111686","usgsCitation":"Douglas, J., Bai, M., Fortini, L., Yelenik, S.G., and Rønsted, N., 2026, Experimental translocation of a rare Hawaiian tree reveals disparity between remnant and potential habitat: Biological Conservation, v. 316, 111686, 14 p., https://doi.org/10.1016/j.biocon.2025.111686.","productDescription":"111686, 14 p.","ipdsId":"IP-172753","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":502101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2025.111686","text":"Publisher Index Page"},{"id":501926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kauai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.43528948717787,\n 21.8600584707048\n ],\n [\n -159.31225642523046,\n 21.965179026209356\n ],\n [\n -159.27950254999953,\n 22.154674352412997\n ],\n [\n -159.3644769358584,\n 22.23581128374363\n ],\n [\n -159.5848810137864,\n 22.234993140593716\n ],\n [\n -159.77333377581635,\n 22.129242159745644\n ],\n [\n -159.80262962648277,\n 22.035753318333562\n ],\n [\n -159.7796155454661,\n 21.971740161149867\n ],\n [\n -159.6025771119729,\n 21.87649287101374\n ],\n [\n -159.43528948717787,\n 21.8600584707048\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"316","noUsgsAuthors":false,"publicationDate":"2026-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas, Julia","contributorId":368953,"corporation":false,"usgs":false,"family":"Douglas","given":"Julia","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":958166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bai, Mingzhou","contributorId":368954,"corporation":false,"usgs":false,"family":"Bai","given":"Mingzhou","affiliations":[{"id":50046,"text":"Technical University of Denmark","active":true,"usgs":false}],"preferred":false,"id":958167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":958168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":958169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rønsted, Nina","contributorId":368955,"corporation":false,"usgs":false,"family":"Rønsted","given":"Nina","affiliations":[{"id":87681,"text":"National Tropical Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":958170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274650,"text":"70274650 - 2026 - Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study","interactions":[],"lastModifiedDate":"2026-04-02T16:47:01.123474","indexId":"70274650","displayToPublicDate":"2026-02-12T09:38:04","publicationYear":"2026","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":"Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study","docAbstract":"

White-tailed deer (Odocoileus virginianus) are a valuable game mammal in the eastern United States necessitating detailed understanding of disease transmission. We conducted a literature review on intraspecific contact (i.e., interactions wherein disease transmission may occur) among deer. From 69 studies, we identified five themes underlying research on intraspecific deer contact: physical touch, social groups, spatial overlap, association rates, and social networks. Visual observations determined physical touch to be infrequent (< 2 touches/h) and indicated deer social groups were dependent on spatial dynamics of parturition and dispersal; most females remained with matriarchal family groups while males dispersed and formed bachelor groups. Assessed using global positioning system (GPS) monitoring, spatial overlap and association rates (i.e., instances of deer in close spatial–temporal proximity) were higher in correspondence to within-group social dynamics, and between-group scores were correspondingly low. Social network analyses indicated between-group transmission may be driven by socially dominant males, often termed super-spreaders (i.e., hosts infecting disproportionately high numbers of healthy individuals). We investigated these themes via a case study of deer infected with chronic wasting disease (CWD) in southcentral Pennsylvania, United States. We assessed spatial overlap and association rates using GPS monitoring data from 180 deer. Our results supported findings in the literature, showing strong correlations among spatial overlap, association rates, and correlated movements. Further, CWD-infected deer exhibited similar association rates to deer in which CWD was not detected. Our literature review and case study indicate direct transmission of CWD and other diseases is likely greatest within social groups following seasonal behavioral dynamics and that between-group transmission is likely driven by males via dispersal and mating interactions. Our results may be used to inform population management models with future work focused on high resolution spatial assessments of transmission in localized areas.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.73040","usgsCitation":"Wehr, N.H., Bondo, K.J., Rosenberry, C.S., Stainbrook, D., Wallingford, B.D., and Walter, W., 2026, Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study: Ecology and Evolution, v. 16, no. 2, e73040, 20 p., https://doi.org/10.1002/ece3.73040.","productDescription":"e73040, 20 p.","ipdsId":"IP-182245","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502090,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.73040","text":"Publisher Index Page"},{"id":502014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"southcentral Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.32215898198577,\n 40.430818578170204\n ],\n [\n -78.32215898198577,\n 39.73578816878745\n ],\n [\n -77.0741919959731,\n 39.73578816878745\n ],\n [\n -77.0741919959731,\n 40.430818578170204\n ],\n [\n -78.32215898198577,\n 40.430818578170204\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wehr, Nathaniel H.","contributorId":369169,"corporation":false,"usgs":false,"family":"Wehr","given":"Nathaniel","middleInitial":"H.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":958559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bondo, Kristin J.","contributorId":369170,"corporation":false,"usgs":false,"family":"Bondo","given":"Kristin","middleInitial":"J.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":958560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Christopher S.","contributorId":369171,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","middleInitial":"S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":958561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stainbrook, David","contributorId":272188,"corporation":false,"usgs":false,"family":"Stainbrook","given":"David","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":958562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":369173,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","middleInitial":"D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":958563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958564,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}