The use of field-deployable fluorescence sensors to better understand dissolved organic matter concentrations and composition has grown immensely in recent years. Applications of these sensors to critical monitoring efforts have also grown, encompassing post-fire monitoring, wastewater tracking, and use as a proxy for various contaminants. Despite the growth, it is well known that these sensors require corrections for temperature (Watras and others, 2011) and are subject to many light-field interferences caused by both scattering and absorbance due to dissolved and particulate substances (Downing and others, 2012; Lee and others, 2015; Booth and others, 2023). The most common fluorescence sensors used by the U.S. Geological Survey (USGS) include those targeting fluorescent dissolved organic matter (fDOM) and chlorophylls. Because fDOM sensors primarily measure fluorescence in the dissolved to colloidal phases, corrections to the interferences caused by particulates can be made relatively easily. By the end of 2024, the USGS had 69 fDOM sensors deployed within official water quality monitoring networks included on the USGS National Water Dashboard (https://dashboard.waterdata.usgs.gov/app/nwd/en/) and numerous others used in surveys and research applications across the Nation.
Although temperature corrections are widely applicable across sensor models, interference corrections can be model specific due to differences in design specifications across manufacturers and models (Booth and others, 2023). The corrections are also potentially subject to changes in manufacturing within a specific sensor model. Recently, USGS staff obtained information regarding possible changes in the manufacturing of its most widely-used fDOM sensor model, raising concerns about data consistency and quality in the USGS fDOM sensor networks.
Furthermore, changes in turbidity sensors since the corrections guidance was performed may also affect the performance of the corrections. The turbidity sensor used in the original experiments (Downing and others, 2012) was determined to have a signal output approximately 1.3 times higher than the output of the turbidity sensor currently used in an extensive field comparison study (Messner and others, 2023). With these changes, it is imperative that the corrections be reevaluated to maintain data consistency and continuity across the USGS.
In this study, we evaluated turbidity corrections for fDOM sensors over a range of serial numbers covering manufacturing dates 2015 through 2022 and turbidity serial numbers covering the range 2013 through 2022. The goal was to determine whether reported changes in the manufacturing process of the fDOM and turbidity sensors affected the correction approach developed by Downing and others (2012) such that additional guidance would be required to address this manufacturing change. To evaluate, we repeated a laboratory-based test similar to that performed by Downing and others (2012) in which a series of tank experiments with multiple sensors were deployed in a suspension of Elliot Silt Loam (ESL). High turbidities of the ESL suspension were maintained throughout the tank by turbulent recirculation using submersible pumps. Particulates were removed using a recirculated line equipped with a capsule filter (0.45 micron). Measurements were collected throughout the filtration until turbidities reached approximately 5 formazin nephelometric units (FNU; data available in Baxter and others, 2023). Each experimental run included a mixture of unique sensor combinations to account for variability imposed by the turbidity and temperature sensors. The fDOM correction factor was calculated for each combination of fDOM and turbidity sensors included in the test.
We observed no systematic change in fDOM correction coefficients across serial numbers representing manufacturing years 2015 through 2022. However, the results highlighted questions raised about the corrections for high-turbidity samples, as noted in USGS Techniques and Methods (Booth and others, 2023). Applying the inverse of the commonly-used fDOM ratio with a quadratic fit performed better than the exponential fits when correcting fDOM data for turbidity in the ESL laboratory filtration test and generated a simple scale factor correction equation. This approach also served as a better indicator of data quality than the exponential fit approach. Similar to fDOM, more rigorous quality assurance measures may be necessary to evaluate turbidity sensor calibrations and performance. Sensors exceeding a certain age may need to be replaced despite passing quality assurance checks during calibration. Further testing of the turbidity corrections for different sediment and water types is warranted to better understand the variations in the fits and correctable ranges of turbidity in different systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261063","programNote":"Water Resources Mission Area","usgsCitation":"Fleck, J.A., Baxter, T.J., and Hansen, A.M., 2026, Evaluation of turbidity corrections for fluorescent dissolved organic matter (fDOM) sensors: U.S. Geological Survey Open-File Report 2026–1063, 30 p., https://doi.org/10.3133/ofr20261063.","productDescription":"Report: vi, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-171907","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1063/coverthb.jpg"},{"id":500843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1063 PDF"},{"id":500844,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261063/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1063 HTML"},{"id":500845,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1063/ofr20261063.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1063 XML"},{"id":500846,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1063/images"},{"id":500847,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OB430E","text":"USGS data release","linkHelpText":"Fluorescence sensor measurements in sediment suspensions to evaluate turbidity corrections"}],"contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Working Group on American Eel (WGAMEEL) met virtually three times in 2022-2024 to address the five Terms of Reference (ToRs) of its three-year term. The first two ToRs tasked WGAMEEL with listing and evaluating data on American eel landings, abundance indices, and spatial and habitat data and also to describe assessment methods used in Canada and the US. Canada-wide American eel trajectory was estimated using 12 fishery-independent datasets. Generally, longer datasets had more negative trends than shorter ones. Limiting data to the post-2000 years produced fewer negative trends that did not differ from zero, suggesting the observed declines occurred pre-2000. Spatial modelling for American eel requires knowledge and mapping that covers the breadth of habitat types occupied by the species, including freshwater, estuarine, and marine environments. In recent years there has been an expansion of online databases with data from the aquatic environment, particularly in freshwater, with estuarine and marine data less consistently documented. This report broadly compiles abiotic data series of relevance to American eel. A larger challenge for spatial modelling will be acquiring enough high quality, georeferenced biological data sets with suitable observations to assess occurrence, abundance, and trends over time in a spatial framework.
The third ToR considered Indigenous Knowledge Systems for American eel. A survey reaching First Nations representatives from four Canadian provinces confirmed the cultural importance of eels in Indigenous communities, and that Indigenous knowledge possessed by the participant groups are place-based and contextual, especially regarding threats impacting eels.
The final two ToRs focused on identifying stock assessment modelling approaches applicable to American and European eel, and assessing whether any of these approaches might be appropriate for American eel management moving forward. WGAMEEL evaluated the various approaches for assessing American eel or providing management advice. Two approaches that could be completed in the next few years because of their minimal data needs are index-based methods and catch-only method. A suite of approaches considered by WGAMEEL that would take more time and data were spatial or habitat models, management strategy evaluation, and spawner-per-recruit (SPR) models potentially paired with meta-population models.
","language":"English","publisher":"International Council for the Exploration of the Sea","doi":"10.17895/ices.pub.31538731","usgsCitation":"April, J., Anstead, K., Brodeur, P., Cairns, D., Castonguay, M., Cieri, M., Jessop, B., D'Astous, A., Denny, S., Dumont, J., Eyler, S., Koops, M.A., Lee, L., Landry-Massicote, L., Maxwell, R., Pratt, T., Reid, S.M., Roloson, S., Schlueter, S.L., Snyder, S., and Young, J.A., 2026, Working group on American Eel (WGAMEEL; outputs from 2024 meeting): ICES Scientific Reports, v. 8, no. 15, 68 p., https://doi.org/10.17895/ices.pub.31538731.","productDescription":"68 p.","ipdsId":"IP-174599","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"15","noUsgsAuthors":false,"publicationDate":"2026-03-06","publicationStatus":"PW","contributors":{"editors":[{"text":"Anstead, Kristen A.","contributorId":329847,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":958372,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Pratt, Thomas","contributorId":347389,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958373,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"April, Julien","contributorId":369015,"corporation":false,"usgs":false,"family":"April","given":"Julien","affiliations":[{"id":87698,"text":"Ministère de l'Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs","active":true,"usgs":false}],"preferred":false,"id":958374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anstead, Kristen A.","contributorId":348307,"corporation":false,"usgs":false,"family":"Anstead","given":"Kristen A.","affiliations":[{"id":83332,"text":"Atlantic States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":958375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodeur, Philippe","contributorId":369056,"corporation":false,"usgs":false,"family":"Brodeur","given":"Philippe","affiliations":[],"preferred":false,"id":958376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cairns, David K.","contributorId":292427,"corporation":false,"usgs":false,"family":"Cairns","given":"David K.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castonguay, Martin","contributorId":292432,"corporation":false,"usgs":false,"family":"Castonguay","given":"Martin","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cieri, Matthew","contributorId":369058,"corporation":false,"usgs":false,"family":"Cieri","given":"Matthew","affiliations":[],"preferred":false,"id":958378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jessop, Brian","contributorId":369057,"corporation":false,"usgs":false,"family":"Jessop","given":"Brian","affiliations":[],"preferred":false,"id":958379,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"D'Astous, Amelie","contributorId":369059,"corporation":false,"usgs":false,"family":"D'Astous","given":"Amelie","affiliations":[],"preferred":false,"id":958380,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Denny, Shelly","contributorId":369060,"corporation":false,"usgs":false,"family":"Denny","given":"Shelly","affiliations":[],"preferred":false,"id":958381,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dumont, Jean-Francois","contributorId":369061,"corporation":false,"usgs":false,"family":"Dumont","given":"Jean-Francois","affiliations":[],"preferred":false,"id":958382,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Eyler, Sheila","contributorId":189779,"corporation":false,"usgs":false,"family":"Eyler","given":"Sheila","affiliations":[],"preferred":false,"id":958383,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Koops, Marten A.","contributorId":16715,"corporation":false,"usgs":false,"family":"Koops","given":"Marten","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":958384,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lee, Laura","contributorId":369062,"corporation":false,"usgs":false,"family":"Lee","given":"Laura","affiliations":[],"preferred":false,"id":958385,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Landry-Massicote, Louis","contributorId":369063,"corporation":false,"usgs":false,"family":"Landry-Massicote","given":"Louis","affiliations":[],"preferred":false,"id":958386,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Maxwell, Robby","contributorId":369064,"corporation":false,"usgs":false,"family":"Maxwell","given":"Robby","affiliations":[],"preferred":false,"id":958387,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pratt, Thomas","contributorId":347389,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958388,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Reid, Scott M.","contributorId":347268,"corporation":false,"usgs":false,"family":"Reid","given":"Scott","email":"","middleInitial":"M.","affiliations":[{"id":83120,"text":"Ontario Ministry of Natural Resources and Forestry.","active":true,"usgs":false}],"preferred":false,"id":958389,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Roloson, Scott","contributorId":368986,"corporation":false,"usgs":false,"family":"Roloson","given":"Scott","affiliations":[{"id":87695,"text":"Canadian Department of Fisheries and Oceans.","active":true,"usgs":false}],"preferred":false,"id":958213,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schlueter, Scott L.","contributorId":197961,"corporation":false,"usgs":false,"family":"Schlueter","given":"Scott","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":958390,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Snyder, Shawn","contributorId":302899,"corporation":false,"usgs":false,"family":"Snyder","given":"Shawn","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":958391,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Young, John A. 0000-0002-4500-3673","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":360717,"corporation":false,"usgs":true,"family":"Young","given":"John","middleInitial":"A.","affiliations":[{"id":85817,"text":"EESC (retired)","active":true,"usgs":false}],"preferred":true,"id":958212,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70274250,"text":"70274250 - 2026 - A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping","interactions":[],"lastModifiedDate":"2026-03-19T19:31:01.642826","indexId":"70274250","displayToPublicDate":"2026-03-05T14:20:03","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping","docAbstract":"Understanding how climatic variables impact host-pathogen relationships in temperature-sensitive ectothermic host organisms is crucial under global change. Few studies have explored how temperature gradients generate inter-individual variation in epidemiological traits like host susceptibility or pathogen replication. Here, we develop a mathematical model to explore a novel hypothesis: stochastic within-host dynamics and simulated thermal mismatches between host and pathogen traits generate predictable variation in infection outcomes among hosts and across thermal gradients. Our model demonstrates that varying trait thermal optima in host immunity and pathogen replication, and stochastic within-host processes produced variation in infection outcomes. Variability was low when temperatures strongly favored host or pathogen traits, but high and diverse when their performance was similar across a broad thermal range. In contrast, when trait performance was equal across all temperatures (no mismatch) variability remained low at all temperatures. Further, the magnitude of variation, quantified by entropy, exhibited predictable patterns depending on host-pathogen thermal mismatches. We conclude that interactions between trait thermal mismatches and within-host stochasticity provide a theoretical framework to improve ectotherm disease models under climate change, providing a valuable tool for exploring the impacts of environmental change on epizootic or epidemic dynamics, particularly in vulnerable marine ecosystems.
","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rstb.2024.0328","usgsCitation":"Carlino, A., Loeher, M.M., Páez, D.J., Hershberger, P., Wolf, N., and Mihaljevic, J., 2026, Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease outcomes: Philosophical Transactions of the Royal Society, Series B, v. 381, no. 1945, 20240328, 12 p., https://doi.org/10.1098/rstb.2024.0328.","productDescription":"20240328, 12 p.","ipdsId":"IP-180151","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"381","issue":"1945","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlino, Andrew","contributorId":369232,"corporation":false,"usgs":false,"family":"Carlino","given":"Andrew","affiliations":[{"id":83041,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":958655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loeher, Malina Mariko 0000-0001-9589-5641","orcid":"https://orcid.org/0000-0001-9589-5641","contributorId":365991,"corporation":false,"usgs":true,"family":"Loeher","given":"Malina","middleInitial":"Mariko","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Páez, David James 0000-0001-9035-394X","orcid":"https://orcid.org/0000-0001-9035-394X","contributorId":296751,"corporation":false,"usgs":true,"family":"Páez","given":"David","middleInitial":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Nathan","contributorId":350132,"corporation":false,"usgs":false,"family":"Wolf","given":"Nathan","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":958659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mihaljevic, Joseph R.","contributorId":352200,"corporation":false,"usgs":false,"family":"Mihaljevic","given":"Joseph R.","affiliations":[{"id":84130,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":958660,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274254,"text":"70274254 - 2026 - Fragmentation as a population rate-changer: A field experiment","interactions":[],"lastModifiedDate":"2026-03-23T14:48:49.820811","indexId":"70274254","displayToPublicDate":"2026-03-05T09:20:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fragmentation as a population rate-changer: A field experiment","docAbstract":"Experimental and observational studies of effects of fragmentation on biodiversity and population dynamics have produced mixed results, with some reviews concluding strong evidence of negative effects and others concluding small positive effects. In addition, many factors (e.g., interspecific interactions, edge effects, nutrient cycling) have been identified as potential explanations underlying the various results. We carried out a population-level fragmentation study on meadow voles, focusing on changes in vital rates caused by reduced movements in experimental 2-patch systems. We developed predictions of fragmentation effects by decomposing rates of apparent survival and recruitment (parameters directly estimated using capture–recapture models) into components that do and do not include movement. Fragmentation was predicted to reduce movement rates, and reduced movement was predicted to increase apparent survival rates, decrease immigration rates, and slightly increase population growth rates. We found evidence of increased adult and juvenile apparent survival and adult population growth rate on fragmented grids, whereas results for recruitment were ambiguous and did not support our predictions. The recruitment results led to the hypothesis that immigration into suitable habitat may not be reduced by fragmentation as much as permanent emigration from that habitat. A focus on effects of reduced movement on vital rates should be a reasonable starting point for investigations of fragmentation effects. This focus suggests that explanations underlying fragmentation effects will require additional effort devoted to isolating movement components of vital rates.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70327","usgsCitation":"Nichols, J.D., Hines, J.E., Hinz, R.L., and Hinz, J., 2026, Fragmentation as a population rate-changer: A field experiment: Ecology, v. 107, no. 3, e70327, 19 p., https://doi.org/10.1002/ecy.70327.","productDescription":"e70327, 19 p.","ipdsId":"IP-183793","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501391,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ja/70274254/images"},{"id":501390,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/ja/70274254/70274254.XML"},{"id":501389,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/publication/70274254/full"},{"id":501388,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hinz, Robert L.","contributorId":43454,"corporation":false,"usgs":true,"family":"Hinz","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":957202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinz, Janet","contributorId":367241,"corporation":false,"usgs":false,"family":"Hinz","given":"Janet","affiliations":[],"preferred":false,"id":957203,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274205,"text":"70274205 - 2026 - Measuring storm waves and water levels from a fixed structure with a rapidly deployable oceanographic radar","interactions":[],"lastModifiedDate":"2026-03-13T13:23:53.855171","indexId":"70274205","displayToPublicDate":"2026-03-05T09:16:28","publicationYear":"2026","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Measuring storm waves and water levels from a fixed structure with a rapidly deployable oceanographic radar","docAbstract":"A new oceanographic radar instrument package was developed by the U.S. Geological Survey (USGS) to measure storm waves and water levels in the nearshore, capable of being deployed rapidly and transmitting data in near real-time. To test the performance and accuracy of the sensor, multiple years of data were collected over various hydrodynamic conditions and compared to long-term monitoring data collected at the U.S. Army Corps of Engineers (USACE) Field Research Facility in Duck, North Carolina, USA. The oceanographic radars were highly reliable, with less than 1% of the record being erroneous spikes or missing data points. At the end of the pier, the radar was highly accurate, with nearly perfect agreement in water level (r2 = 0.997) compared to a nearby National Oceanic and Atmospheric Administration (NOAA) tide gauge, and good agreement in significant wave height (r2 = 0.98) and peak wave period (r2 = 0.65) compared to a nearby USACE sensor. This work demonstrates the potential of the USGS radar for rapid response storm deployments and collecting reliable and accurate hydrodynamic measurements in the nearshore for validating coastal impact models.
","conferenceTitle":"Coastal Dynamics 2025","conferenceDate":"April 7-11, 2025","conferenceLocation":"Aveiro, Portugal","language":"English","publisher":"Springer","doi":"10.1007/978-3-032-15473-6_106","usgsCitation":"Brown, J., McClenney, B.J., and Dickhudt, P., 2026, Measuring storm waves and water levels from a fixed structure with a rapidly deployable oceanographic radar, Coastal Dynamics 2025, Aveiro, Portugal, April 7-11, 2025, p. 696-702, https://doi.org/10.1007/978-3-032-15473-6_106.","productDescription":"7 p.","startPage":"696","endPage":"702","ipdsId":"IP-174186","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":500987,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501099,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-032-15473-6_106","text":"Publisher Index Page"}],"country":"United States","state":"North Carolina","city":"Duck","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Jenna A. 0000-0003-3137-7073","orcid":"https://orcid.org/0000-0003-3137-7073","contributorId":208564,"corporation":false,"usgs":true,"family":"Brown","given":"Jenna A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":956978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClenney, Bryce J 0009-0007-6454-2078","orcid":"https://orcid.org/0009-0007-6454-2078","contributorId":367183,"corporation":false,"usgs":true,"family":"McClenney","given":"Bryce","middleInitial":"J","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickhudt, Patrick J. ","contributorId":169593,"corporation":false,"usgs":false,"family":"Dickhudt","given":"Patrick J. ","affiliations":[{"id":25562,"text":"(former) Woods Hole Coastal and Marine Science Center employee","active":true,"usgs":false}],"preferred":false,"id":956980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274668,"text":"70274668 - 2026 - Who needs closure? Estimating abundance with a Markovian availability model for geographically open removal sampling","interactions":[],"lastModifiedDate":"2026-04-03T15:59:32.312798","indexId":"70274668","displayToPublicDate":"2026-03-05T08:51:53","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Who needs closure? Estimating abundance with a Markovian availability model for geographically open removal sampling","docAbstract":"Removal sampling is an important method for estimating abundance, but nearly all removal models assume closure during sampling. Yet, closure may be difficult to assume, evaluate, or enforce in many settings. To address situations where populations are geographically open between each removal sample, we incorporated a Markovian availability process into an N-mixture model framework. This model relates local abundance available for sampling to a superpopulation through recruitment of new individuals to the sampling area. To test the model, we (1) conducted parameter identifiability analysis, (2) fit the model to removal data generated from a random walk movement model, and (3) analyzed a case study of empirical removal data. Parameters were increasingly identifiable as capture probability exceeded 0.25 and removal samples increased from 3 to 6. Abundance estimates were unbiased when parameters were identifiable, except for scenarios that simulated a behavioral response to sampling. For our case study, the model estimated negligible recruitment for benthic-oriented fishes, indicating closure, but we found evidence against closure for juvenile Chinook salmon, a highly mobile species. Our removal model allows researchers to formally test closure assumptions, to estimate the degree of closure, and to estimate abundance without bias when closure is violated.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70289","usgsCitation":"Perry, R.W., Pope, A.C., Hendrix, A.N., Kirsch, J.E., Matthias, B.G., and Dodrill, M.J., 2026, Who needs closure? Estimating abundance with a Markovian availability model for geographically open removal sampling: Ecology, v. 107, no. 3, e70289, 17 p., https://doi.org/10.1002/ecy.70289.","productDescription":"e70289, 17 p.","ipdsId":"IP-173976","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.83191369646093,\n 38.29270493761476\n ],\n [\n -121.83191369646093,\n 37.97384682645672\n ],\n [\n -121.44796698911333,\n 37.97384682645672\n ],\n [\n -121.44796698911333,\n 38.29270493761476\n ],\n [\n -121.83191369646093,\n 38.29270493761476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"107","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220177,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrix, A. Noble","contributorId":369226,"corporation":false,"usgs":false,"family":"Hendrix","given":"A.","middleInitial":"Noble","affiliations":[{"id":87738,"text":"QEDA Consulting, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":958641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirsch, Joseph E.","contributorId":369227,"corporation":false,"usgs":false,"family":"Kirsch","given":"Joseph","middleInitial":"E.","affiliations":[{"id":87739,"text":"U.S. Fish and Wildlife Service, Lodi Fish and Wildlife Office, Lodi, CA","active":true,"usgs":false}],"preferred":false,"id":958642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matthias, Bryan G.","contributorId":369228,"corporation":false,"usgs":false,"family":"Matthias","given":"Bryan","middleInitial":"G.","affiliations":[{"id":87739,"text":"U.S. Fish and Wildlife Service, Lodi Fish and Wildlife Office, Lodi, CA","active":true,"usgs":false}],"preferred":false,"id":958643,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":958644,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274672,"text":"70274672 - 2026 - The impacts of co-circulating pathogens in Pacific herring depend on interactions between viral life-cycle traits and transmission parameters, highlighting interdependencies between pathogen epizootics","interactions":[],"lastModifiedDate":"2026-04-03T15:48:44.185294","indexId":"70274672","displayToPublicDate":"2026-03-05T08:37:06","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23782,"text":"Philosophical Transactions of the Royal Society, Series B","active":true,"publicationSubtype":{"id":10}},"title":"The impacts of co-circulating pathogens in Pacific herring depend on interactions between viral life-cycle traits and transmission parameters, highlighting interdependencies between pathogen epizootics","docAbstract":"The average host susceptibility decreases as the epizootic progresses because easily infected hosts are first removed from the population. While host susceptibility is pathogen-specific, it is likely that host susceptibility is correlated between different pathogens, so that co-circulating pathogens may have reciprocal impacts on their epidemics. However, despite well-documented examples of concomitant infections in marine hosts, reciprocal epizootic effects have not been documented in wild marine organisms. We quantify reciprocal impacts between viral haemorrhagic septicaemia and viral erythrocytic necrosis in Pacific herring (Clupea pallasii) using field and laboratory work. We show that the causative viruses for both diseases circulate through herring populations and that infection with one pathogen has negative impacts on the epizootic and infection characteristics of the other pathogen, suggesting positive correlations in the susceptibility to infection between pathogens. We then use simulations of a two-strain pathogen model to show that the impact of the correlation is modulated by transmission parameters, such as the incubation period and the initial transmission rate. Our work shows that co-occurring epizootics pose a management challenge because single-pathogen management actions may amplify the epizootics of the non-targeted pathogen. This study provides a framework to evaluate the consequences of reciprocal epizootic impacts through field, experimental and modelling work.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rstb.2024.0329","usgsCitation":"Páez, D.J., Grady, C.A., Gregg, J.L., Batts, W.N., Ferreiro-Luce, S., Herron, V.L., Loeher, M.M., Williamson, S., and Hershberger, P., 2026, The impacts of co-circulating pathogens in Pacific herring depend on interactions between viral life-cycle traits and transmission parameters, highlighting interdependencies between pathogen epizootics: Philosophical Transactions of the Royal Society, Series B, v. 381, no. 1945, 20240329, 12 p., https://doi.org/10.1098/rstb.2024.0329.","productDescription":"20240329, 12 p.","ipdsId":"IP-180382","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Port Angeles Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.46245173833248,\n 48.14469328364527\n ],\n [\n -123.46245173833248,\n 48.11631496533502\n ],\n [\n -123.39897354240969,\n 48.11631496533502\n ],\n [\n -123.39897354240969,\n 48.14469328364527\n ],\n [\n -123.46245173833248,\n 48.14469328364527\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"381","issue":"1945","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Páez, David James 0000-0001-9035-394X","orcid":"https://orcid.org/0000-0001-9035-394X","contributorId":296751,"corporation":false,"usgs":true,"family":"Páez","given":"David","middleInitial":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grady, Courtney Ann 0009-0001-9079-2501","orcid":"https://orcid.org/0009-0001-9079-2501","contributorId":369229,"corporation":false,"usgs":true,"family":"Grady","given":"Courtney","middleInitial":"Ann","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batts, William N.","contributorId":369230,"corporation":false,"usgs":false,"family":"Batts","given":"William","middleInitial":"N.","affiliations":[{"id":87741,"text":"Formerly U.S. Geological Survey, Western Fisheries Research Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":958651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferreiro-Luce, Shayla","contributorId":369245,"corporation":false,"usgs":false,"family":"Ferreiro-Luce","given":"Shayla","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":958682,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herron, V. L.","contributorId":369247,"corporation":false,"usgs":false,"family":"Herron","given":"V.","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":958683,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loeher, Malina Mariko 0000-0001-9589-5641","orcid":"https://orcid.org/0000-0001-9589-5641","contributorId":365991,"corporation":false,"usgs":true,"family":"Loeher","given":"Malina","middleInitial":"Mariko","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williamson, Sarah","contributorId":369231,"corporation":false,"usgs":false,"family":"Williamson","given":"Sarah","affiliations":[{"id":87742,"text":"Alaska Pacific University, Fisheries, Aquatic Science, and Technology Laboratory, 4101 University Drive, Anchorage, AK","active":true,"usgs":false}],"preferred":false,"id":958653,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958654,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274267,"text":"70274267 - 2026 - Comparison of nonlethal techniques as indicators of lipid content in Lake Whitefish","interactions":[],"lastModifiedDate":"2026-03-24T15:28:44.904443","indexId":"70274267","displayToPublicDate":"2026-03-05T08:20:47","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of nonlethal techniques as indicators of lipid content in Lake Whitefish","docAbstract":"Objective
Energetic reserves are important indicators of the relative health of fish and fish populations. Body condition indices that relate fish weight to length are commonly used as quick, noninvasive methods for approximating lipid content and condition. A microwave meter (i.e., fat meter or energy meter) is a noninvasive method found to be more accurate in some species. The objective of this study was to evaluate the suitability of nonlethal techniques for estimating muscle lipid content in Lake Whitefish Coregonus clupeaformis.
Methods
We compared the sensitivity of three nonlethal indicators of lipid content to laboratory-extracted muscle lipid content in Lake Whitefish, including readings from a handheld microwave meter at several positions, Fulton’s condition factor, and relative weight.
Results
We found significant, positive relationships between lipid content and each estimation method, except relative weight, with weak to moderate correlations. The microwave meter was moderately correlated to lipid content when positioned anterior to the dorsal fin above the lateral line (r2 = 0.50), while other positions and combinations of positions had weaker correlations (r2 range = 0.27–0.45). Correlation was only slightly improved by including additional model variables (i.e., length and weight). Fulton’s condition factor was weakly correlated with lipid content (r2 = 0.19), while relative weight was not significantly correlated with lipid content.
Conclusion
The microwave meter provides an improvement to muscle lipid estimation compared with length–weight body condition indices; however, microwave meter readings alone do not constitute a reliable predictive measure for true muscle lipid content under the conditions tested here. We hypothesize that the low strength of correlation may be due to low muscle lipid content or the presence of thick scales in Lake Whitefish. Further investigation is needed to understand the mechanisms negatively affecting the predictive performance of the microwave meter in Lake Whitefish and other species.
","language":"English","publisher":"American Fisheries Society","doi":"10.1093/tafafs/vnag002","usgsCitation":"Funnell, T.R., Shrestha, J., Leads, R.R., Holbrook, C.M., Sano, K., and Murphy, C.A., 2026, Comparison of nonlethal techniques as indicators of lipid content in Lake Whitefish: Transactions of the American Fisheries Society, vnag002, 9 p., https://doi.org/10.1093/tafafs/vnag002.","productDescription":"vnag002, 9 p.","ipdsId":"IP-164860","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501674,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/tafafs/vnag002","text":"Publisher Index Page"},{"id":501453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","city":"St. Ignace","otherGeospatial":"northern Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.68726826607411,\n 45.970689451800894\n ],\n [\n -84.68726826607411,\n 45.75821537500693\n ],\n [\n -84.21785270269774,\n 45.75821537500693\n ],\n [\n -84.21785270269774,\n 45.970689451800894\n ],\n [\n -84.68726826607411,\n 45.970689451800894\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Funnell, Tyler Reid 0000-0002-9074-3531","orcid":"https://orcid.org/0000-0002-9074-3531","contributorId":334195,"corporation":false,"usgs":true,"family":"Funnell","given":"Tyler","email":"","middleInitial":"Reid","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":957473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shrestha, Jenus","contributorId":367695,"corporation":false,"usgs":false,"family":"Shrestha","given":"Jenus","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":957474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leads, Rachel R.","contributorId":367696,"corporation":false,"usgs":false,"family":"Leads","given":"Rachel","middleInitial":"R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":957475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":957476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sano, Koji","contributorId":367697,"corporation":false,"usgs":false,"family":"Sano","given":"Koji","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":957477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Cheryl A.","contributorId":367698,"corporation":false,"usgs":false,"family":"Murphy","given":"Cheryl","middleInitial":"A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":957478,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274669,"text":"70274669 - 2026 - From understanding to action: Integrating new and old methodologies to manage marine infectious disease","interactions":[],"lastModifiedDate":"2026-04-03T15:12:56.68187","indexId":"70274669","displayToPublicDate":"2026-03-05T08:08:04","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23782,"text":"Philosophical Transactions of the Royal Society, Series B","active":true,"publicationSubtype":{"id":10}},"title":"From understanding to action: Integrating new and old methodologies to manage marine infectious disease","docAbstract":"Marine diseases can have far-reaching effects on population, community and ecosystem health; however, our ability to track, predict and manage these diseases has, historically, been poor. As a result, the fields of disease ecology and epidemiology have developed at a slower pace for marine than terrestrial systems [1]. New methodologies, including genomic tools for diagnostics [2,3], transcriptomic tools for measuring host and pathogen responses to infection (e.g. [4,5]), regional oceanic modelling systems that estimate environmental conditions influencing pathogen dispersal and disease progression [6], artificial intelligence methods for quantifying pathology from images (e.g. [7]) and advanced disease modelling techniques [8,9] are precipitating a rapid increase in our understanding of marine pathosystems. In 2016, these efforts led to the first special issue of Philosophical Transactions of the Royal Society B (Marine diseases, volume 371, issue 1689) focused entirely on marine disease ecology and evolution, and in 2020, the first book, Marine disease ecology, was devoted to this topic [10].
This special issue, focused on marine disease management, is being published a decade after the first Philosophical Transactions special issue on marine diseases. The shift to a management focus reflects an urgent need for management strategies to address high-impact diseases and the rapid methodological advances that have resulted. The papers included in this issue demonstrate the value of combining classical approaches (e.g. routine disease surveillance, reductionistic pathogen challenge trials, rapid throughput diagnostics) with cutting-edge technologies (e.g. high-resolution oceanographic models, Bayesian models, replicated transcriptomic studies) to identify drivers of disease, quantify impacts and suggest management strategies.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rstb.2024.0318","usgsCitation":"Groner, M.L., Paez, D.J., and Gehman, A.M., 2026, From understanding to action: Integrating new and old methodologies to manage marine infectious disease: Philosophical Transactions of the Royal Society, Series B, v. 381, no. 1945, 20240318, 4 p., https://doi.org/10.1098/rstb.2024.0318.","productDescription":"20240318, 4 p.","ipdsId":"IP-185260","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"381","issue":"1945","noUsgsAuthors":false,"publicationDate":"2026-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":292708,"corporation":false,"usgs":false,"family":"Groner","given":"Maya","middleInitial":"L.","affiliations":[{"id":62985,"text":"Senior Research Scientist, Bigelow Laboratory for Ocean Sciences, 60 Bigelow Drive, East Boothbay, ME 04544","active":true,"usgs":false}],"preferred":false,"id":958645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Páez, David James 0000-0001-9035-394X","orcid":"https://orcid.org/0000-0001-9035-394X","contributorId":296751,"corporation":false,"usgs":true,"family":"Páez","given":"David","middleInitial":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":958646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gehman, Alyssa-Lois M.","contributorId":335110,"corporation":false,"usgs":false,"family":"Gehman","given":"Alyssa-Lois","middleInitial":"M.","affiliations":[{"id":80312,"text":"Hakai Institute; University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":958647,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273889,"text":"70273889 - 2026 - Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA","interactions":[],"lastModifiedDate":"2026-03-23T14:02:07.561392","indexId":"70273889","displayToPublicDate":"2026-03-04T08:59:53","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA","docAbstract":"Large magnitude snow avalanches (destructive size ≥ D3) impact settlements, transportation corridors, and public safety worldwide. In Colorado, United States, avalanches have killed more people than any other natural hazard since 1950. In March 2019, a large magnitude avalanche cycle occurred throughout the entire mountainous portion of Colorado resulting in more than 1000 reported avalanches during a two-week period. Nearly 200 of these avalanches were size D4 or larger with at least three D5 avalanches. However, placing this 2019 large magnitude avalanche cycle in historic context requires data prior to the instrumental record. Here, we paired tree disturbance data from dendrochronology (1698 to 2020) with meteorological data from the modeled and instrumental record (1901 to 2020) to understand the frequency and climate drivers of large magnitude snow avalanche cycles. The extensive number of downed trees from the 2019 avalanche cycle allowed us to collect 1,188 cross-sections and cores from 1023 individual trees within 24 avalanche paths across the state. From these samples we identified 4135 avalanche-related growth disturbances. We employed a strategic nested sampling design to spatially aggregate avalanche frequency from individual avalanche paths, to counties, to three major sub-regions (i.e., north, central, and south), and across the entire region (i.e., state of Colorado). Over a period spanning more than three centuries (1698 to 2020), we identified 76 avalanche years within 24 individual avalanche paths. Large magnitude avalanche event frequency varied across paths and sub-regions with several notable region-wide avalanche cycles. Both tree-ring and historical written records highlighted 1899 as a year with widespread and large magnitude avalanche activity similar to the March 2019 avalanche cycle. Since the early-20th century (1900 to 2020) regional avalanche probability declined significantly in parallel with decreasing snowpack throughout Colorado. Similarly, dominant avalanche regimes shifted from large magnitude regional cycles driven by above average snowfall years over most of the record, to regional avalanche cycles occurring more commonly in average to low snow years since 1988. In recent decades, a lack of December precipitation and above average March precipitation characterized years with regional large magnitude avalanche activity. Even with declining snow water equivalent, truly extreme regional large magnitude avalanche cycles remain possible – as demonstrated by the 2019 cycle. This underscores that rare but high-impact events are not eliminated by long-term trends. Understanding the changing snow and weather drivers and subsequent behavior of large magnitude avalanche cycles across multiple spatial scales may improve avalanche forecasting and the products and mitigations strategies developed by structural engineers to mitigate avalanche danger. This can decrease the avalanche risk to the public and improve infrastructure design in avalanche terrain.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/nhess-26-1059-2026","usgsCitation":"Peitzsch, E.H., Martin, J.T., Greene, E.M., Eckert, N., Favillier, A., Konigsberg, J., Kichas, N., Stahle, D.K., Birkeland, K.W., Elder, K., and Pederson, G.T., 2026, Changing drivers of regional large magnitude avalanche frequency throughout Colorado, USA: Natural Hazards and Earth System Sciences, v. 26, p. 1059-1074, https://doi.org/10.5194/nhess-26-1059-2026.","productDescription":"16 p.","startPage":"1059","endPage":"1074","ipdsId":"IP-175486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501654,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-26-1059-2026","text":"Publisher Index Page"},{"id":499809,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.129166385724,\n 41.04962213955744\n ],\n [\n -109.129166385724,\n 36.99334376580887\n ],\n [\n -102.04655644997314,\n 36.99334376580887\n ],\n [\n -102.04655644997314,\n 41.04962213955744\n ],\n [\n -109.129166385724,\n 41.04962213955744\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2026-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science 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Nicolas","contributorId":330971,"corporation":false,"usgs":false,"family":"Eckert","given":"Nicolas","email":"","affiliations":[{"id":27334,"text":"Universite Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":955443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Favillier, Adrien","contributorId":330970,"corporation":false,"usgs":false,"family":"Favillier","given":"Adrien","email":"","affiliations":[{"id":66013,"text":"University of Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":955444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Konigsberg, Jason","contributorId":330955,"corporation":false,"usgs":false,"family":"Konigsberg","given":"Jason","email":"","affiliations":[{"id":40054,"text":"Colorado Avalanche Information Center","active":true,"usgs":false}],"preferred":false,"id":955445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kichas, Nickolas","contributorId":366210,"corporation":false,"usgs":false,"family":"Kichas","given":"Nickolas","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":955446,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stahle, Daniel K.","contributorId":210004,"corporation":false,"usgs":true,"family":"Stahle","given":"Daniel","middleInitial":"K.","affiliations":[],"preferred":false,"id":955447,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Birkeland, Karl W.","contributorId":173366,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","middleInitial":"W.","affiliations":[{"id":27213,"text":"USDA Forest Service National Avalanche Center, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":955448,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Elder, Kelly","contributorId":346220,"corporation":false,"usgs":false,"family":"Elder","given":"Kelly","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":955449,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":955450,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274161,"text":"ofr20261065 - 2026 - Evaluation of pathogen risks and testing considerations for Chinook salmon egg movements between New Zealand and California","interactions":[],"lastModifiedDate":"2026-03-04T15:20:21.949375","indexId":"ofr20261065","displayToPublicDate":"2026-03-03T12:16:41","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":"2026-1065","displayTitle":"Evaluation of Pathogen Risks and Testing Considerations for Chinook Salmon Egg Movements Between New Zealand and California","title":"Evaluation of pathogen risks and testing considerations for Chinook salmon egg movements between New Zealand and California","docAbstract":"Oncorhynchus tshawytscha (Walbaum in Artedi, 1792; Chinook salmon) were historically abundant in the McCloud River but are now extirpated from this tributary owing to dam construction and lack of passage. Planning efforts to restore populations above Shasta and Keswick Dams are currently underway, including an evaluation of potential source populations. One potential source is New Zealand Chinook salmon, which are believed to have originated from tributaries of the Sacramento River. These fish could be returned to California if reintroduction risks, including risks of pathogen introduction, could be sufficiently mitigated. The U.S. Geological Survey was contracted to provide scientific support for reintroduction efforts, including evaluating the risks of pathogen transmission via the movement of Chinook salmon eggs from New Zealand to the McCloud River. This report estimates pathogen risks associated with egg movement and considers epidemiological and biosecurity measures to minimize these risks.
Pathogen risks associated with the movement of Chinook salmon eggs from New Zealand were evaluated based on pathogen virulence, transmission route, and geographic distribution. These criteria identified 14 moderate- and high-risk pathogens out of the 30 pathogens evaluated. Pathogen species and strains were considered high risk if they have the potential for vertical transmission (that is, transmission from parent to offspring), are moderately or highly virulent, and are exotic to the Sacramento River Basin. According to these criteria, we identified the following pathogens as high risk:
Strategic use of testing and biosecurity measures can minimize pathogen risks associated with the movement of eggs. The most effective measures include iodophor treatment of eggs to remove external pathogens, testing of all the adult fish from which gametes are obtained, and a quarantine period after transport to confirm pathogen testing results. Additional measures to enhance biosecurity could include testing the quarantined fish following emergence and (or) developing a fish health history of the source population through pathogen monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261065","collaboration":"Prepared in cooperation with California Department of Fish and Wildlife, Anchor QEA, and HDR","programNote":"Land Management Research Program and Species Management Research Program","usgsCitation":"Couch, C.E., Powell, D.B., and Lovy, J., 2026, Evaluation of pathogen risks and testing considerations for Chinook salmon egg movements between New Zealand and California: U.S. Geological Survey Open-File Report 2026–1065, 18 p., https://doi.org/10.3133/ofr20261065.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-182977","costCenters":[{"id":654,"text":"Western Fisheries Research 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\"}}]}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
5501- A Cook Underwood Road
Cook, Washington 98605-9717
This report presents the results of a cooperative study by the U.S. Geological Survey and Missouri Department of Natural Resources to quantify sediment transport source contributions in the Medicine Creek drainage basin. Understanding relative source contributions provides valuable information for selecting the conservation practices that may be most effective in reducing sediment and sediment-associated nutrient transport in the Medicine Creek drainage basin and similar areas of the Lower Grand River drainage basin. Sediment samples were collected from potential contributing areas (source samples) and from fluvial-transported samples (target samples). Source sample types included streambanks, row crop fields, and a combined pastures and forests category. Samples were analyzed for particle size and quantity of carbon, nitrogen, stable isotopes of carbon and nitrogen, and 49 mineral elements as potential tracers. Results for the carbon stable isotope ratio of carbon-13/carbon-12 (δ13C) and concentrations of total carbon, total nitrogen, calcium, potassium, and copper were selected by discriminant function analysis as the best combination of multiple tracers to differentiate each source type. The discriminant function analysis poorly differentiated pastures and forests, so these source types were combined. The sources defined by the discriminant function analysis were then used in an unmixing model to apportion sources for each target sample.
In the study area, transported sediment was predominantly bank sediment, with an overall average of 86.9 percent of suspended-sediment samples and depositional streambed samples attributed to bank material. Suspended-sediment samples from the mainstem of Medicine Creek were dominated by bank sediments (average of 95.8 percent), and depositional streambed samples from throughout the drainage basin had more variable source contributions with an average of 71.1 percent attributed to bank material. The relative importance of upland sources (row crop fields and the combined pastures and forests category) varied seasonally and with streamflow but was not related to land use or drainage basin size. Relative contributions from upland sources were greater in the summer through winter rather than spring and during lower streamflow, though this may be driven by the seasonality of streamflow. These results indicate management practices that reduce bank erosion could be effective strategies for managing the dominant source of sediment and sediment-associated phosphorus.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265121","collaboration":"Prepared in cooperation with Missouri Department of Natural Resources","usgsCitation":"Garrett, J.D., 2026, Stream sediment sources in Medicine Creek, northern Missouri and southern Iowa: U.S. Geological Survey Scientific Investigations Report 2026–5121, 11 p., https://doi.org/10.3133/sir20265121.","productDescription":"Report: vi, 11 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164057","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501166,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119303.htm","linkFileType":{"id":5,"text":"html"}},{"id":500681,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":500680,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13EN5TA","text":"USGS data release","linkHelpText":"Chemical and physical data for sediment source and fluvial target samples for fingerprinting of suspended and bed sediment in Medicine Creek, Missouri and Iowa"},{"id":500679,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265121/full"},{"id":500678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5121/images/"},{"id":500677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.XML"},{"id":500676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5121/sir20265121.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5121"},{"id":500675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5121/coverthb.jpg"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Medicine Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1667,\n 40.75\n ],\n [\n -93.5,\n 40.75\n ],\n [\n -93.5,\n 40\n ],\n [\n -93.1667,\n 40\n ],\n [\n -93.1667,\n 40.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
Controlling invasive wildlife species relies on the ability to efficiently remove individuals from the invaded environment. Thus, maximizing capture potential is of high interest, particularly for species that are difficult to capture. For invasive species such as the Argentine black and white tegu lizard (Salvator merianae), increasing attraction to traps could increase the probability of removal. While it has been established that S. merianae can be lured with a single chicken egg, the efficacy of increasing olfactory or visual cues to increase tegu captures has not been rigorously tested. To test this, we leveraged an ongoing National Park Service trapping effort near Everglades National Park. In 2023 and 2024, we randomly assigned traps to a control treatment (single real egg), increased olfactory and visual treatment (three real eggs), an increased visual plus standard olfactory treatment (one real egg and one decoy egg, or one real egg and two decoy eggs), or visual treatment only (three decoy eggs). We fitted Bayesian binomial models for tegu lizards and non-target species to the trapping data to assess how bait treatment, trap style, and trap location affected the daily probability of capture at a trap. Additionally, we fitted Bayesian linear models to test the effect of bait treatment on the size of tegus captured. We found that increasing the olfactory cue to three real eggs increased the probability of tegu capture, but not the probability of non-target species capture. Conversely, traps with one real egg and two decoy eggs increased the probability of non-target captures while reducing the probability of tegu captures. Trap style and trap location also had statistically significant effects. Bait treatment did not significantly influence the size of tegus captured; however, there was a weak effect suggesting juvenile and male tegus captured in traps with three real eggs were larger compared to traps with a single egg and two decoy eggs. Our results highlight potential improvements in tegu control methods that balance effective capture with minimizing non-target bycatch.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/famrs.2026.1758585","usgsCitation":"Kissel, A.M., Donmoyer, K.L., Sandfoss, M.R., Howard, J.C., Romagosa, C.M., and Yackel Adams, A.A., 2026, Efficacy of increased visual and olfactory cues for luring and trapping invasive tegu lizards: Frontiers in Amphibian and Reptile Science, v. 4, 1758585, 10 p., https://doi.org/10.3389/famrs.2026.1758585.","productDescription":"1758585, 10 p.","ipdsId":"IP-183287","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":501599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/famrs.2026.1758585","text":"Publisher Index Page"},{"id":501498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park, Southern Glades and Frog Pond Wildlife areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.72257615830546,\n 25.470240548699877\n ],\n [\n -80.72257615830546,\n 25.321246280361024\n ],\n [\n -80.52864489446742,\n 25.321246280361024\n ],\n [\n -80.52864489446742,\n 25.470240548699877\n ],\n [\n -80.72257615830546,\n 25.470240548699877\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2026-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":957792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donmoyer, Kevin L.","contributorId":150242,"corporation":false,"usgs":false,"family":"Donmoyer","given":"Kevin","middleInitial":"L.","affiliations":[{"id":17944,"text":"University of Hawaii, Pacific Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":957793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sandfoss, Mark Robert 0000-0002-0162-7265","orcid":"https://orcid.org/0000-0002-0162-7265","contributorId":328884,"corporation":false,"usgs":true,"family":"Sandfoss","given":"Mark","email":"","middleInitial":"Robert","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":957794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howard, James C.","contributorId":178546,"corporation":false,"usgs":false,"family":"Howard","given":"James","middleInitial":"C.","affiliations":[{"id":54672,"text":"National Park Service, Everglades National Park, 40001 SR 9336, Homestead, Florida 33034, USA","active":true,"usgs":false}],"preferred":false,"id":957795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":316356,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","middleInitial":"M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":957796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":957797,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274499,"text":"70274499 - 2026 - Brewing change in the (glacier) percolation zone","interactions":[],"lastModifiedDate":"2026-03-27T17:10:12.038922","indexId":"70274499","displayToPublicDate":"2026-03-01T12:09:12","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":691,"text":"Alaska Park Science","printIssn":"1545- 496","active":true,"publicationSubtype":{"id":10}},"title":"Brewing change in the (glacier) percolation zone","docAbstract":"Alaska's glaciers are losing mass at the fastest rate of any region globally, significantly affecting both the volume and distribution of water across the landscape. Though glaciers in the Alaska region (as defined by glaciologists this includes both Alaska and portions of adjacent Canada) range from sea level to nearly 6200 m (20,320 ft), the majority of glacier area in the Alaska region is concentrated between 900 and 2100 m (2950 to 6890 ft). Long term glacier monitoring in Alaska by the U.S. Geological Survey (USGS) Benchmark Glacier Project is on moderate-sized glaciers with distributions of glacier area in this elevation range. These are some of the longest in-situ records of glacier mass change in the world. The process-based understanding of glacier change on those “Benchmark Glaciers” is robust, but it is limited to the range of conditions present on those particular glaciers—at moderate elevations—where large amounts of melt water and rain pass through the glacier and into the downstream ecosystem on an annual basis.","language":"English","publisher":"U.S. National Park Sevice","usgsCitation":"Sass, L., McNeil, C., Baker, E.A., Frederick, Z.A., and Loso, M., 2026, Brewing change in the (glacier) percolation zone: Alaska Park Science, v. 24, no. 1, p. 2-15.","productDescription":"14 p.","startPage":"2","endPage":"15","ipdsId":"IP-182134","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":501727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501707,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2317596"}],"country":"United 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0000-0003-3443-5419","orcid":"https://orcid.org/0000-0003-3443-5419","contributorId":361983,"corporation":false,"usgs":false,"family":"Baker","given":"Emily","middleInitial":"A.","affiliations":[{"id":86409,"text":"Hamilton College, Wisconsin Geological and Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":958019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frederick, Zanden Arthur 0009-0007-9365-0334","orcid":"https://orcid.org/0009-0007-9365-0334","contributorId":368877,"corporation":false,"usgs":true,"family":"Frederick","given":"Zanden","middleInitial":"Arthur","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":958020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loso, Michael","contributorId":353465,"corporation":false,"usgs":false,"family":"Loso","given":"Michael","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":958021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274628,"text":"70274628 - 2026 - Abandonment of the Upper Devonian Greenland Gap Group and Scherr Formation and revision of the Upper Devonian Brallier and Foreknobs Formations in the central Valley and Ridge Province","interactions":[],"lastModifiedDate":"2026-04-02T16:08:57.895011","indexId":"70274628","displayToPublicDate":"2026-03-01T09:00:45","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Abandonment of the Upper Devonian Greenland Gap Group and Scherr Formation and revision of the Upper Devonian Brallier and Foreknobs Formations in the central Valley and Ridge Province","docAbstract":"This study revises the lithostratigraphic framework of the Upper Devonian interval traditionally assigned to the Greenland Gap Group across the central Appalachian Valley and Ridge Province. The work aims to modernize and standardize lithostratigraphic nomenclature, establish a new reference section and demonstrate how the revised stratigraphy improves edge-matching of 1:24,000 scale geologic maps and supports compilation mapping at scales of 1:100,000 and larger. The revision eliminates the names Greenland Gap Group, Scherr Formation and the Minnehaha Springs Member of the Scherr Formation; reassigns all strata previously designated as Scherr Formation by Dennison (1970) to the upper Brallier Formation; and abandons the basal Mallow Member of the Foreknobs Formation, placing its strata within the upper Brallier as originally defined by Butts (1918).\n\nThe contact between the Brallier and Foreknobs formations is placed at the base of the first mappable, ridge-forming package of fine- to coarse-grained, cross-bedded, sandstone beds, often containing rounded quartz pebbles with minor interbeds of shale and siltstone. This contact may be gradational in places but, even in absence of good exposure, can usually be distinguished topographically in recently produced lidar-derived imagery as having elevated relief due to the presence of more resistant, compositionally mature coarse-grained sandstone-rich strata. Applying this criterion for mapping the contact between the Brallier and Foreknobs formations has resulted in reconciliation of mismatches of geologic contacts along several 7.5-minute quadrangle boundaries in the states of Virginia, West Virginia, Maryland and Pennsylvania. A new reference section at Baker, West Virginia showcases the contacts between the Harrell Shale, Brallier Formation, Foreknobs Formation and Hampshire Formation. A digital outcrop model of the reference section is provided for future preservation.","language":"English","publisher":"Micropaleontology Press","doi":"10.29041/strat.23.1.03","usgsCitation":"Pitts, A.D., and Doctor, D.H., 2026, Abandonment of the Upper Devonian Greenland Gap Group and Scherr Formation and revision of the Upper Devonian Brallier and Foreknobs Formations in the central Valley and Ridge Province: Stratigraphy, v. 23, no. 1, p. 31-44, https://doi.org/10.29041/strat.23.1.03.","productDescription":"14 p.","startPage":"31","endPage":"44","ipdsId":"IP-153186","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":502010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.5837839625223,\n 41.90737349195368\n ],\n [\n -80.97986900952827,\n 39.8912761703621\n ],\n [\n -82.00598531940697,\n 38.93662885204664\n ],\n [\n -82.63094418286235,\n 38.26806111836963\n ],\n [\n -82.14502301832408,\n 37.467676901275595\n ],\n [\n -83.57714608050935,\n 36.57298398456588\n ],\n [\n -75.54432999451647,\n 36.46466032532334\n ],\n [\n -75.54432999451647,\n 41.90737349195368\n ],\n [\n -80.5837839625223,\n 41.90737349195368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pitts, Alan D. 0000-0002-9661-4917","orcid":"https://orcid.org/0000-0002-9661-4917","contributorId":350522,"corporation":false,"usgs":true,"family":"Pitts","given":"Alan","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":958490,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","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":958491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274284,"text":"70274284 - 2026 - Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder","interactions":[],"lastModifiedDate":"2026-03-24T17:58:00.328721","indexId":"70274284","displayToPublicDate":"2026-02-28T10:36:32","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder","docAbstract":"Retrieving the phytoplankton absorption coefficient (aphy; m−1), one of the most spectrally rich inherent optical properties, remains challenging in optically complex coastal waters worldwide. Leveraging NASA's new hyperspectral mission, PACE, we introduce Hyper-MoE-VAE, a deep-learning architecture that integrates a Mixture-of-Experts with a Variational Autoencoder to retrieve high-dimensional aphy and subsequent estimation of phytoplankton community composition (PCC) from PACE-OCI hyperspectral remote sensing reflectance (Rrs). Pre-trained on global hyperspectral bio-optical datasets and fine-tuned using regional field Rrs–aphy pairings from inland– estuarine–coastal waters, Hyper-MoE-VAE demonstrated strong transferability and effective adaptation across regions. Validation with in-situ Rrs showed accurate aphy retrievals in Lake Erie (NRMSE = 0.12, ε = 17.10), Lake Pontchartrain (NRMSE = 0.11, ε = 37.12), and the Barataria–Terrebonne Estuary (NRMSE = 0.14, ε = 38.89). Using same-day PACE-OCI Level 2 Rrs, the model achieved comparable performance in Lake Erie (NRMSE = 0.19, ε = 55.19), Lake Pontchartrain (NRMSE = 0.14, ε = 51.39), and the Barataria–Terrebonne Estuary (NRMSE = 0.17, ε = 47.92). Hyper-MoE-VAE derived PACE-OCI hyperspectral aphy was further decomposed against mass-specific absorption spectra to estimate group-specific contributions to total chlorophyll a. The resulting PCC showed strong agreement with HPLC–CHEMTAX in Lake Erie (R2= 0.692) and Gulf estuarine–coastal systems (R2 = 0.732). Monte Carlo noise experiments further revealed group-dependent sensitivities, with diatoms and dinoflagellates showing moderate susceptibility to noise, while cyanobacteria and cryptophytes exhibited narrow uncertainty distributions. These results demonstrate Hyper-MoE-VAE's capability for regional, operational water-quality monitoring with PACE-OCI and its adaptability to current and future hyperspectral missions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2026.115327","usgsCitation":"Bai, X., Liu, B., Li, J., Xiong, Y., D'Sa, E.J., Baustian, M.M., Zhang, X., Grunert, B.K., Emeghiebo, C.O., Glasspie, C., and Yuan, X., 2026, Hyperspectral retrieval of phytoplankton absorption and community composition from NASA’s PACE-OCI in estuarine–coastal waters using a hybrid framework combining mixture-of-experts and Variational Autoencoder: Remote Sensing of Environment, v. 337, 115327, 21 p., https://doi.org/10.1016/j.rse.2026.115327.","productDescription":"115327, 21 p.","ipdsId":"IP-183464","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":501687,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2026.115327","text":"Publisher Index Page"},{"id":501480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes, Lake Pontchartrain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.98026146025376,\n 46.682013140642226\n ],\n [\n -90.422396423442,\n 35.665871696553445\n ],\n [\n -91.75807129638213,\n 28.880274469368075\n ],\n [\n -85.60463244761702,\n 28.94843644039912\n ],\n [\n -84.63467351669269,\n 34.847516695576886\n ],\n [\n -75.35467727698664,\n 44.62674716649638\n ],\n [\n -79.69951379257085,\n 42.91048225290065\n ],\n [\n -82.43165382508761,\n 42.336846755600035\n ],\n [\n -82.42607197782405,\n 45.94544889925933\n ],\n [\n -87.22784803627331,\n 48.41305438275214\n ],\n [\n -90.76218980539744,\n 47.92081108337736\n ],\n [\n -91.98026146025376,\n 46.682013140642226\n ]\n ]\n ],\n \"type\": 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Center","active":true,"usgs":true}],"preferred":true,"id":957609,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhang, Xiaodong","contributorId":367741,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaodong","affiliations":[{"id":12460,"text":"The University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":957610,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grunert, Brice K.","contributorId":367742,"corporation":false,"usgs":false,"family":"Grunert","given":"Brice","middleInitial":"K.","affiliations":[{"id":18143,"text":"Cleveland State University","active":true,"usgs":false}],"preferred":false,"id":957611,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Emeghiebo, Chisom O.","contributorId":367743,"corporation":false,"usgs":false,"family":"Emeghiebo","given":"Chisom","middleInitial":"O.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":957612,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Glasspie, Cassie","contributorId":367744,"corporation":false,"usgs":false,"family":"Glasspie","given":"Cassie","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":957613,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yuan, Xu","contributorId":367734,"corporation":false,"usgs":false,"family":"Yuan","given":"Xu","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":957614,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274266,"text":"70274266 - 2026 - Extreme precipitation variability and soil texture controls on water-table response","interactions":[],"lastModifiedDate":"2026-03-24T16:31:28.917628","indexId":"70274266","displayToPublicDate":"2026-02-27T09:28:04","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Extreme precipitation variability and soil texture controls on water-table response","docAbstract":"Extreme precipitation events (EPEs), a key class of hydrometeorological extremes, are intensifying globally under climate change; however, their effects on water-table dynamics across varying soil textures remain poorly understood. To better understand the impacts of EPEs, we conducted one-dimensional modeling to evaluate water-table response time, displacement, recession time, and total recharge under EPEs of 0.20 m, 0.40 m, and 0.60 m amounts, applied over 1-, 7-, and 20-day durations across twelve soil textures. The results show that coarse soils (i.e., sand) respond within days, while fine soils (i.e., clay) may take over 200 days. Water-table displacement ranged from 0.30 to 1.64 m and increased with EPE magnitude. The time it took for water tables to recede ranged from 1.2 to 3.0 years. A first-order estimate of total possible recharge, calculated from porosity and displacement, ranged from 17% (clay) to 97% (sand), averaging ~63% across soil textures. These findings highlight that recharge is primarily governed by EPE magnitude and soil properties, not event duration. This modeling effort provides new insight into how soil texture modulates groundwater response to extreme precipitation, informing future water budget and resilience assessments.
","language":"English","publisher":"MDPI","doi":"10.3390/w18050587","usgsCitation":"Corona, C.R., Ge, S., Anderson, S.P., and Dickinson, J.E., 2026, Extreme precipitation variability and soil texture controls on water-table response: Water, v. 18, no. 5, 587, 20 p., https://doi.org/10.3390/w18050587.","productDescription":"587, 20 p.","ipdsId":"IP-160684","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":501680,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w18050587","text":"Publisher Index Page"},{"id":501472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Corona, Claudia R.","contributorId":152548,"corporation":false,"usgs":false,"family":"Corona","given":"Claudia","middleInitial":"R.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":957469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ge, Shemin","contributorId":203465,"corporation":false,"usgs":false,"family":"Ge","given":"Shemin","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":957470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Suzanne P. 0000-0002-6796-6649","orcid":"https://orcid.org/0000-0002-6796-6649","contributorId":172732,"corporation":false,"usgs":false,"family":"Anderson","given":"Suzanne","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":957471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":957472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273969,"text":"sir20255052 - 2026 - Reconstructing the Quaternary depositional history using geologic mapping and three-dimensional modeling of the subsurface near Fort Morgan, northeastern Colorado","interactions":[],"lastModifiedDate":"2026-02-27T21:35:08.45987","indexId":"sir20255052","displayToPublicDate":"2026-02-26T13:00:00","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":"2025-5052","displayTitle":"Reconstructing the Quaternary Depositional History Using Geologic Mapping and Three-Dimensional Modeling of the Subsurface Near Fort Morgan, Northeastern Colorado","title":"Reconstructing the Quaternary depositional history using geologic mapping and three-dimensional modeling of the subsurface near Fort Morgan, northeastern Colorado","docAbstract":"Centered on Fort Morgan, Colorado, this study is intended to build from previous work by adding a three-dimensional (3D) view of the subsurface to better understand the depositional history of Quaternary deposits. A 1:100,000 scale geologic map was made by combining previous geologic maps, regional soil maps, and recent field investigations. In addition to the geologic mapping, drill hole lithologic data from water wells and oil and gas exploration were compiled and lithologic units simplified to best represent the stratigraphy of the Quaternary deposits. From these subsurface data, a 3D subsurface model was constructed, trimmed at the surface by a digital elevation model, and a bedrock surface foundation gridded from drill hole data was added. The surface of the 3D model was then compared visually to the surficial geologic map. Cross sections were constructed from the 3D model and compared to site-specific drilling that was done as part of this project. Finally, the model was examined in detail to reconstruct the depositional history of the subsurface alluvial and eolian units. Alluvial and fluvial drainage basins exposed in the subsurface have a greater areal extent than the present-day narrow drainages. Older eolian sand in the subsurface tends to be interbedded with loess indicating coeval deposition. Holocene sand, both eroded from bedrock exposed at the surface north of the study area and reworked from the South Platte River, buries most of the interbedded older sand and loess.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255052","usgsCitation":"Taylor, E.M., Berry, M.E., Mahan, S.A., and Havens, J.C., 2026, Reconstructing the Quaternary depositional history using geologic mapping and three-dimensional modeling of the subsurface near Fort Morgan, northeastern Colorado: U.S. Geological Survey Scientific Investigations Report 2025–5052, 48 p., https://doi.org/10.3133/sir20255052.","productDescription":"Report: iv, 48 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-095650","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":500655,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119276.htm","linkFileType":{"id":5,"text":"html"}},{"id":500266,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5052/sir20255052.pdf","text":"Report","size":"60.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5052"},{"id":500265,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5052/coverthb.jpg"},{"id":500267,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13KTS2B","text":"USGS data release","linkHelpText":"Luminescence data for: Reconstructing the Quaternary depositional history using geologic mapping and a 3D model of the subsurface in the vicinity of Fort Morgan, Eastern Colorado"},{"id":500268,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AQ72FB","text":"USGS data release","linkHelpText":"Digital drillhole lithologic data and a radiocarbon age -- data supporting interpretation of Quaternary depositional history in the vicinity of Fort Morgan, Eastern Colorado"}],"country":"United States","state":"Colorado","city":"Fort Morgan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.5,\n 40.5\n ],\n [\n -104.5,\n 40.5\n ],\n [\n -104.5,\n 40\n ],\n [\n -103.5,\n 40\n ],\n [\n -103.5,\n 40.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
The eastern box turtle (Terrapene carolina carolina) is a long-lived terrestrial turtle species distributed throughout the eastern United States that has experienced widespread population decline. Many eastern box turtle populations are persisting as remanent populations in small, fragmented urban green spaces. We investigated the movement and resource selection of eastern box turtles within a mid-Atlantic region urban forest in the eastern United States. We used a combination of turtle occurrence data (via visual encounter surveys) and radio telemetry to create resource selection functions. Additionally, we applied a simulation modeling approach and modeled activity areas via dynamic Brownian Bridge Movement Models to quantify interactions between turtles and roads or trails. We also used these models to determine the propensity for turtles to move outside of the managed urban forest boundary and into surrounding development. We observed that turtles selected for deciduous forest patches and avoided roads and trails despite the urban forest having very little available areas where anthropogenic features could be avoided. We also demonstrated observed (and probable) movements outside of the urban forest boundary. Although eastern box turtles are persisting within the urban green space we examined, our work determined that interactions with roads and trails, and movements outside of protected boundaries into developed areas present challenges to individuals navigating the urban forest.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s11252-026-01938-0","usgsCitation":"Jones, M.D., Ferebee, K.B., Ford, W., and Hunter, E.A., 2026, Boxed in or branching out? Movement and resource selection of eastern box turtles (Terrapene carolina carolina) in an urban green space: Urban Ecosystems, v. 29, 72, 14 p., https://doi.org/10.1007/s11252-026-01938-0.","productDescription":"72, 14 p.","ipdsId":"IP-180260","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11252-026-01938-0","text":"Publisher Index Page"},{"id":502028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States, mid-Atlantic region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.51749069483542,\n 39.74954311636529\n ],\n [\n -80.30490645674448,\n 33.87108405455136\n ],\n [\n -77.15471518629862,\n 32.58298528230786\n ],\n [\n -73.67400827908685,\n 39.35915324575973\n ],\n [\n -76.51749069483542,\n 39.74954311636529\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2026-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Max D.","contributorId":369034,"corporation":false,"usgs":false,"family":"Jones","given":"Max","middleInitial":"D.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":958334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferebee, Kenneth B.","contributorId":369035,"corporation":false,"usgs":false,"family":"Ferebee","given":"Kenneth","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":958335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":958336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958337,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273903,"text":"sir20265116 - 2026 - Erosion potential and flood vulnerability of streams and stream crossings at Acadia National Park, Maine","interactions":[],"lastModifiedDate":"2026-02-27T21:38:18.2943","indexId":"sir20265116","displayToPublicDate":"2026-02-26T09:30:00","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":"2026-5116","displayTitle":"Erosion Potential and Flood Vulnerability of Streams and Stream Crossings at Acadia National Park, Maine","title":"Erosion potential and flood vulnerability of streams and stream crossings at Acadia National Park, Maine","docAbstract":"Acadia National Park has had increases in the frequency and magnitude of precipitation in recent years, leading to increased flood flows, stream erosion, and costly infrastructure damage. To improve infrastructure management in a changing climate, the U.S. Geological Survey, in cooperation with the National Park Service, has developed multiple datasets that can help natural resource managers identify stream reaches and stream crossings that have the highest potential for erosion and flood damage within Acadia National Park. To develop these datasets, we first created a lidar- derived hydrography based on a 1- meter digital elevation model and then estimated peak flows at stream crossings and along the stream network using regional regression equations for Maine. We assessed the erosion potential of stream reaches by computing channel morphologic and hydrologic metrics associated with erosive power, such as stream steepness, topographic openness, and percent storage in the contributing watershed. Stream crossing flood vulnerability was assessed by comparing estimated peak flows to stream crossing conveyance capacities. Our results indicate that stream reaches in the headwaters of the Acadia National Park highlands such as Sargent, Penobscot, and Cadillac Mountain, have the highest erosion potential and generally coincide with reaches that have had erosion and infrastructure damage in the past. Stream crossings with the highest flood vulnerability are distributed throughout Mount Desert Island and Acadia National Park, especially south of Jordan Pond, north of Sargent Mountain, and surrounding Eagle Lake. Over a quarter of the total stream crossings have insufficient information to compute flood vulnerability and are often on the parts of the stream with the highest potential for erosion. The datasets allow users to identify stream reaches with the highest erosion potential, stream crossings that are most vulnerable to flood damage, and to highlight areas where supplemental field assessments could most effectively be completed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265116","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Armstrong, I.P., McCallister, M.A., Hyslop, K.M., and Benthem, A.J., 2026, Erosion potential and flood vulnerability of streams and stream crossings at Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2026–5116, 21 p., https://doi.org/10.3133/sir20265116.","productDescription":"Report: vii, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-178032","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":500752,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13Y2RY2","text":"USGS data release","linkHelpText":"Data for an Erosion and Flood Vulnerability Assessment of Streams and Stream Crossings at Acadia National Park, Maine"},{"id":500656,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119275.htm","linkFileType":{"id":5,"text":"html"}},{"id":500517,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://geonarrative.usgs.gov/acadiaerosionfloodvulnerability/","text":"Interactive dashboard","linkHelpText":"- Erosion Potential and Flood Vulnerability of Streams and Stream Crossings at Acadia National Park"},{"id":499819,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265116/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5116 HTML"},{"id":499818,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5116/sir20265116.pdf","size":"7.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5116 PDF"},{"id":499817,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5116/coverthb.jpg"},{"id":499820,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5116/sir20265116.xml","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5116 XML"},{"id":499821,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5116/images/"},{"id":499822,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1EHZNHN","text":"USGS data release","linkHelpText":"Data for an erosion potential and flood vulnerability assessment of streams and stream crossings at Acadia National Park, Maine"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.45003175798666,\n 44.44178922865794\n ],\n [\n -68.45003175798666,\n 44.21621316604151\n ],\n [\n -68.13514216440173,\n 44.21621316604151\n ],\n [\n -68.13514216440173,\n 44.44178922865794\n ],\n [\n -68.45003175798666,\n 44.44178922865794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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The U.S. Geological Survey, in cooperation with the National Park Service, has developed multiple datasets that can help natural resource managers identify stream reaches with the highest potential for erosion and stream crossings most vulnerable to flood damage within Acadia National Park. These datasets allow users to identify areas where supplemental field assessments could be most effectively completed.
","publicationDate":"2026-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Armstrong, Ian P. 0000-0002-8239-8029","orcid":"https://orcid.org/0000-0002-8239-8029","contributorId":344363,"corporation":false,"usgs":true,"family":"Armstrong","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCallister, Meghan A. 0000-0001-8814-7725","orcid":"https://orcid.org/0000-0001-8814-7725","contributorId":358213,"corporation":false,"usgs":true,"family":"McCallister","given":"Meghan","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hyslop, Kristina M. 0009-0001-2525-5574","orcid":"https://orcid.org/0009-0001-2525-5574","contributorId":334465,"corporation":false,"usgs":true,"family":"Hyslop","given":"Kristina","middleInitial":"M.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955713,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273923,"text":"sir20265120 - 2026 - Methods for estimating selected streamflow statistics at ungaged sites in Wyoming based on data through water year 2021","interactions":[],"lastModifiedDate":"2026-02-27T21:40:16.939028","indexId":"sir20265120","displayToPublicDate":"2026-02-26T07:11:17","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":"2026-5120","displayTitle":"Methods for Estimating Selected Streamflow Statistics at Ungaged Sites in Wyoming Based on Data Through Water Year 2021","title":"Methods for estimating selected streamflow statistics at ungaged sites in Wyoming based on data through water year 2021","docAbstract":"The U.S. Geological Survey, in cooperation with the Wyoming Water Development Office, developed regional regression equations based on basin characteristics and streamflow statistics for streamgages through water year 2021 (October 1, 2020, to September 30, 2021). The regression equations allow estimates of mean annual maximum, mean annual, mean seasonal, and mean monthly streamflows; frequency statistics for the 7- day mean low flows with 2- year and 10- year recurrence intervals, 14- and 30- day mean low flows with 5- year recurrence intervals, and 60- and 1- day mean high flow with 2- year and 5- year recurrence intervals, respectively; and the 0.1- , 0.2- , 0.5- , 1- , 2- , 4- , 5- , 10- , 20- , 25- , 30- , 50- , 60- , 70- , 75- , 80- , 90- , 95- , 98- , and 99- percent durations for annual streamflows and 0.1- , 0.5- , 10- , 15- , 20- , 25- , 30- , 40- , 50- , 60- , 70- , 75- , 80- , 85- , 90- , 95- , and 99- percent durations for monthly streamflows for most months for ungaged locations in Wyoming that are largely unaltered by diversions or upstream reservoirs.
Regression equations were developed for 243 streamflow statistics. Best- subset selection was used to assess explanatory variables for respective streamflow statistics. Exploratory data analyses determined that, of the 81 basin characteristics evaluated as potential explanatory variables, characteristics such as drainage area and precipitation often produced models with the highest adjusted coefficient of determination and lowest mean squared error, as determined in the best- subset selection. To address heteroskedasticity of model residuals, model variables were regionalized using fixed- effects models; the percentages of the streamgage basins in selected ecoregions were defined as interaction terms, which represent the model slope for specific ecoregions. Most models were determined to be statistically significant for probability values less than or equal to 0.1 for one or more regional explanatory variables. The final regional regression equations defined in this report are available for use in the U.S. Geological Survey’s StreamStats web application at https://streamstats.usgs.gov/ss/.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265120","collaboration":"Prepared in cooperation with the Wyoming Water Development Office","usgsCitation":"Taylor, N.J., and Sando, R., 2026, Methods for estimating selected streamflow statistics at ungaged sites in Wyoming based on data through water year 2021: U.S. Geological Survey Scientific Investigations Report 2026–5120, 38 p., https://doi.org/10.3133/sir20265120.","productDescription":"Report: vii, 38 p.; 1 Linked Appendix Table; Data Release; Dataset","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-179497","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":500657,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119274.htm","linkFileType":{"id":5,"text":"html"}},{"id":500117,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265120/full"},{"id":500115,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":500111,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5120/sir20265120.XML"},{"id":500114,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14WLVAH","text":"USGS data release","linkHelpText":"Regression equations for selected streamflow statistics based on data through water year 2021 in and near Wyoming"},{"id":500113,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2026/5120/downloads/","text":"Table 1.1","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":500112,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5120/images/"},{"id":500110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5120/sir20265120.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5120"},{"id":500109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5120/coverthb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, North Dakota, South Dakota, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.82002110650585,\n 46.421867179561445\n ],\n [\n -113.82002110650585,\n 39.89961451938157\n ],\n [\n -103.32595673094282,\n 39.89961451938157\n ],\n [\n -103.32595673094282,\n 46.421867179561445\n ],\n [\n -113.82002110650585,\n 46.421867179561445\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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As fragility and risk modeling techniques and computational capabilities evolve, complemented by moving toward more routine and systematic seismic risk assessment of all buildings and critical infrastructure, the authors pose a few critical questions to investigate how the U.S. Geological Survey (USGS) National Seismic Hazard Models (NSHMs) can be used and enhanced further to serve such issues. In this paper, we use three examples from multiple sectors to (1) identify the role of USGS NSHMs in evaluating seismic risks to critical infrastructure, (2) quantify potential impacts from NSHM enhancements (i.e., [i] hazard curves for the vertical component of ground motion, [ii] stochastic event sets, and [iii] maps of probabilistic ground failure hazards), and (3) clarify the feasibility of relevant NSHM improvements. We illuminate that NSHMs are commonly used in location-specific performance assessments, whereas earthquake effects on critical infrastructure can be widespread across large geospatial regions. Further, we found that without the NSHM extensions considered here, risk can be severely underestimated, e.g., neglecting ground failure hazards can underestimate regional loss by a factor of two or more. Although many challenges remain, we developed example prototypes to clarify the feasibility of the NSHM extensions, which can facilitate improved management of risks to critical infrastructure.
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The September 1859 storm disrupted global telegraph operations, the March 1989 storm caused a blackout in Canada and interfered with electric-power-transmission systems in the United States, and other storms have had related impacts. The geographic and temporal dependence of geoelectric fields are functions of both geomagnetic variation and local surface impedance, which differ considerably across different geological regions. These dependencies can be mapped across the contiguous United States by combining magnetotelluric impedance tensors with ground magnetometer time series. This review illustrates such mapping for the 1989 storm and shows that power-system interference was experienced where surface impedance is high, and when and where geoelectric fields were intense. Statistical analyses indicate that storms comparable to that of March 1989 occur roughly once every four solar cycles. Ongoing developments in numerical modeling and real-time monitoring are anticipated to enable prediction of geoelectric hazards.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-earth-032524-012356","usgsCitation":"Love, J.J., Bedrosian, P.A., Kelbert, A., Rigler, E.J., Lucas, G.M., and Schnepf, N.R., 2026, Magnetic storms and geoelectric hazards: Annual Review of Earth and Planetary Sciences, v. 54, https://doi.org/10.1146/annurev-earth-032524-012356.","ipdsId":"IP-180570","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":957846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelbert, Anna","contributorId":367869,"corporation":false,"usgs":false,"family":"Kelbert","given":"Anna","affiliations":[{"id":85814,"text":"Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts, 02138, USA","active":true,"usgs":false}],"preferred":false,"id":957847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957848,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lucas, Greg M.","contributorId":367872,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg","middleInitial":"M.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":957849,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schnepf, Neesha R.","contributorId":367873,"corporation":false,"usgs":false,"family":"Schnepf","given":"Neesha","middleInitial":"R.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":957850,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274573,"text":"70274573 - 2026 - Climate change and water quality influence on juvenile Atlantic sturgeon aggregation in the Altamaha River, Georgia","interactions":[],"lastModifiedDate":"2026-04-01T22:30:59.589279","indexId":"70274573","displayToPublicDate":"2026-02-23T15:25:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and water quality influence on juvenile Atlantic sturgeon aggregation in the Altamaha River, Georgia","docAbstract":"
In the summer, juvenile Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) are vulnerable to extreme water quality conditions (i.e., temperature, dissolved oxygen [DO], and salinity) in the estuaries they inhabit. The effects of climate change on Atlantic sturgeon are largely unknown, but it may exacerbate these water quality issues. We used a 20-year dataset from the Altamaha River estuary, Georgia, USA to fit negative binomial mixed-effects models describing the relationship between water quality and catch per net hour of juvenile Atlantic sturgeon. Water temperature and DO were significant positive predictors of catch; salinity and sampling year were significant negative predictors. The interaction between temperature and DO was also significant. Water temperature, salinity, and year were significant in explaining variability in catch. Our modeling results suggest that response to water quality depends on fish age. Next, we used global climate projections to construct future climate scenarios incorporating warming water and increased salinity. By coupling these predictions with catch models, we forecast juvenile Atlantic sturgeon catch as a proxy for distribution. Water temperature increases of 1–5 °C led to predicted catch increases of 5–24%, although this result may be influenced by aggregation behavior or sampling limitations at high temperatures. Salinity increases of 1–2 ppt led to 9–17% decreases in catch, suggesting that saltwater intrusion may limit future Atlantic sturgeon estuarine habitat availability. Our study combines a long-term dataset with a robust statistical modeling approach to offer some of the first insights into future climate change effects on juvenile Atlantic sturgeon’s southern nursery habitats.
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