Eruptions at Mount Rainier produce lava flows, plumes of airborne volcanic ash, and avalanches of hot rock, ash, and gas—pyroclastic flows—that rush down the steep, ice-covered slopes of the volcano. Hot rock and ash ejected during an eruption can melt large quantities of snow and ice, forming huge, fast moving mudflows called lahars that travel 30+ miles, all the way to Puget Sound. Very large lahars can also form when weak and water-saturated rock high on the volcano collapses with or without volcanic activity. Learn more inside!
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip265","isbn":"978-1-4113-4657-4","usgsCitation":"Weiss-Racine, H.F., Bard, J.A., Ball, J.L, and Mastin, C.L., 2026, Mount Rainier volcanic hazard information: U.S. Geological Survey General Information Product 265, https://doi.org/10.3133/gip265.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-186867","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":503251,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119365.htm","linkFileType":{"id":5,"text":"html"}},{"id":502667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/265/gip265.pdf","text":"Brochure","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 265"},{"id":502666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/265/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.09920525440018,\n 46.5\n ],\n [\n -122.7,\n 46.5\n ],\n [\n -122.7,\n 47.6\n ],\n [\n -121.09920525440018,\n 47.6\n ],\n [\n -121.09920525440018,\n 46.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center
U.S. Geological Survey
David A. Johnston Cascades Volcano Observatory
1300 SE Cardinal Court, Building 10, Suite 100
Vancouver, Washington, 98683-9589
Coral bleaching events have become increasingly common across the Hawaiian Archipelago since 1996 because of more frequent and intense marine heatwaves. The most significant bleaching event to date occurred from 2014 to 2015, which resulted in catastrophic state-wide coral loss. Bleaching events with less severe effects also occurred in 1996 and 2019. To understand the long-term effects of repeated bleaching events, along with other anthropogenic factors such as water quality, storms, sewage runoff, and coastal development, on coral reefs on the Kona Coast of the Island of Hawaiʻi, the U.S. Geological Survey, in collaboration with the National Park Service, collected underwater imagery in the early 2000s (baseline survey) and again in 2022 (resurvey). These images were captured within and adjacent to the National Historic Parks (NHP) and National Historic Sites (NHS) of Kaloko-Honokōhau NHP (KAHO), Puʻuhonua o Hōnaunau NHP (PUHO), and Puʻukohola Heiau NHS (PUHE). Imagery was classified for live coral cover and dominant type (four coral types, rubble, macroalgae, and two bottom substrate types). Change of percent live coral cover was determined for all sites. Change of coral and non-coral dominant types were calculated by aggregating classifications for each park into coral and non-coral. Net coral cover decreased between the baseline and resurvey period across all three parks, though PUHE exhibited the greatest loss of live coral cover. Across all three parks, the occurrence of lower coral cover classes (0–20 percent) increased and higher coral cover classes (greater than 50 percent) decreased. Furthermore, the total occurrence of non-coral dominant type classifications (rubble, macroalgae, sand, and volcanic pavement) increased by approximately 25 percent across all three parks, with PUHE experiencing a nearly 90-percent increase in the occurrence of non-coral types. There was little to no effect of water depth on change of live coral cover, indicating that marine heatwave driven bleaching events and additional anthropogenic influences affected the entire reef across all water depths from the lower fore reef to the reef flat.
Because coral loss was more severe at PUHE and PUHO than KAHO, creating a monitoring framework that utilizes periodic underwater camera surveys and fixed diver transects by the National Park Service would contextualize the periodic spatial surveys to the fixed transects that have greater temporal resolution. Similarly, increased frequency of spatial surveys would allow for the National Park Service to continue monitoring changes to critical nearshore habitats and marine resources relevant to National Park jurisdiction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261061","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"McPherson, M.L., Logan, J.B., Alkins, K.A., Groff, S., Hatcher, G.A., Gibbs, A.E., Cochran, S.A., and Storlazzi, C.D., 2026, Evaluation of benthic habitat change within the national historic sites of Hawaiʻi’s Kona Coast: U.S. Geological Survey Open-File Report 2026–1061, 28 p., https://doi.org/10.3133/ofr20261061.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-178080","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":503252,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119366.htm","linkFileType":{"id":5,"text":"html"}},{"id":502799,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZPWNS","text":"USGS data release","linkHelpText":"Underwater imagery and classifications of the substrate and coral reef habitat on the Kona coast of the Island of Hawaiʻi, from 2003, 2004, and 2022"},{"id":502798,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1061/images"},{"id":502795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1061/ofr20261061.pdf","text":"Report","size":"8.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1061 PDF"},{"id":502794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1061/coverthb.jpg"},{"id":502796,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261061/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1061 HTML"},{"id":502797,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1061/ofr20261061.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1061 XML"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kona Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.77407070286742,\n 20.114961049183847\n ],\n [\n -156.2156728366818,\n 20.114961049183847\n ],\n [\n -156.2156728366818,\n 19.280147118202123\n ],\n [\n -155.77407070286742,\n 19.280147118202123\n ],\n [\n -155.77407070286742,\n 20.114961049183847\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Despite the extensive natural gas pipeline network in the United States that intersects streams and other sensitive habitats, few case studies use a comparative upstream-to-downstream approach to evaluate potential short- and long-term effects of pipeline stream crossings from pre-construction through post-restoration. In 2017, the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, deployed real-time continuous stream monitoring stations upstream and downstream from six proposed Mountain Valley Pipeline stream crossings in southwestern Virginia. Water temperature and turbidity data collected at the upstream and downstream sites were compared across three periods—before stream crossing construction, during stream crossing construction, and after stream crossing construction—to determine potential influences from the pipeline stream crossing. Additionally, the monitoring network was used to notify regulators of potentially anomalous conditions throughout the entire monitoring period.
The results of this study indicate that pipeline stream crossing did not affect long-term or short-term upstream-to-downstream water temperature conditions or long-term upstream-to-downstream turbidity conditions in any of the six monitored streams. Some short-term anomalously elevated turbidity conditions were observed and attributable to pipeline stream crossing; however, the magnitudes and durations were not sufficient to alter the long-term turbidity regimes of the streams in which they were observed. The application of the monitoring network as a real-time alert system successfully alerted regulators to potentially anomalous conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265011","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Foster, B.M., Maas, C.M., and Flota, A.L., 2026, Assessment of natural gas pipeline construction on stream temperature and turbidity in southwestern Virginia, 2017–25: U.S. Geological Survey Scientific Investigations Report 2026–5011, 40 p., https://doi.org/10.3133/sir20265011. [Supersedes preprint https://doi.org/10.31223/X5XT9G.]","productDescription":"ix, 40 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-182747","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":503250,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119364.htm","linkFileType":{"id":5,"text":"html"}},{"id":502763,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5011/images"},{"id":502762,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5011/sir20265011.XML","description":"SIR 2026-5011 XML"},{"id":502764,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265011/full","text":"HTML Document","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5011 HTML"},{"id":502761,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5011/sir20265011.pdf","text":"Report","size":"12.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5011 PDF"},{"id":502760,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5011/coverthb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.75,\n 37.5\n ],\n [\n -80.75,\n 37\n ],\n [\n -79.75,\n 37\n ],\n [\n -79.75,\n 37.5\n ],\n [\n -80.75,\n 37.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Continental remobilization is a crucial driver of metallogenesis and the formation of ore deposits. Some of the world’s largest mineral deposits of the economically valuable elements tin (Sn), tungsten (W), gold (Au), copper (Cu), lead (Pb), and zinc (Zn) formed during the Mesozoic Era. Additionally, the chemistry and distribution of the elements Sn and W have been investigated in previous studies to understand planetary formation and differentiation processes. These two elements are largely co-located during certain South China Mesozoic metallogenic events but are not co-located during other time periods in the same regions. Here, we investigated the mineral chemistry network similarities and dissimilarities of Sn and W to understand their mineral formation and distribution during the Mesozoic Era and throughout Earth history. Mineral chemistry network community detection analysis and electronegativity associations among mineral constituent elements of Sn minerals and W minerals indicate that the elements have similar chemistry among their oxide minerals. However, Sn forms a much wider range of minerals that also contain S compared to W, which occurs in a limited number of S-containing minerals. The divergent constituent element interactions among S-containing Sn minerals and W minerals reflect the redox sensitivity and importance of oxygen (O) fugacity in Sn mineral formation. Conversely, extensive W mineral deposits are known to form at both high and low O fugacities. The similarities and differences between the mineral chemistry networks of Sn and W reflect the mineral distribution of the two elements in the Sn-W mineralization event from 160 to 139 Ma vs. the Sn–uranium (U) mineralization event from 125 to 98 million years ago (Ma). The mineral chemistry and distribution of Mesozoic Sn and W deposits illustrate the contrasting importance of redox and O fugacity on the mineral formation of different elements, and the dynamic crustal evolution that took place during this period of Earth history.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences16040158","usgsCitation":"Moore, E.K., Morrison, S.M., and Hatter, A., 2026, The mineral chemistry networks of tin and tungsten reflect metallogenic eras of the Mesozoic: Geosciences, v. 16, no. 4, 158, 14 p., https://doi.org/10.3390/geosciences16040158.","productDescription":"158, 14 p.","ipdsId":"IP-184681","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":505055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences16040158","text":"Publisher Index Page"},{"id":504994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Elisha Kelly 0000-0002-9750-7769","orcid":"https://orcid.org/0000-0002-9750-7769","contributorId":334043,"corporation":false,"usgs":true,"family":"Moore","given":"Elisha","email":"","middleInitial":"Kelly","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":962330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Shaunna M.","contributorId":371761,"corporation":false,"usgs":false,"family":"Morrison","given":"Shaunna","middleInitial":"M.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":962331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatter, Amber","contributorId":352523,"corporation":false,"usgs":false,"family":"Hatter","given":"Amber","affiliations":[{"id":84250,"text":"Department of Environmental Science, School of Earth and the Environment, Rowan University, Glassboro, NJ, United States","active":true,"usgs":false}],"preferred":false,"id":962332,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70276348,"text":"70276348 - 2026 - Predicted range shifts of non‐native grasses in response to climate change are influenced by photosynthetic pathway: A case study in the Hawaiian Islands","interactions":[],"lastModifiedDate":"2026-06-01T14:08:47.436304","indexId":"70276348","displayToPublicDate":"2026-04-14T09:03:35","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Predicted range shifts of non‐native grasses in response to climate change are influenced by photosynthetic pathway: A case study in the Hawaiian Islands","docAbstract":"Grasses comprise three main photosynthetic pathway variants (C3-BOP, C3-PACMAD and C4-PACMAD hereafter referred to as C4). We sought to confirm climate niche differences among these photosynthetic pathway variants and assessed whether predicted non-native grass range shift patterns with climate change differ among photosynthetic pathway variants.
Hawaiian Islands.
We used a species distribution modelling (SDM) approach that uses global occurrence records to inform local SDM based on local (Hawaiian Islands) occurrences. We compared climate niches and projected climate-driven range shifts, assuming moderate climate change (RCP 4.5, end of century), among 22 non-native grasses representing C3-BOP, C3-PACMAD and C4 photosynthetic pathway variants.
C4 grasses exhibited the warmest temperature niches on average, but did not differ substantially in rainfall niche versus C3-BOP grasses. C3-PACMAD species averaged high suitability across a broad range of temperatures and rainfall conditions, except extreme aridity. In response to projected climate change, C4 grasses had projected range increases. C3-BOP grasses typically responded with net range decreases, while C3-PACMAD grasses had variable range responses. However, patterns were contingent on elevation: for instance, the projected expansion of C4 grasses was generally limited to elevations below 2000 m, with the largest increases in areas up to ~750 m. Areas of greatest reduction for C3-BOP and C3-PACMAD were projected at 750–1900 m and 100–1100 m elevation, respectively. Above 2000 m, range increases were projected for both C3 grass variants.
Our projections suggest that non-native C4 grasses pose the greatest risk for increasing spread and impacts under RCP 4.5, while certain C3-PACMAD grasses may endanger valuable high-elevation habitats. Photosynthetic pathway may be a useful component of weed risk assessment to evaluate how species may respond to climate change as similar range response patterns may be expected for other non-native grasses in other tropical and subtropical regions.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.70190","usgsCitation":"Daehler, C., Faccenda, K., Aquino Peterson, E., Brock, K., and Fortini, L., 2026, Predicted range shifts of non‐native grasses in response to climate change are influenced by photosynthetic pathway: A case study in the Hawaiian Islands: Diversity and Distributions, v. 32, no. 4, e70190, 16 p., https://doi.org/10.1111/ddi.70190.","productDescription":"e70190, 16 p.","ipdsId":"IP-177967","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":505041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.70190","text":"Publisher Index Page"},{"id":504909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Daehler, Curtis","contributorId":346962,"corporation":false,"usgs":false,"family":"Daehler","given":"Curtis","email":"","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":962183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faccenda, Kevin","contributorId":371622,"corporation":false,"usgs":false,"family":"Faccenda","given":"Kevin","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":962184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aquino Peterson, Elizabeth","contributorId":371623,"corporation":false,"usgs":false,"family":"Aquino Peterson","given":"Elizabeth","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":962185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brock, Kelsey C.","contributorId":354589,"corporation":false,"usgs":false,"family":"Brock","given":"Kelsey C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":962186,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fortini, Lucas B. 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":202074,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas B.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":962187,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275093,"text":"70275093 - 2026 - Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma","interactions":[],"lastModifiedDate":"2026-04-16T13:34:29.776864","indexId":"70275093","displayToPublicDate":"2026-04-14T08:35:56","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17061,"text":"Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma","docAbstract":"Characterizing terrain surface properties is an essential step in assessing the feasibility of landing successfully at a location on a planetary surface. Slopes and terrain ruggedness index (TRI) values derived from high-resolution (2 m pixel−1) digital terrain models provided important constraints in selecting the landing site for the upcoming Payloads and Research Investigations on the Surface of the Moon program as part of the Commercial Lunar Payload Services task order CP-21 mission. The selected landing site needed to balance safety requirements with the ability to achieve the science and exploration goals of the Lunar Vulkan Imaging and Spectroscopy Explorer payload. In this study, we compare several morphometric parameters in the context of the CP-21 landing site on Mons Gruithuisen Gamma, or the Gamma dome, and quantify the information they convey about lunar surface properties to assess their utility for future landing site evaluation. TRI was found to be a useful metric for assessing landing site safety. Metrics that better decouple slope and surface roughness, the vector ruggedness measure and the standard deviation of slope, provided additional information about surface characteristics and textures such as the degree to which roughness is isotropic.
","language":"English","publisher":"American Astronomical Society","doi":"10.3847/PSJ/ae523b","usgsCitation":"Williams, J., Valencia, S., Bennett, K.A., Landis, M., Donaldson Hanna, K.L., Dove, A.T., O'Brien, P., Denevi, B.W., Hagerty, J., Hardgrove, C., Hayne, P.O., LaMee, A., Prettyman, T.H., Shirley, K.A., Siegler, M.A., and Sunshine, J.M., 2026, Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma: Planetary Science Journal, v. 7, no. 4, 78, 9 p., https://doi.org/10.3847/PSJ/ae523b.","productDescription":"78, 9 p.","ipdsId":"IP-177339","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":502977,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/ae523b","text":"Publisher Index Page"},{"id":502820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mons Gruithuisen Gamma, Moon","volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Jean-Pierre","contributorId":291741,"corporation":false,"usgs":false,"family":"Williams","given":"Jean-Pierre","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":959432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valencia, Sarah","contributorId":369959,"corporation":false,"usgs":false,"family":"Valencia","given":"Sarah","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":959433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Kristen A. 0000-0001-8105-7129","orcid":"https://orcid.org/0000-0001-8105-7129","contributorId":237068,"corporation":false,"usgs":true,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":959434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landis, Margaret E.","contributorId":176713,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret E.","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. 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In January 2025, we assembled a group of subject matter experts to perform the following tasks:
This document is a summarization of what occurred at the meeting and provides suggested next steps toward developing the capacity to conduct routine long-term monitoring and assessment of floodplain vegetation as part of the Upper Mississippi River Restoration Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261001","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program and the National Great Rivers Research and Education Center","usgsCitation":"Weiss, S.A., Trumper, M.L., De Jager, N.R., Guyon, L.J., and Van Appledorn, M., 2026, Proceedings of the Floodplain Vegetation Monitoring Workshop for the Long Term Resource Monitoring Element of the Upper Mississippi River Restoration Program, January 7–8, 2025, Moline, Illinois: U.S. Geological Survey Open-File Report 2026–1001, 29 p., https://doi.org/10.3133/ofr20261001.","productDescription":"viii, 29 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179749","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":502679,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261001/full"},{"id":502678,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1001/images/"},{"id":502675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1001/coverthb.jpg"},{"id":502676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1001/ofr20261001.pdf","text":"Report","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1001"},{"id":502677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1001/ofr20261001.XML"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.84995652179344,\n 47.38059349406069\n ],\n [\n -94.51879131555569,\n 45.1779196807436\n ],\n [\n -91.67435276851998,\n 43.23290915291983\n ],\n [\n -91.65945041845046,\n 38.647765678088035\n ],\n [\n -89.78655455017767,\n 38.796516838946786\n ],\n [\n -90.68564412568368,\n 40.42375517193139\n ],\n [\n -89.76470125204189,\n 42.49536202047\n ],\n [\n -92.0520195269138,\n 45.04310183668423\n ],\n [\n -94.84995652179344,\n 47.38059349406069\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
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This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1563","programNote":"Global Seismographic Network Program and Earthquake Hazards Program","usgsCitation":"Ringler, A.T., Wilson, D.C., Anthony, R., Beutel, C.I., Holcomb, A., Hutt, C.R., and Telesha, T., 2026, Albuquerque Seismological Laboratory strategic vision: U.S. Geological Survey Circular 1563, 23 p., https://doi.org/10.3133/cir1563.","productDescription":"viii, 23 p.","onlineOnly":"N","ipdsId":"IP-170747","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":502214,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1563/cir1563.xml"},{"id":502212,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1563/cir1563.pdf","text":"Report","size":"55.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1563"},{"id":502753,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1563/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1563"},{"id":502213,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1563/images"},{"id":502211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1563/coverthb.jpg"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
2P.O. Box 25046, Mail Stop 966
Denver, CO 80225
The Albuquerque National Laboratory is a U.S. Geological Survey field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. These seismic networks provide the data used by the U.S. Geological Survey to meet the needs of earthquake monitoring within the multiagency National Earthquake Hazard Reduction Program. This report highlights the key priorities of the Albuquerque National Laboratory during the next ten years (2026–36) and indicates where the laboratory could focus efforts to improve earthquake monitoring.
","publicationDate":"2026-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":958745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":958746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":958747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beutel, Corey I.","contributorId":363197,"corporation":false,"usgs":false,"family":"Beutel","given":"Corey","middleInitial":"I.","affiliations":[{"id":86649,"text":"Kegman ASL","active":true,"usgs":false}],"preferred":false,"id":958748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holcomb, Andrew","contributorId":363195,"corporation":false,"usgs":false,"family":"Holcomb","given":"Andrew","affiliations":[{"id":86647,"text":"KBR-ASL","active":true,"usgs":false}],"preferred":false,"id":958749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutt, Charles R.","contributorId":336749,"corporation":false,"usgs":false,"family":"Hutt","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":958750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Telesha, Tom 0009-0001-1826-0359","orcid":"https://orcid.org/0009-0001-1826-0359","contributorId":369281,"corporation":false,"usgs":true,"family":"Telesha","given":"Tom","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":958751,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274718,"text":"sir20255093 - 2026 - Opportunities and challenges in using Solid Phase Adsorption Toxin Tracking (SPATT) samplers for monitoring cyanotoxins in freshwater and estuarine environments","interactions":[],"lastModifiedDate":"2026-04-28T17:26:16.677111","indexId":"sir20255093","displayToPublicDate":"2026-04-13T11:44:00","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":"2025-5093","displayTitle":"Opportunities and Challenges in Using Solid Phase Adsorption Toxin Tracking (SPATT) Samplers for Monitoring Cyanotoxins in Freshwater and Estuarine Environments","title":"Opportunities and challenges in using Solid Phase Adsorption Toxin Tracking (SPATT) samplers for monitoring cyanotoxins in freshwater and estuarine environments","docAbstract":"Cyanobacterial toxins (cyanotoxins) represent a substantial threat to drinking water supplies and safe recreational uses of freshwater resources in watersheds worldwide. 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SPATT samplers have been used by six U.S. Geological Survey (USGS) Water Science Centers (New York, California, Oregon, Upper Midwest, New Jersey, and Lower Mississippi-Gulf) to monitor various cyanotoxins in waterbodies such as streams, rivers, lakes, waterfalls, estuaries, and drinking-water intakes. Despite their use across the USGS, there is little guidance available to ensure consistent approaches and data quality across the Bureau. This report summarizes best practices for SPATT deployment and analysis, synthesizes data and describes lessons learned from USGS studies, identifies priority knowledge gaps, and offers considerations for future targeted experiments to help improve data collection and interpretation.
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U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Pronghorn Antilocapra americana occupy only a portion of their historical range and in Oklahoma occur at the eastern edge of the species' contemporary distribution. Monitoring has suggested pronghorn populations in Oklahoma have declined in recent years. We captured and collared 125 adult females across two winters, monitored them for signs of parturition during each subsequent spring, and then captured and radio-collared 70 fawns ≤ 4 days old. We assessed cause-specific mortality, estimated proportional survival, and visualized survival of fawns through 60 days of life with Kaplan–Meier curves. Nearly 87% of fawn mortalities were attributed to predation, with > 77% of predations attributed to coyotes Canis latrans. Our results indicated that fawn survival was lowest during the first 15 days of life, with 33% of fawns surviving to 15 days and 12% surviving to 60 days. We used known-fate models to evaluate the influence of biological factors (i.e. sex, mass, birth timing), environmental factors (i.e. ambient temperature, precipitation, vegetation), and temporal variation on the probability of early life (i.e. the first 15 days) survival. For each adult female with a collared fawn, we used female space-use patterns for 30 days before and 15 days after parturition to collect environmental covariates. Early life probability of survival was lower for larger fawns, those born earlier in the parturition period (i.e. earlier in the year relative to the range of parturition days), and those with higher pre-parturition temperatures; daily probability of survival decreased with time-since-parturition within the first 15 days of life. Our results indicate poor fawn survival, highlight a potential limitation of population growth, and can inform population management by identifying factors influencing early life fawn survival.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/wlb3.01577","usgsCitation":"Hahn, D.P., Lonsinger, R.C., Chitwood, M.C., Moeller, A.K., Turnley, M.T., Dart, M.M., Heffelfinger, L.J., Tanner, E.P., Cherry, M.J., Wang, H.G., and Fairbanks, W.S., 2026, Biological and environmental drivers of early life fawn survival in a declining pronghorn population: Wildlife Biology, v. 2026, no. 3, e01577, 15 p., https://doi.org/10.1002/wlb3.01577.","productDescription":"e01577, 15 p.","ipdsId":"IP-180721","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":505270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The Sedimentary Geochemistry and Paleoenvironments Project (SGP) is a scientific consortium centered around open data and community-driven development of cyberinfrastructure tools and resources for sedimentary geochemistry and Earth history. Here we describe the SGP Phase 2 data release, which focused on incorporating Paleoproterozoic and Mesoproterozoic (2500–1000 million years ago) data and better accommodating carbonate data. This data release was built through the involvement of >200 researchers worldwide in academia, government, and industry, and provides the largest available public data resource for our user community in the academic fields of geochemistry, sedimentology, tectonics, paleontology, Earth history, and paleoclimate, as well as the petroleum and minerals industries. The dataset now encompasses 126,006 samples and 4,132,371 geochemical analyses. In addition to direct entry by SGP Team Members, we have ingested and incorporated datasets from the Geoscience Australia OZCHEM database, the Alberta Geological Survey, and the Deep-Time Marine Sedimentary Element Database (DM-SED) compilation. This paper details sampling in the Phase 2 dataset with respect to age, geography, lithology, and other geological characteristics, documents access via our search website and API, discusses possible issues and/or biases in the dataset that could impact analyses, describes plans for governance and stewardship of data from Indigenous lands, and serves as the citable reference paper for the data release.
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Automated detection expedites processing of audio data for large-scale surveillance and monitoring programs. However, current available methods commonly used for anuran species have not been sufficient to detect Cuban treefrogs. Here, we present results from a two-stage method for automated detection that employs both cross-correlation template matching and secondary supervised learning classifiers. In the first stage, audio data are screened for initial detections using template matching, in which the detections contain both true and false positives. In the second stage, the false positives are screened out using classifier algorithms. We used this method to process 139,985 audio recordings, consisting of 596,046 total minutes, collected at 13 locations in Louisiana and Florida from 2014 to 2022. From the stage 1 template matching, we detected 83,191 Cuban treefrog signals across recordings. The stage 2 machine learning model was able to identify stage 1 false positive detections with a testing accuracy of 98.46% and a testing false positive rate of 1.116%. After pruning false positive detections, a total of 20,271 individual Cuban treefrog detections remained, distributed mainly across 3 sites in an area with known presence. Locations with presumed absence had an easily verifiable number of false positive detections (n = 109 across all other sites). The two-stage methodology utilizing both template matching and machine learning algorithms can be integrated into wildlife surveillance or monitoring programs for species with distinctive, conserved calls as an effective way to achieve sensitive species detection with a low incidence of false positives.
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We developed a quantitative polymerase chain reaction (qPCR) assay to detect the DNA of Franklin’s bumble bee (Bombus franklini) from flower samples and conducted an initial test of the assay using samples collected within and around the historical range of the species. We further analyzed all samples using metabarcoding. Our qPCR assay successfully amplified B. franklini DNA and exhibited no cross-reactivity with nontarget bumble bee DNA during in silico and in vitro testing. We did not detect B. franklini DNA from field-collected flower samples using either qPCR or metabarcoding. However, metabarcoding analysis revealed DNA of at least 16 other bumble bee species. This finding underscores the potential utility of eDNA sampling for surveying bumble bees. Nondetection of B. franklini from field-collected flower samples may be due to the extreme rarity of the species; B. franklini is endangered and has not been observed in the wild since 2006. Our B. franklini assay is among the first bee-specific qPCR assays ever developed and provides proof of concept for additional assays that may improve detection rates of rare and endangered bees.
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Akhil","contributorId":370041,"corporation":false,"usgs":false,"family":"Kholwadwala","given":"Akhil","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":959570,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, Amanda Jean 0000-0002-6579-2569","orcid":"https://orcid.org/0000-0002-6579-2569","contributorId":349758,"corporation":false,"usgs":true,"family":"Boone","given":"Amanda Jean","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":959571,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lor, Yer 0000-0002-5738-2412","orcid":"https://orcid.org/0000-0002-5738-2412","contributorId":210011,"corporation":false,"usgs":true,"family":"Lor","given":"Yer","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959572,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kaminski, Marissa 0000-0003-4127-8685","orcid":"https://orcid.org/0000-0003-4127-8685","contributorId":331025,"corporation":false,"usgs":true,"family":"Kaminski","given":"Marissa","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":959573,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Everett, Jeffrey G.","contributorId":302932,"corporation":false,"usgs":false,"family":"Everett","given":"Jeffrey","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":959574,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70275192,"text":"70275192 - 2026 - Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California","interactions":[],"lastModifiedDate":"2026-04-22T14:41:53.267617","indexId":"70275192","displayToPublicDate":"2026-04-13T07:37:24","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22185,"text":"Environmental Research: Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California","docAbstract":"Uncertainties in terrestrial ecosystem models limit their predictive power. Efforts to reduce projection error have rarely focused on constraining uncertainty in the initial state of the ecosystem, however, despite evidence that matching model initial conditions to real-world observations reduces overall model bias. Here we use an integrated land change and carbon gain-loss model to evaluate the influence of initial condition uncertainty on simulations of California wildland ecosystems during the years 1985–2020. We generated 36 initial conditions scenarios by varying the source data used to initialize state variables and then ran simulations based on each of these scenarios under a constant set of historical conditions. We found that discrepancies in initial forest extent and initial forest age among scenarios generated wide uncertainty ranges in model estimates of terrestrial ecosystem carbon stocks and flux rates at the outset of the simulation period, but differences in initial forest composition had no impact. Over time, forest age became more homogeneous across model scenarios leading to exponential rates of decline in the uncertainty ranges of live biomass and dead wood carbon but little to no impact on uncertainties in litter and soil organic carbon. Uncertainties in individual carbon flux rates were consistent with uncertainties in their source pools. In contrast, model estimates of ecosystem carbon balance demonstrated a shift in system behavior not apparent in trends for individual carbon stocks and fluxes. Specifically, estimates of ecosystem carbon balance converged across scenarios for the first 20 years of the simulation period but then began to diverge at an accelerating rate, possibly due to weakened resilience to the increased frequency and severity of climate-driven disturbances. Our results demonstrate that uncertainty in the initial state of the system can have large and persistent impacts on the predictability of ecosystem carbon dynamics, and that ongoing shifts in external forcing by climate and climate-driven disturbances can exacerbate these impacts.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/2752-664X/ae565f","usgsCitation":"Selmants, P.C., Sleeter, B., and Daniel, C.J., 2026, Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California: Environmental Research: Ecology, v. 5, no. 2, 025001, 20 p., https://doi.org/10.1088/2752-664X/ae565f.","productDescription":"025001, 20 p.","ipdsId":"IP-182837","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":504058,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P137ZDHO","text":"USGS data release","linkHelpText":"lucas-uncertainty, version 1.0.0"},{"id":503442,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/2752-664x/ae565f","text":"Publisher Index 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deposition","docAbstract":"Runoff-generated debris flows are a known response to wildfire, and accurately predicting the volume of these debris flows is important for estimating the magnitude of downstream hazards. Prior data collection efforts have focused on debris-flow volume measurements at catchment outlets, but few studies have considered how erosion and deposition modulate the volume of sediment arriving at catchment outlets. This study takes advantage of a high-resolution dataset to document the factors that control the total debris-flow volume reaching the catchment outlet during a fatal postfire debris flow. Using pre- and post-event airborne lidar, satellite imagery and field mapping, we found that a postfire debris flow in the Black Hollow catchment in northern Colorado eroded 136,000 ± 30,000 m3 and redeposited 27,000 ± 7,500 m3 in the main channel. Most of the in-channel deposition (52% by volume) occurred where a confined channel reach transitioned to an unconfined channel reach downstream, allowing the flow to widen and deposit material. Wood jams played multiple roles in the debris-flow dynamics, both nucleating deposition (25% of the deposit volume was stored behind wood jams) and exacerbating erosion (50% of the total erosion occurred downstream from a wood dam break). The remaining deposition occurred due to spatial changes in channel slope as well as deposition observed at newly formed channel bars. Using these data in this study, we identified topographic and vegetation metrics that can be used (pre-event) to anticipate where deposition may occur in channels prior to a debris flow.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.70287","usgsCitation":"Rengers, F.K., Stoker, J.M., Kostelnik, J., Kean, J.W., Wohl, E.E., Barnhart, K.R., and Guido, L.E., 2026, Channel morphology and large wood control postfire debris-flow erosion and deposition: Earth Surface Processes and Landforms, v. 51, no. 4, e70287, 13 p., https://doi.org/10.1002/esp.70287.","productDescription":"e70287, 13 p.","ipdsId":"IP-170524","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":505058,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.70287","text":"Publisher Index Page"},{"id":504998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Black Hollow","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.8998964,\n 40.6376787\n ],\n [\n -104.8998964,\n 40.6376787\n ],\n [\n -104.8998964,\n 40.6376787\n ],\n [\n -104.8998964,\n 40.6376787\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.89825097286936,\n 40.63651931644344\n ],\n [\n -104.8713368174039,\n 40.63651931644344\n ],\n [\n -104.8713368174039,\n 40.622069349338375\n ],\n [\n -104.89825097286936,\n 40.622069349338375\n ],\n [\n -104.89825097286936,\n 40.63651931644344\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":962354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":962355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":962356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":962392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wohl, Ellen E.","contributorId":313566,"corporation":false,"usgs":false,"family":"Wohl","given":"Ellen","middleInitial":"E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":962358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":962359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guido, Lauren Elizabeth 0000-0003-4449-560X","orcid":"https://orcid.org/0000-0003-4449-560X","contributorId":371791,"corporation":false,"usgs":true,"family":"Guido","given":"Lauren","middleInitial":"Elizabeth","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - 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In the past, CHIRPS version 2 (CHIRPS2) has proven to be valuable for drought monitoring, hydrologic modeling, scientific studies and agricultural decision making. Version 3 (CHIRPS3) improves each of these components. The new version, CHIRPS3 extends to 60°S/N, adopts an improved variance-preserving TIR-to-precipitation estimation method, uses many more stations and station sources than the original CHIRPS2 product, and implements gauge-undercatch correction. In this paper, we evaluate the performance of satellite-only CHIRP3, CHIRP2, IMERG, PERSIANN- CCS, and GPI using high quality interpolated data in twelve regions with dense station coverage. CHIRP3 represents both the observed mean and variance more accurately than CHIRP2. A usage section in Morocco shows that CHIRPS3 better captures the observed rainfall variability when compared to CHIRPS2. This section also demonstrates how station data should be gauge-undercatch-corrected when validating CHIRPS3.
","language":"English","publisher":"Nature","doi":"10.1038/s41597-026-07096-4","usgsCitation":"Funk, C., Peterson, P., Harrison, L., Saldivar, R., Landsfeld, M., Pedreros, D., Shukla, S., Fink, A.H., Davenport, F., Peterson, S.H., Turner, W., Sonnier, A., Budde, M., Tabor, K., Verdin, J., Hauzaree, D., Naim, M., Alaso, D., and Husak, G., 2026, The Climate Hazards Center Infrared Precipitation with Stations, version 3: Scientific Data, v. 13, 78, 24 p., https://doi.org/10.1038/s41597-026-07096-4.","productDescription":"78, 24 p.","ipdsId":"IP-182849","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":504155,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-026-07096-4","text":"Publisher Index 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Florida","interactions":[],"lastModifiedDate":"2026-04-10T19:24:09.199907","indexId":"sir20265141","displayToPublicDate":"2026-04-10T11:27:30","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":"2026-5141","displayTitle":"Phytoplankton Responses to Experimental Nitrogen and Phosphorus Loading in the Eutrophic and Colored Caloosahatchee River, Florida","title":"Phytoplankton responses to experimental nitrogen and phosphorus loading in the eutrophic and colored Caloosahatchee River, Florida","docAbstract":"The Caloosahatchee River, located in southwest Florida, is a eutrophic and colored river that flows from Lake Okeechobee westward into its estuary and the Gulf of America. Cyanobacterial harmful algal blooms (HABs) are a documented problem along this freshwater-to-marine waterway where nutrient enrichment has been identified as a key factor in bloom occurrence but has not been experimentally tested in the river. This study is the first to test the effects of inorganic nutrient loading on phytoplankton assemblages in the Caloosahatchee River and the effects of different nutrient sources on phytoplankton dynamics at different times of the year. Three independent, in situ experiments were conducted to test the effects of daily, incrementally increased ammonium, nitrate, and phosphate loading on phytoplankton at different times of the year (summer, fall, winter). Over the 72-hour enclosure period, phytoplankton abundance metrics (cell concentration, chlorophyll-a, and phycocyanin), dissolved oxygen, and pH increased, and fluorescent dissolved organic matter and turbidity decreased in all treatments and controls. Increased phytoplankton abundance metrics relative to controls were observed after 72 hours of exposure to elevated ammonium and nitrate in summer and only ammonium in winter, suggesting periodic nitrogen limitation; however, no treatment effects on phytoplankton assemblage structure in terms of resemblance and diversity metrics were found. Increases in total cell concentrations were driven by elevated growth rates of already dominant taxa but not sufficiently to form a visible bloom. Cyanobacteria consistently dominated the phytoplankton, particularly Aphanocapsa and Merismopedia, whereas the common HAB-forming Microcystis maintained consistently low abundance. This study provides new information on the ecology of phytoplankton assemblages in the Caloosahatchee River and could be used by water resources managers to evaluate strategies for controlling cyanobacterial HABs in the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265141","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Nova Southeastern University, and Florida Gulf Coast University","programNote":"Environmental Health Program","usgsCitation":"Mazzei, V., Loftin, K.A., Karwacki, E., Lopez, J.V., Krausfeldt, L.E., Rosen, B.H., and Urakawa, H., 2026, Phytoplankton responses to experimental nitrogen and phosphorus loading in the eutrophic and colored Caloosahatchee River, Florida: U.S. Geological Survey Scientific Investigations Report 2026–5141, 32 p., https://doi.org/10.3133/sir20265141.","productDescription":"Report: x, 32 p.; 3 Data Releases","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146459","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":502717,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119361.htm","linkFileType":{"id":5,"text":"html"}},{"id":502324,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5141/sir20265141.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5141 XML"},{"id":502323,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JX9NA1","text":"USGS Data Release","linkHelpText":"Water-quality profiles within the Caloosahatchee River and twelve fiberglass tanks, during experimental nutrient addition treatments, 2021 (ver. 1.1, August 2024)"},{"id":502322,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ELCEC","text":"USGS Data Release","linkHelpText":"Caloosahatchee River nutrient enrichment mesocosms—Phytoplankton taxonomic quantification September 2019, June 2020, September 2020, February 2021"},{"id":502321,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P900BQZR","text":"USGS Data Release","linkHelpText":"Water-quality profiles within the Caloosahatchee River and twelve fiberglass tanks, during experimental nutrient addition treatments, 2020"},{"id":502317,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5141/sir20265141.pdf","size":"10.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5141"},{"id":502309,"rank":1,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5141/images"},{"id":502310,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5141/coverthb4.jpg"},{"id":502325,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265141/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5141 HTML"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80,\n 27.33\n ],\n [\n -82.5,\n 27.33\n ],\n [\n -82.5,\n 26.4\n ],\n [\n -80,\n 26.4\n ],\n [\n -80,\n 27.33\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Us- USGS Publications Warehouse
","tableOfContents":"Harmful algal blooms, particularly cyanobacteria harmful algal blooms (cyanoHABs), have emerged as a substantial global concern because of their detrimental effects on water quality and aquatic ecosystem health. CyanoHABs can produce cyanotoxins, which pose serious health risks to humans and wildlife, such as liver failure and respiratory distress. This is particularly concerning for water bodies that serve as drinking-water sources. Recent trends indicate an increase in the frequency and intensity of cyanoHABs globally. This study focuses on the Raritan Basin Water Supply Complex in New Jersey, where extensive monitoring was conducted from August 2020 to August 2021 to assess the presence of cyanobacteria and associated cyanotoxins. The research utilized a combination of discrete water-quality sampling, continuous monitoring, and solid phase adsorption toxin tracking (SPATT) to capture the dynamics of cyanotoxin occurrence and potential transport. Findings revealed a widespread presence of cyanobacteria and potential for cyanotoxin production, although actual cyanotoxin concentrations remained below drinking water and recreational thresholds. The study, conducted by the U.S. Geological Survey (USGS) in collaboration with the New Jersey Water Supply Authority (NJWSA) and the New Jersey Department of Environmental Protection (NJDEP), highlighted the limitations of traditional sampling methods and emphasized that continuous monitoring can support better understanding of how cyanoHAB conditions change over time and in different places. Genetic testing included quantitative polymerase chain reaction (qPCR) analyses, which demonstrated higher sensitivity, or increased findings of cyanobacteria compared to microscopy, indicating the potential for use in early warning systems. This research underscores that integrating various detection methods and hydrological data can enhance understanding of cyanotoxin dynamics in river systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265128","collaboration":"Prepared in cooperation with the New Jersey Water Supply Authority and the New Jersey Department of Environmental Protection","programNote":"Water Availability and Use Science Program","usgsCitation":"Gorney, R.M., Heckathorn, H.A., Clonan, K.R., Reilly, P.A., Cahalane, K., and Bjorklund, B.W., 2026, Occurrence of cyanobacteria and associated cyanotoxins in the Raritan Basin Water Supply Complex, New Jersey, August 2020 to August 2021: U.S. Geological Survey Scientific Investigations Report 2026–5128, 30 p., https://doi.org/10.3133/sir20265128.","productDescription":"Report, ix, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":502716,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119360.htm","linkFileType":{"id":5,"text":"html"}},{"id":502326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5128/coverthb3.jpg"},{"id":502327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5128/sir20265128.pdf","text":"Report","size":"6.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5128 PDF"},{"id":502329,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5128/sir20265128.XML","description":"SIR 2026-5128 XML"},{"id":502330,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5128/images"},{"id":502328,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265128/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5128 HTML"},{"id":502331,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1S5DQ6A","text":"USGS Data Release","linkHelpText":"Cyanobacteria, other water-quality, and discharge data collected from the Raritan River Basin, New Jersey, August 2020 through August 2021"}],"country":"United States","state":"New Jersey","otherGeospatial":"Raritan Basin Water Supply Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.0833,\n 40.9167\n ],\n [\n -75.0833,\n 40.0167\n ],\n [\n -74.1667,\n 40.0167\n ],\n [\n -74.1667,\n 40.9167\n ],\n [\n -75.0833,\n 40.9167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, New Jersey 08648
Wildlife health is integral to functioning, complex ecosystems [1], directly and indirectly influencing the health of people, animals, plants, and the environment [2–4]. Healthy wildlife populations are essential for ecosystem services and are at the heart of the One Health approach [3,4], which aims to sustainably balance and optimize the health of people, animals, and ecosystems through multisectoral and transdisciplinary collaboration [5].
Despite its importance, wildlife health initiatives often operate in silos, limiting capacity to address transboundary threats such as emerging diseases, pollution, and environmental changes. Anthropogenic changes, including habitat loss, degradation, fragmentation, and unsustainable harvesting, exacerbate wildlife health challenges [6–9]. These pressures disrupt species biology and alter host-pathogen dynamics [10–12], underscoring the importance of coordinated collective action in addressing harmful effects on the health of wild animals. While local conservation efforts are vital, long-term success in safeguarding biodiversity requires a unified, global network. For instance, without harmonized surveillance and response systems, individual institutions cannot effectively track pathogens across borders or share diagnostic capabilities.
The World Organisation for Animal Health (WOAH) Collaborating Centre Network for Wildlife Health—WOAH-WildNet—was established to bridge these gaps. By fostering global collaboration, sharing resources, and enabling data exchange, WOAH-WildNet provides a transformative, systems-based approach to wildlife health, managing risks, and enhancing ecosystem resilience. Central to this mission is breaking down silos to promote intersectoral coordinated responses to complex wildlife health challenges.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pstr.0000228","usgsCitation":"Hayman, D.T., Unwin, S., Bateman, K., Behravesh, C.B., Berg, C., Bergfeld, J., Casalone, C., Cayol, C., Davis, E., Ekesi, S., Esterhuizen, J., Getahun, M., Giorda, F., Hamilton, K., Joly, D.O., Kuhn, C., Manuguerra, J., Masig, D., Michel, A., Mulatti, P., Mulumba, M., Njui, A., Paley, R., Fernandez, A., Knauf, S., Tchouassi, D.P., Wang, Y., Vachiery, N., Villinger, J., Wong, F.Y., Zhong, G., and Shetty, B., 2026, The WOAH global wildlife health collaborating centre network (WOAH-WildNet): A coordinated and transformative approach to global wildlife health challenges: PLOS Sustainability and Transformation, v. 5, no. 4, e0000228, 6 p., https://doi.org/10.1371/journal.pstr.0000228.","productDescription":"e0000228, 6 p.","ipdsId":"IP-188041","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":503428,"rank":0,"type":{"id":40,"text":"Open 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Agricultural Sciences, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":959683,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergfeld, Jemma","contributorId":370110,"corporation":false,"usgs":false,"family":"Bergfeld","given":"Jemma","affiliations":[{"id":87958,"text":"Commonwealth Scientific and Industrial Research Organisation, Australia","active":true,"usgs":false}],"preferred":false,"id":959684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Casalone, Cristina","contributorId":370111,"corporation":false,"usgs":false,"family":"Casalone","given":"Cristina","affiliations":[{"id":87959,"text":"Istituto Zooprofilattico Sperimentale del Piemonte, Italy","active":true,"usgs":false}],"preferred":false,"id":959685,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cayol, Claire","contributorId":370137,"corporation":false,"usgs":false,"family":"Cayol","given":"Claire","affiliations":[{"id":87971,"text":"World Organisation for 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Dharmaveer","contributorId":370134,"corporation":false,"usgs":false,"family":"Shetty","given":"B. Dharmaveer","affiliations":[{"id":87971,"text":"World Organisation for Animal Health, Paris, France","active":true,"usgs":false}],"preferred":false,"id":959709,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}} ,{"id":70274762,"text":"sir20265138 - 2026 - Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023","interactions":[],"lastModifiedDate":"2026-04-16T17:22:01.249485","indexId":"sir20265138","displayToPublicDate":"2026-04-09T15:06:02","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":"2026-5138","displayTitle":"Arsenic and Isotope Concentrations in the Lower Platte River Valley of Eastern Nebraska, early 1970s to 2023.","title":"Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023","docAbstract":"The City of Lincoln, Nebraska, has been monitoring concentrations of arsenic in their source water and evaluating their options for treatment and removal since at least 2002. In 2022, the City of Lincoln, Nebr., with funding assistance from the Nebraska Water Sustainability Fund, began cooperating with the U.S. Geological Survey to examine arsenic concentrations in surface water and groundwater in the lower Platte River valley and the area around City of Lincoln Water System (LWS) well field. Arsenic data collected from the Platte River since 1974 were examined using the “weighted regression on time, discharge, and season” model, which compared the streamflow (also referred to as “discharge”), time of year, and season to estimate concentrations of arsenic. Annual mean arsenic concentrations modeled for more than 49 years at the Platte River at Louisville, Nebr., U.S. Geological Survey streamgage (station 06805500), indicated a significant increasing trend. Arsenic concentrations in the Platte River were seasonal, with the highest concentrations being observed during mid- to late summer. When seasonal patterns and streamflow were combined with arsenic concentrations in the Platte River during low streamflow conditions, groundwater contributions, which can have higher arsenic concentrations, make up a larger portion of the streamflow. Arsenic samples were collected from upstream rivers in 2022 and 2023 and were paired to analyze the arsenic contributions at the U.S. Geological Survey streamgage on the Platte River near Ashland, Nebr. (station 06801000), near the City of Lincoln well field. The arsenic concentrations from the streamgage on the Platte River near Ashland, Nebr., location, were higher than the U.S. Geological Survey streamgage on the Elkhorn River at Waterloo, Nebr. (station 06800500), and significantly lower than at the U.S. Geological Survey streamgage on the Platte River near Leshara, Nebr.(station 06796500), indicating that the Platte River usually contributes a higher concentration of arsenic than does the Elkhorn River as they join near Ashland, Nebr. During 1991–2023, six groundwater monitoring wells were analyzed to identify trends in arsenic concentrations. Two of the six wells had a positive trend during the 33-year period. One monitoring well did not reveal a long-term trend during this period but showed a trend during 2019–23, correlating to a period when the island in the middle of the Platte River was connected to the east bank of the river when manganese reducing conditions were present and groundwater levels were declining in the well. Across all wells the oxidation and reduction (redox) condition during the time of sampling was assessed. Mixed anoxic and (or) oxic redox condition was the most common redox process and the highest sampled arsenic concentrations in monitoring wells were observed in anoxic conditions driven by manganese reduction. Groundwater arsenic concentrations had seasonal variation around the City of Lincoln well field, with higher arsenic concentrations tending to be further south in comparison to samples collected further north. Isotope samples were collected and analyzed in surface water and groundwater around the LWS well field. The samples indicate that the proportion of surface water present in the LWS production wells can be higher in the spring and lower in the summer. With higher arsenic concentrations observed in the stream water during the summer period, the LWS source water can be affected by these elevated arsenic concentrations even though the proportion of surface water is lower.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265138","collaboration":"Prepared in cooperation with City of Lincoln, Nebraska","usgsCitation":"Moser, M.T., Cherry, M.L., and Hall, B.M., 2026, Arsenic and isotope concentrations in the lower Platte River valley of eastern Nebraska, early 1970s to 2023: U.S. Geological Survey Scientific Investigations Report 2026–5138, 23 p., https://doi.org/10.3133/sir20265138.","productDescription":"Report: vii; 23 p.; Data Release; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161400","costCenters":[{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":502306,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release"},{"id":502305,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5138/images"},{"id":502304,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265138/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5138 HTML"},{"id":502303,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5138/sir20265138.pdf","text":"Report","size":"5.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5138"},{"id":502302,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5138/coverthb.jpg"},{"id":502715,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119359.htm","linkFileType":{"id":5,"text":"html"}},{"id":502308,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5138/sir20265138.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5138 XML"},{"id":502307,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/usgs-national-water-quality-network","text":"USGS National Water Quality Network"}],"country":"United States","state":"Nebraska","otherGeospatial":"lower Platte River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.95,\n 41.667\n ],\n [\n -97,\n 41.667\n ],\n [\n -97,\n 40.667\n ],\n [\n -95.95,\n 40.667\n ],\n [\n -95.95,\n 41.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Plains Water Science Center
U.S. Geological Survey
1217 Biltmore Drive Lawrence, KS 66049
5231 South 19th Street Lincoln, NE 68512
The 2024 annual report of the U.S. Geological Survey Woods Hole Coastal and Marine Science Center highlights accomplishments of 2024, includes a list of 2024 publications, and summarizes the work of the center, as well as the work of each of its science groups. This product allows readers to gain a general understanding of the focus areas of the center’s scientific research and learn more about specific projects and progress made throughout 2024, all while enjoying photographs taken in various environments and laboratories, and applicable maps and figures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1564","usgsCitation":"Ernst, S., 2026, Woods Hole Coastal and Marine Science Center—2024 annual report: U.S. Geological Survey Circular 1564, 39 p., https://doi.org/10.3133/cir1564.","productDescription":"iv, 39 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-176220","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501550,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1564/images/"},{"id":501549,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1564/cir1564.XML","linkFileType":{"id":8,"text":"xml"},"description":"CIR 1564 XML"},{"id":501547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1564/cir1564.pdf","size":"39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1564 PDF"},{"id":501548,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1564/full","linkFileType":{"id":5,"text":"html"},"description":"CIR 1564 HTML"},{"id":501546,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1564/coverthb2.jpg"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
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Quissett Campus
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Lake St. Clair Metropark Beach in Michigan has a history of closures because of elevated Escherichia coli (E. coli) concentrations in its recreational waters. To reduce closures, restoration projects were implemented in 2021 to deter waterfowl from congregating on the beach. In this study, the U.S. Geological Survey, in cooperation with the Michigan Department of the Environment, Great Lakes, and Energy and in collaboration with Huron-Clinton Metroparks and the Macomb County Health Department, monitored E. coli from 2022–23 in surface water, shallow groundwater, and sediment at Lake St. Clair Metropark Beach. Results were compared to data from a prerestoration (2018–19) study. A significant decrease in daily geometric mean E. coli concentrations in surface water was observed postrestoration, but the number of high concentration events increased. This resulted in more frequent beach closures postrestoration. Surface-sediment E. coli concentrations significantly decreased after restoration, and waterfowl populations generally decreased from 2021 to 2023, suggesting that the deterrence measures could be influencing E. coli concentrations in surface sediments and surface water. Groundwater E. coli concentrations were orders of magnitude higher than those in surface water and revealed no change correlated with restoration. Seepage measurements indicated that groundwater occasionally discharges into surface water, potentially providing a transport mechanism for E. coli to reach the lake. Continued monitoring and consideration of environmental factors could help to better understand the beach system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265134","issn":"2328-0328","collaboration":"Prepared in cooperation with Michigan Department of Environment, Great Lakes, and Energy","usgsCitation":"Lockmiller, H.A., Byers, V.C., and Fogarty, L.R., 2026, Escherichia coli monitoring and assessment in 2022 and 2023 after beach restoration at Lake St. Clair Metropark Beach, Macomb County, Michigan: U.S. Geological Survey Scientific Investigations Report 2026–5134, 24 p., https://doi.org/10.3133/sir20265134.","productDescription":"Report: viii, 24 p.; Data Release; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-165989","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502714,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119358.htm","linkFileType":{"id":5,"text":"html"}},{"id":502180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5134/coverthb.jpg"},{"id":502187,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":502186,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GGCXS","text":"USGS data release","linkHelpText":"Water flux and avian species data at Lake St. Clair Metropark in Macomb County, Michigan, collected during recreational seasons of 2021, 2022, and 2023"},{"id":502184,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5134/sir20265134.XML","description":"SIR 2026-5134 XML"},{"id":502183,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265134/full","text":"HTML","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5134 HTML"},{"id":502182,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5134/sir20265134.pdf","text":"Report","size":"4.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5134"},{"id":502181,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5134/images"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake St. Clair Metropark Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.7975,\n 42.57167\n ],\n [\n -82.7975,\n 42.570278\n ],\n [\n -82.794722,\n 42.570278\n ],\n [\n -82.794722,\n 42.57167\n ],\n [\n -82.7975,\n 42.57167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been detected at combined concentrations above 2,000 nanograms per liter (ng/L) at groundwater seep locations near the Coakley Landfill Superfund site, in North Hampton, New Hampshire. The landfill was active from 1972 to 1985. An impermeable cap was placed on the landfill in 1998. The adjacent area to the Coakley Landfill has many water supply wells, and transport of PFAS compounds to the wells is a concern. Fracture anisotropy in the underlying bedrock aquifer complicates the understanding of PFAS transport because groundwater preferentially travels along fractures that may not align with the prevailing groundwater flow direction. In 2018, the U.S Environmental Protection Agency and the U.S. Geological Survey began an investigation of the groundwater flow from the Coakley Landfill site. This report describes the modification of a numerical groundwater-flow model for the local area around the Coakley Landfill and summarizes findings of the investigation. In addition, this report includes a brief description of PFOA and PFOS occurrence, a discussion of model construction, evaluation of model performance through calibration, and discussion of simulation results for two periods (before and after capping). Limitations are also discussed. Results show that simulated groundwater flow moves from the Coakley Landfill to the west and north. Advective transport modeling using particle tracking shows that groundwater from the landfill discharges primarily to streams to the west and north, and a small amount is transported to distal wells. Dilution of contaminants through advection and dispersion likely plays a role in whether PFAS compounds from the landfill will be detected above laboratory reporting levels at distal wells.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X53761","usgsCitation":"Harte, P., and Collins, A.L., 2026, Simulation of groundwater flow to evaluate hydrogeologic controls on a PFAS plume, Coakley Landfill Superfund Site, Rockingham County, New Hampshire: EarthArXiv, preprint posted April 09, 2026, https://doi.org/10.31223/X53761.","productDescription":"72 p.","ipdsId":"IP-188248","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":502680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2026-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Harte, Phil 0000-0002-7718-1204","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":369789,"corporation":false,"usgs":false,"family":"Harte","given":"Phil","affiliations":[{"id":63928,"text":"Former USGS (ret.)","active":true,"usgs":false}],"preferred":false,"id":959179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Andrew L. 0000-0003-4751-7333","orcid":"https://orcid.org/0000-0003-4751-7333","contributorId":332093,"corporation":false,"usgs":true,"family":"Collins","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959180,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70275062,"text":"70275062 - 2026 - Incorporating data sets with multiple sources of uncertainty in integrated species distribution models","interactions":[],"lastModifiedDate":"2026-04-14T16:29:45.038418","indexId":"70275062","displayToPublicDate":"2026-04-09T09:24:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating data sets with multiple sources of uncertainty in integrated species distribution models","docAbstract":"Data integration methods aim to improve species distribution estimates by incorporating multiple sources of uncertainty across datasets. Two major sources of uncertainty are: (1) variation in sampling effort across space and within datasets, and (2) variation in reliability associated with data collection protocols or timing among datasets. Our goal was to evaluate how different approaches to address these uncertainties influence predictive performance of integrated models. We modeled distributions of four bird species using three datasets that differed in sampling design. We examined three strategies to reduce uncertainty: (1) filtering data, (2) incorporating functions that account for uncertainty in observation models, and (3) varying how datasets are integrated into a single estimate. We first examine methods to account for variable effort in observations, focusing on both spatial differences in sampling intensity and effort given to a single observation record. We then examine approaches to account for data sets with differing reliability. Sampling effort was best addressed through conservative filtering, including spatial thinning and excluding observations with highly variable effort. Next, we considered how to account for potential false positive detections—due to either misidentification or changes in distributions. We found that treating less reliable data as a covariate, an approach previously suggested for data integration that can greatly speed up model fitting, performed well. Other effective approaches included directly modeling false positive rates and complete exclusion of less reliable data sets. Our results provide insights into best practices in integrated modeling for handling uncertainty in integrated models. We demonstrate the flexible options available when using integrated models to address uncertainty.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.73185","usgsCitation":"Lunt, F., Scher, C.L., Mummah, R.O., and Miller, D.A., 2026, Incorporating data sets with multiple sources of uncertainty in integrated species distribution models: Ecology and Evolution, v. 16, no. 4, e73185, 11 p., https://doi.org/10.1002/ece3.73185.","productDescription":"e73185, 11 p.","ipdsId":"IP-180463","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":503008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.73185","text":"Publisher Index Page"},{"id":502788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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