Species diversity is the foundation of many ecological disciplines. This metric is often approximated using species richness and evenness, even though actual richness likely exceeds observations due to imperfect sampling methods. Estimating the “true” species richness, which includes identifying the number of missing species, has intrigued ecologists for decades. We adopted a parametric model that appeared in Fisher et al. (1943), which models the numbers of individuals from different species as random samples from a negative binomial distribution, and developed a Bayesian computational approach to directly estimate the distribution model parameters. The model parameters represent species abundance and evenness, and can be used to derive species richness. We evaluated our parametric approach using (1) a simulation study and (2) three historical data sets. Furthermore, we illustrated the hierarchical modeling approach to combine data from multiple parallel studies using a biannual fishery survey data set. Our parametric model formulation is computationally efficient, and the hierarchical structure facilitates embedding diversity estimation into broader application, such as assessing spatial and temporal trends in species diversity associated with environmental stressors. Additionally, because the two parameters of the negative binomial distribution model represent species abundance and evenness of a community, this parametric approach facilitates a deeper understanding of the ecological systems under study. The negative binomial distribution model works with a wide range of species frequency distribution types. As a result, our emphasis on a parametric model can help us characterize the structure of an ecosystem and provide a greater depth of ecologically meaningful information.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2026.103773","usgsCitation":"Qian, S.S., Dufour, M.R., Jaffe, S., Hilling, C.D., and Hintz, W.D., 2026, A Bayesian hierarchical modeling approach for species diversity in ecology: Ecological Informatics, v. 95, 103773, 9 p., https://doi.org/10.1016/j.ecoinf.2026.103773.","productDescription":"103773, 9 p.","ipdsId":"IP-170631","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":503760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2026.103773","text":"Publisher Index Page"},{"id":503510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","noUsgsAuthors":false,"publicationDate":"2026-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S.","contributorId":370365,"corporation":false,"usgs":false,"family":"Qian","given":"Song","middleInitial":"S.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":960214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":960215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Sabrina","contributorId":333990,"corporation":false,"usgs":false,"family":"Jaffe","given":"Sabrina","email":"","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":960216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":960217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hintz, William D.","contributorId":370367,"corporation":false,"usgs":false,"family":"Hintz","given":"William","middleInitial":"D.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":960218,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275730,"text":"70275730 - 2026 - A practical decision tool for marine bird mortality assessments","interactions":[{"subject":{"id":70263997,"text":"70263997 - 2025 - A practical decision tool for marine bird mortality assessments","indexId":"70263997","publicationYear":"2025","noYear":false,"title":"A practical decision tool for marine bird mortality assessments"},"predicate":"SUPERSEDED_BY","object":{"id":70275730,"text":"70275730 - 2026 - A practical decision tool for marine bird mortality assessments","indexId":"70275730","publicationYear":"2026","noYear":false,"title":"A practical decision tool for marine bird mortality assessments"},"id":1}],"lastModifiedDate":"2026-05-14T14:01:51.445707","indexId":"70275730","displayToPublicDate":"2026-04-17T08:58:00","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"A practical decision tool for marine bird mortality assessments","docAbstract":"Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ornithapp/duag044","usgsCitation":"Harvey, J., Ramey, A.M., Avery-Gomm, S., Robertson, G.J., Romano, M.D., Mullinax, J.M., Boldenow, M.L., Atkinson, P.W., and Prosser, D., 2026, A practical decision tool for marine bird mortality assessments: Ornithological Applications, https://doi.org/10.1093/ornithapp/duag044.","ipdsId":"IP-180115","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":504377,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duag044","text":"Publisher Index Page"},{"id":504327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Johanna","contributorId":304699,"corporation":false,"usgs":false,"family":"Harvey","given":"Johanna","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":961559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":961560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avery-Gomm, Stephanie","contributorId":213093,"corporation":false,"usgs":false,"family":"Avery-Gomm","given":"Stephanie","email":"","affiliations":[{"id":12552,"text":"University of Queensland","active":true,"usgs":false}],"preferred":false,"id":961561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, Gregory J.","contributorId":371324,"corporation":false,"usgs":false,"family":"Robertson","given":"Gregory","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":961562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romano, Marc D.","contributorId":371325,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","middleInitial":"D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":961563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullinax, Jennifer M","contributorId":371326,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","middleInitial":"M","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":961564,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boldenow, Megan L","contributorId":371327,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","middleInitial":"L","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":961565,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Atkinson, Philip W.","contributorId":371328,"corporation":false,"usgs":false,"family":"Atkinson","given":"Philip","middleInitial":"W.","affiliations":[{"id":38864,"text":"British Trust for Ornithology","active":true,"usgs":false}],"preferred":false,"id":961566,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":961567,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70275246,"text":"70275246 - 2026 - Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2026-04-24T14:10:27.768067","indexId":"70275246","displayToPublicDate":"2026-04-17T08:57:51","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11111,"text":"PLOS Water","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California","docAbstract":"This study seeks to determine the effects of oil field produced water disposal operations and well mechanical integrity issues on groundwater quality in oil fields in the southwest San Joaquin Valley, California. Whereas previous studies used groundwater wells to study shallow aquifers outside the oil fields, this study demonstrates that future approaches may use oil well geophysical logs to map groundwater head gradients, create salinity profiles and document changes in salinity over time in oil field areas with sparse groundwater well data and at depths greater than 330 m. We also incorporate an analysis of well histories to determine potential effects of compromised wellbore seals on changes in aquifer quality that cannot be explained by water disposal practices. Water quality in the aquifers is naturally brackish across most of the area, with better quality groundwater occurring in the eastern part. Geophysical logs are used to determine salinity variations within aquifers including the depth at which TDS exceeds 10,000 mg/L. This depth ranges from 366 m in the northwest to approximately 1,500 m in the southeast. Oil well porosity logs are used to determine water table elevations. These logs indicate the water table slopes south-southeast, showing the predominant groundwater flow direction is from oil field disposal areas toward better quality groundwater east of the oil fields. Geophysical logs show formation resistivity near some disposal facilities has decreased over time, indicating the salinity of the aquifer has increased due to disposal of saline produced water in injection wells and ponds. Oil well history analysis suggests that increased salinity over time in water-saturated sand intervals >1.5 km from disposal facilities may be caused by mechanical failures and/or incomplete borehole seals in poorly constructed or abandoned wellbores prevalent throughout the study area—particularly wells drilled prior to 1930.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000450","usgsCitation":"Gillespie, J.M., Gannon, R., Ball, L.B., Warden, J.G., Everett, R.R., and Stephens, M.J., 2026, Hydrogeology, groundwater salinity distributions, and assessment of the effect of oil-production activities on groundwater in the Midway Valley area, western Kern County, San Joaquin Valley, California: PLOS Water, v. 5, no. 4, e0000450, 26 p., https://doi.org/10.1371/journal.pwat.0000450.","productDescription":"e0000450, 26 p.","ipdsId":"IP-180280","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":503759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000450","text":"Publisher Index Page"},{"id":503509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Midway Valley area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 35.5\n ],\n [\n -119,\n 35.5\n ],\n [\n -119,\n 34.75\n ],\n [\n -120,\n 34.75\n ],\n [\n -120,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"4","noUsgsAuthors":false,"publicationDate":"2026-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":219675,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice","email":"","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannon, Riley 0000-0002-1239-1083","orcid":"https://orcid.org/0000-0002-1239-1083","contributorId":205967,"corporation":false,"usgs":true,"family":"Gannon","given":"Riley","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":960229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warden, John G. 0000-0003-1384-458X","orcid":"https://orcid.org/0000-0003-1384-458X","contributorId":215846,"corporation":false,"usgs":true,"family":"Warden","given":"John","email":"","middleInitial":"G.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Everett, Rhett R. 0000-0001-7983-6270","orcid":"https://orcid.org/0000-0001-7983-6270","contributorId":208212,"corporation":false,"usgs":true,"family":"Everett","given":"Rhett","email":"","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":960232,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70275178,"text":"70275178 - 2026 - Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA","interactions":[],"lastModifiedDate":"2026-04-21T15:01:47.79332","indexId":"70275178","displayToPublicDate":"2026-04-17T07:49:27","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA","docAbstract":"The iconic Old Faithful Geyser in Yellowstone National Park, USA, has attracted a significant amount of research because of the relative regularity and impressive size of its eruptions. Numerous studies have included observations, measurements, and analyses that informed models of geyser eruptions. However, fundamental quantities, including the associated mass and heat discharged, remain poorly constrained. In April 2025 we measured the volume of water from 45 Old Faithful Geyser eruptions using a portable flume in an outflow channel and specific conductance measurements in the Firehole River. We used high-speed video to perform velocimetry, measured changes in water chemistry to calculate the volume of water evaporated along the outflow channels, and used thermodynamic calculations to estimate the volume of water erupted as steam and to quantify the geyser's heat output. The calculated average volume of water discharged by Old Faithful Geyser in each eruption is 27.9 ± 9.4 m3, with no relation between eruption volume and the length of the preceding eruption interval. Video analysis of the eruption's liquid-dominated phase yields similar volumes of 21–30 m3. The calculated heat flow from the geyser is 2.2–2.4 MW and the average annual discharge of chloride, fluoride, and arsenic are 63 tons, 3.9 tons, and 241 kg, respectively. Average annual silica deposition rate on the geyser cone and along the outflow channels is 7 tons. This study provides a methodology for future studies at geysers worldwide and a baseline for monitoring future activity changes at Old Faithful.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2026.108624","usgsCitation":"Hurwitz, S., McCleskey, R., Rudolph, M.L., Peek, S., Roth, D.A., Schott-Atkins, M., Manga, M., Folz Donahue, K.F., Reed, M.H., and Hungerford, J.D., 2026, Water volumes, heat flow, and solute discharge from Old Faithful Geyser eruptions, Yellowstone National Park, USA: Journal of Volcanology and Geothermal Research, v. 474, 108624, 13 p., https://doi.org/10.1016/j.jvolgeores.2026.108624.","productDescription":"108624, 13 p.","ipdsId":"IP-185069","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":503750,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2026.108624","text":"Publisher Index Page"},{"id":503268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Old Faithful Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.05006455962126,\n 45.0129140640631\n ],\n [\n -111.05006455962126,\n 43.754298426623194\n ],\n [\n -109.3525348558879,\n 43.754298426623194\n ],\n [\n -109.3525348558879,\n 45.0129140640631\n ],\n [\n -111.05006455962126,\n 45.0129140640631\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"474","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":216321,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":959885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":959886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudolph, Maxwell L.","contributorId":370157,"corporation":false,"usgs":false,"family":"Rudolph","given":"Maxwell","middleInitial":"L.","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":959887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":959888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, David A. 0000-0002-7515-3533 daroth@usgs.gov","orcid":"https://orcid.org/0000-0002-7515-3533","contributorId":202097,"corporation":false,"usgs":true,"family":"Roth","given":"David","email":"daroth@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":959889,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schott-Atkins, Melissa","contributorId":370161,"corporation":false,"usgs":false,"family":"Schott-Atkins","given":"Melissa","affiliations":[{"id":87977,"text":"U. Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":959890,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Manga, Michael","contributorId":370162,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":33781,"text":"U.C. Berkeley","active":true,"usgs":false}],"preferred":false,"id":959891,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Folz Donahue, Kiernan F.","contributorId":370163,"corporation":false,"usgs":false,"family":"Folz Donahue","given":"Kiernan","middleInitial":"F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":959892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed, Mara H.","contributorId":370164,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","middleInitial":"H.","affiliations":[{"id":33781,"text":"U.C. 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Continued research can be used to show the potential for previously undiscovered critical mineral resources in southwestern Montana and in other parts of the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20263064","collaboration":"Prepared in collaboration with Montana Technical University and Montana Bureau of Geology and Mines","programNote":"Mineral Resources Program and National Cooperative Geologic Mapping Program","usgsCitation":"Gaynor, S.P., Anderson, E.D., Eastman, K.A., Lund, K., Gammons, C., Lowers, H., and Thompson, J., 2026, Critical minerals in zinc ore—An update on Earth Mapping Resources Initiative Research in the Boulder Batholith region (ver. 1.2, April 2026), Montana: U.S. Geological Survey Fact Sheet 2026–3064, 6 p., https://doi.org/10.3133/fs20263064.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-179404","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":503181,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119302.htm","linkFileType":{"id":5,"text":"html"}},{"id":503104,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20263064/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2026-3064"},{"id":500811,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2026/3064/versionHist.txt","size":"8.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2026-3064 version history"},{"id":500765,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2026/3064/fs20263064.xml"},{"id":500764,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2026/3064/images"},{"id":500740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2026/3064/fs20263064.pdf","text":"Report","size":"8.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2026-3064"},{"id":500739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2026/3064/coverthb2.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Boulder Batholith region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.667,\n 46.667\n ],\n [\n -113.4167,\n 46.667\n ],\n [\n -113.4167,\n 45.25\n ],\n [\n -111.667,\n 45.25\n ],\n [\n -111.667,\n 46.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 4, 2026; Version 1.1: March 5, 2026; Version 1.2: April 16, 2026","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
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Computation of detailed groundwater flow budgets for subdivisions of the Virginia Coastal Plain aquifer system has enabled quantification and more thorough understanding of groundwater flow within this important water resource. A zone budget analysis based on previously published groundwater models of the Virginia Coastal Plain and Virginia Eastern Shore indicates that groundwater conditions vary substantially throughout the Coastal Plain aquifer system because of local variations in hydrogeology and historical and ongoing variations in groundwater use and management. Decades of substantial groundwater withdrawal from the Coastal Plain aquifer system have altered groundwater flow from predevelopment conditions. Rates of sustainable withdrawal are limited because the downward groundwater flow rate into confined aquifers is a relatively small part of the total groundwater budget for the aquifer system compared to the rate of recharge at the land surface.
Analyses of groundwater budgets from the Virginia Coastal Plain model indicate that groundwater flow is generally outward from the surficial aquifer to rivers and coastal waterbodies and downward through a series of underlying aquifers and confining units to the Potomac aquifer, which is the deepest aquifer and the source of most groundwater withdrawals. Downward flow into the Potomac aquifer is estimated to be only 7 percent of total net precipitation-derived net recharge at the land surface but makes up about 66 percent of inflow to the aquifer in Virginia, with much of the remaining inflow occurring laterally from outside of defined groundwater budget regions in Virginia. For several decades prior to 2010, high rates of withdrawal from the Potomac aquifer resulted in substantial decline in groundwater storage in the aquifer and in most overlying aquifers and confining units. From 2010 to 2023, rates of withdrawal substantially lower than the historical maximum resulted in small net increases in groundwater storage in the confined aquifer system for most regions of the Virginia Coastal Plain. Nevertheless, for the same period, groundwater storage for the entire model domain continues to incrementally decline, indicating that storage recovery in Virginia is offset by a continued decrease in storage in areas beneath the Chesapeake Bay or adjacent areas of Maryland and North Carolina. Withdrawals from the Potomac aquifer have induced substantial downward flow which is a large part of groundwater budgets for confined aquifers such as the Potomac. For the most recent simulated conditions (2023) downward groundwater flow continues, but because vertical flow rates are a function of the difference between water pressure in the upper surficial systems and lower confined units, rates of downward flow are lower than those in earlier decades as the confined water levels partially recover from larger groundwater withdrawals in the past. Geographically, groundwater flow is generally inward from perimeter regions of the Virginia Coastal Plain toward central regions with the largest withdrawal rates. Groundwater inflow from coastal regions could be contributing to saltwater intrusion, even though that was not measured in this study.
Analyses of groundwater budgets from the Virginia Eastern Shore peninsula, a geographic region of the Virginia Coastal Plain, indicate that groundwater flow for that isolated aquifer system is generally outward from the surficial aquifer to coastal water bodies and downward into the confined Yorktown-Eastover aquifer system, which is the source of most withdrawals. Downward groundwater flow into the confined Yorktown-Eastover aquifer system is estimated to be less than 2 percent of total recharge and less than 9 percent of net recharge at the water table but makes up more than 93 percent of all inflow to the confined aquifer system. Decades of substantial but relatively consistent groundwater withdrawals have induced greater downward flow rates into the confined aquifer system but also have resulted in loss of groundwater from storage. For the most recent simulated period (2023), estimated storage loss accounts for slightly under 7 percent of withdrawals from the confined aquifer system. The reported withdrawal rate for this period from the confined Yorktown-Eastover system is near the highest reported rate for the Virginia Eastern Shore, which means that the storage depletion is expected to continue, even though groundwater levels appear to be relatively stable. Estimated groundwater flow rates upward from the confining unit underlying the Yorktown-Eastover system and low rates of inflow from coastal water bodies underscore ongoing concerns about up-coning and lateral intrusion of salty groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20261002","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Pope, J.P., Gordon, A.D., and Frederiks, R.S., 2026, Computation of regional groundwater budgets for the Virginia Coastal Plain aquifer system: U.S. Geological Survey Open-File Report 2026–1002, 48 p., https://doi.org/10.3133/ofr20261002. [Supersedes USGS Preprint https://doi.org/10.31223/X5HB5D.]","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-185679","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":503256,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119369.htm","linkFileType":{"id":5,"text":"html"}},{"id":502777,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GJEYW","text":"USGS data release","linkHelpText":"Input and output files from the Zonebudget program used with MODFLOW models to compute regional groundwater budgets for the Virginia Coastal Plain aquifer system"},{"id":502776,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2026/1002/images/"},{"id":502775,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2026/1002/ofr20261002.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2026-1002 XML"},{"id":502772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2026/1002/coverthb.jpg"},{"id":502773,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2026/1002/ofr20261002.pdf","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2026-1002 PDF"},{"id":502774,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20261002/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2026-1002 HTML"}],"country":"United States","state":"Virginia","otherGeospatial":"Virginia Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.5,\n 38.5\n ],\n [\n -75,\n 38.5\n ],\n [\n -75,\n 36.55435844550527\n ],\n [\n -77.5,\n 36.55435844550527\n ],\n [\n -77.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
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Ice jams occur regularly at the southern outlet of Osoyoos Lake, which spans the border between the State of Washington and British Columbia, Canada. In recent winters, ice jams caused (1) decreases in downstream discharge that may adversely affect salmon spawning habitat and (2) short-duration lake-level rise that can interfere with lake level management agreements. In response, water managers sought to understand the environmental conditions associated with the historical ice-jam occurrences on Osoyoos Lake. Researchers compiled datasets of discharge, lake level, and air temperature from four meteorological and three hydrologic stations near Oroville, Washington, to determine “ice-jam” or “non-ice-jam” days from 1942 to 2024.
After confirming known ice jams since 1994 using Landsat 8–9 and Sentinel–2 satellite imagery along with discharge, lake level, and air temperature data, researchers designated ice-jam days. They conducted statistical analyses to examine environmental conditions associated with ice-jam occurrences on Osoyoos Lake. Statistical tests indicated significant differences in wind speed, wind direction, and air temperature between ice-jam and non-ice-jam days. A linear discriminant-analysis model correctly predicted 12 of 13 historical ice-jam days since 1994 and determined that ice jams are more likely under westerly and northwesterly winds near or above 10 kilometers per hour (km/h) and minimum temperatures near or below –9.4 degrees Celsius (°C). An analysis of historical discharge suggests that ice jams have occurred since at least the 1940s, but 13 ice jam days occurred in the past decade (2014–2024), exceeding any previous decade. The daily minimum air temperature in the Osoyoos Lake region has increased at a rate of 0.021 °C per year since the 1940s, but ice jams usually occur in winters with colder average temperatures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265003","collaboration":"Prepared in cooperation with the International Osoyoos Lake Board of Control","programNote":"Water Availability and Use Science Program","usgsCitation":"Sutfin, N.A., and Breen, S.J., 2026, Historical ice jams and associated environmental conditions on Osoyoos Lake: U.S. Geological Survey Scientific Investigations Report 2026–5003, 38 p., https://doi.org/10.3133/sir20265003.","productDescription":"vii, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171288","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":503254,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119368.htm","linkFileType":{"id":5,"text":"html"}},{"id":502874,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5003/sir20265003.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5003 XML"},{"id":502873,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265003/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5003 HTML"},{"id":502872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5003/sir20265003.pdf","size":"49.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5003 PDF"},{"id":502871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5003/coverthb.jpg"},{"id":502875,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5003/images/"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Osoyoos Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.67443538186532,\n 49.11443094771283\n ],\n [\n -119.3142803507082,\n 49.11443094771283\n ],\n [\n -119.3142803507082,\n 48.87431047779373\n ],\n [\n -119.67443538186532,\n 48.87431047779373\n ],\n [\n -119.67443538186532,\n 49.11443094771283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Washington Water Science Center
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Ice jams are accumulations of ice that partially block water from flowing downstream in rivers and lakes. Ice jams form at the shallow outlet of Osoyoos Lake, which drains into the Okanogan River at the border of the United States and Canada. These ice jams can temporarily reduce river flow downstream, which can harm salmon habitat and cause short lived increases in lake levels that complicate international agreements for managing water levels.
To better understand when and why these ice jams form, researchers from the U.S. Geological Survey examined historical records of river flow, lake level, and air temperature data from stations near Oroville, Washington (located just south of the lake outlet), for the years 1942–2024. Researchers used satellite images and environmental data during 1994–2024 to confirm known ice jams and then identified “ice jam days” for that period.
The team compared weather conditions on ice jam days and non-ice-jam days. They found that ice jams are more likely to form when winds blow from the west or northwest at speeds of about 10 kilometers per hour or more, and when minimum temperatures drop to –9.4 degrees Celsius or lower. A statistical model based on air temperature, wind speed, and wind direction correctly identified nearly all known ice jam days since 1994. While the statistical model identified some days without ice jams as ice-jam days, no ice-jam days occurred outside of the range of wind and temperature conditions identified.
Although ice jams have occurred since at least the 1940s, they have become more frequent in recent years: 13 ice jam days occurred during 2014–2024, more than in any previous decade. Even though winter temperatures in the Osoyoos Lake region have risen slightly over time, ice jams tend to occur during colder than average winters.
Understanding the conditions that lead to ice jams can help decision-makers better anticipate when ice jams may occur and plan for their potential effects on salmon habitat and lake level management.
","publicationDate":"2026-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sutfin, Nicholas A. 0000-0003-4429-7814","orcid":"https://orcid.org/0000-0003-4429-7814","contributorId":357883,"corporation":false,"usgs":true,"family":"Sutfin","given":"Nicholas","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breen, Stephen J. 0000-0002-2630-6206","orcid":"https://orcid.org/0000-0002-2630-6206","contributorId":369971,"corporation":false,"usgs":true,"family":"Breen","given":"Stephen","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70275535,"text":"70275535 - 2026 - Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems","interactions":[],"lastModifiedDate":"2026-05-04T16:56:07.20148","indexId":"70275535","displayToPublicDate":"2026-04-16T09:50:08","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17103,"text":"Water Biology and Security","active":true,"publicationSubtype":{"id":10}},"title":"Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems","docAbstract":"In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2026.100626","usgsCitation":"Cooper, C.R., Rogosch, J.S., Smith, N.G., Robertson, C.R., and Wilson, W.M., 2026, Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems: Water Biology and Security, 8 p., https://doi.org/10.1016/j.watbs.2026.100626.","productDescription":"8 p.","ipdsId":"IP-170052","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":504183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2026.100626","text":"Publisher Index Page"},{"id":503953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Colorado River tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.25288697239256,\n 32.83973386818306\n ],\n [\n -103.66787485319756,\n 31.396795472090005\n ],\n [\n -95.91239697047968,\n 27.731334360060373\n ],\n [\n -95.88841147436196,\n 29.31705583154367\n ],\n [\n -103.25288697239256,\n 32.83973386818306\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cooper, Cienna R.","contributorId":370959,"corporation":false,"usgs":false,"family":"Cooper","given":"Cienna","middleInitial":"R.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":960825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":960826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Nathan G.","contributorId":370961,"corporation":false,"usgs":false,"family":"Smith","given":"Nathan","middleInitial":"G.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, Clinton R.","contributorId":370963,"corporation":false,"usgs":false,"family":"Robertson","given":"Clinton","middleInitial":"R.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Wade M.","contributorId":370966,"corporation":false,"usgs":false,"family":"Wilson","given":"Wade","middleInitial":"M.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":960829,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275256,"text":"70275256 - 2026 - Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon","interactions":[],"lastModifiedDate":"2026-04-24T14:51:49.560386","indexId":"70275256","displayToPublicDate":"2026-04-16T09:40:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon","docAbstract":"The timing and mechanism of the integration of the Colorado River and incision of the Grand Canyon remain among geology’s enduring controversies. A key question is the configuration of the upper Colorado River watershed between 11 and 6 million years ago. In this study, we present new evidence from zircon uranium-lead geochronology for the arrival of distinctive Colorado–Green River sediment in the Bidahochi basin by 6.6 million years ago derived from the Browns Park Formation. This is coeval with an order-of-magnitude increase in depositional rate, an increase in carbonate strontium isotope (87Sr/86Sr) ratios, the appearance of large fish species characteristic of fast-flowing waters, and other sedimentological changes. This evidence is consistent with the Colorado River supplying water and sediment to the Bidahochi basin before spillover integration of the river through the Grand Canyon.
","language":"English","publisher":"AAAS","doi":"10.1126/science.adz6826","usgsCitation":"He, J.J., Crow, R.S., Douglass, J.R., Holm-Denoma, C., Vazquez, J.A., Gootee, B.F., Lidzbarski, M.I., Pianowski, L., Gray, H., Heitmann, E., Pearthree, P., House, K., and Dulin, S., 2026, Late Miocene Colorado River arrival in the Bidahochi basin supports spillover origin of Grand Canyon: Science, v. 395, no. 6795, p. 285-295, https://doi.org/10.1126/science.adz6826.","productDescription":"11 p.","startPage":"285","endPage":"295","ipdsId":"IP-179903","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":503513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Bidahochi basin, Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":960249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglass, John R.","contributorId":271080,"corporation":false,"usgs":false,"family":"Douglass","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":960250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":960251,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":960252,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gootee, Brian F. 0000-0001-5251-9080 bgootee@email.arizona.edu","orcid":"https://orcid.org/0000-0001-5251-9080","contributorId":201637,"corporation":false,"usgs":false,"family":"Gootee","given":"Brian","email":"bgootee@email.arizona.edu","middleInitial":"F.","affiliations":[{"id":34160,"text":"Arizona Geological Survey","active":true,"usgs":false}],"preferred":false,"id":960253,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lidzbarski, Marsha I 0009-0001-1534-2930","orcid":"https://orcid.org/0009-0001-1534-2930","contributorId":370374,"corporation":false,"usgs":true,"family":"Lidzbarski","given":"Marsha","middleInitial":"I","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":960254,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pianowski, Laura 0000-0002-5346-8251","orcid":"https://orcid.org/0000-0002-5346-8251","contributorId":218817,"corporation":false,"usgs":true,"family":"Pianowski","given":"Laura","email":"","affiliations":[],"preferred":true,"id":960255,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gray, Harrison J. 0000-0002-4555-7473","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":207019,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":960256,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heitmann, Emma","contributorId":370376,"corporation":false,"usgs":false,"family":"Heitmann","given":"Emma","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":960257,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pearthree, Phil","contributorId":218167,"corporation":false,"usgs":false,"family":"Pearthree","given":"Phil","email":"","affiliations":[{"id":39771,"text":"AZGS","active":true,"usgs":false}],"preferred":false,"id":960258,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":960259,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dulin, Shannon","contributorId":260688,"corporation":false,"usgs":false,"family":"Dulin","given":"Shannon","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":960260,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70275748,"text":"70275748 - 2026 - Logical data model for hydrographic data based on HY_Features concepts","interactions":[],"lastModifiedDate":"2026-05-18T14:33:53.753123","indexId":"70275748","displayToPublicDate":"2026-04-16T09:24:17","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":24339,"text":"OCG Public Engineering Report","active":true,"publicationSubtype":{"id":3}},"seriesNumber":"25-045","title":"Logical data model for hydrographic data based on HY_Features concepts","docAbstract":"This report describes background and design of the “hydrofabric data model” which defines logic for implementation of data schemas and software that deals with hydrologic geospatial data. As a “logical” data model, the hydrofabric data model specifies details necessary to support compatibility of data and software that satisfy diverse needs without unnecessarily restricting implementation details. The logic presented in this report is based on concepts defined in WaterML2 Part 3 Surface Hydrology Features Concepts and is designed to serve the needs of a range of hydroscience use cases.
Development of international community standards applicable to hydrofabrics began, prompted by the World Meteorological Organization Commission for Hydrology, in 2012 [5] . More than 10 years later, this report documents one aspect of a long-term research and development activity that traces its roots back that far.
This report describes terminology, use cases, and background as context preceding presentation of the logical model and discussion of its design. Three appendices document related data models, an example encoding of the hydrofabric data model, and an artificial schematic and tabular data example. The sections of the report can be accessed in the Clause 5 section.
","language":"English","publisher":"Open Geospatial Consortium","usgsCitation":"2026, Logical data model for hydrographic data based on HY_Features concepts: OCG Public Engineering Report 25-045, v, 76 p.","productDescription":"v, 76 p.","ipdsId":"IP-172082","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":504473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":504462,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.opengis.net/doc/PER/hydrofabric"}],"noUsgsAuthors":false,"publicationDate":"2026-04-16","publicationStatus":"PW","contributors":{"editors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":961717,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":70275149,"text":"70275149 - 2026 - Characterizing changes in postfire debris-flow hazard as burned areas recover","interactions":[],"lastModifiedDate":"2026-06-02T15:36:59.528242","indexId":"70275149","displayToPublicDate":"2026-04-16T08:18:14","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing changes in postfire debris-flow hazard as burned areas recover","docAbstract":"Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02936.1","usgsCitation":"Graber, A.P., Thomas, M.A., Kean, J.W., King, J., and Kostelnik, J., 2026, Characterizing changes in postfire debris-flow hazard as burned areas recover: Geosphere, v. 22, no. 3, p. 494-515, https://doi.org/10.1130/GES02936.1.","productDescription":"22 p.","startPage":"494","endPage":"515","ipdsId":"IP-164736","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":503207,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":503429,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02936.1","text":"Publisher Index Page"}],"country":"United States","state":"Arizona, California, Colorado, New Mexico, Washington","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.36424169921565,\n 48.80629133966778\n ],\n [\n -125.66472868317365,\n 39.31207129554762\n ],\n [\n -120.57415228729428,\n 32.73149552158408\n ],\n [\n -102.99484796823218,\n 31.342076734545344\n ],\n [\n -103.00675719934162,\n 36.96546857037297\n ],\n [\n -102.11928173488546,\n 36.875567234398886\n ],\n [\n -102.08687031215692,\n 40.90392441449369\n ],\n [\n -117.07043377025515,\n 40.85240779137647\n ],\n [\n -116.74859098099466,\n 48.97374450456343\n ],\n [\n -125.36424169921565,\n 48.80629133966778\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Graber, Andrew Paul 0000-0003-4179-0291","orcid":"https://orcid.org/0000-0003-4179-0291","contributorId":304628,"corporation":false,"usgs":true,"family":"Graber","given":"Andrew","email":"","middleInitial":"Paul","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":959656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":959657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":959658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Jonathan Michael 0000-0003-0834-2200","orcid":"https://orcid.org/0000-0003-0834-2200","contributorId":350805,"corporation":false,"usgs":true,"family":"King","given":"Jonathan Michael","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"preferred":true,"id":959659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":959660,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275100,"text":"sir20265140 - 2026 - Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona","interactions":[],"lastModifiedDate":"2026-04-20T17:40:45.285521","indexId":"sir20265140","displayToPublicDate":"2026-04-15T15:25:00","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2026-5140","displayTitle":"Analyses of Meteorological and Hydrological Records Support Tribal Members’ Accounts of Changing Climate on the Fort Apache Reservation, East–Central Arizona","title":"Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona","docAbstract":"The Fort Apache Reservation in east–central Arizona, home to the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, contains several climate zones because of the large variation in surface elevation within the reservation. This study was carried out in cooperation with the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona, to raise awareness of how the changing climate affects the Fort Apache Reservation. This report documents the evaluation of existing multidecadal meteorological and hydrological datasets for the Fort Apache Reservation, used to evaluate the effects of a changing climate on the reservation. In this evaluation, near-surface air temperature, snow depth, snow water equivalent, precipitation, and streamflow datasets were analyzed for monotonic trends indicative of changing climatic conditions during specified periods of time. The results of these trend analyses were then compared with the Tribal community's memories of the changing climate.
Trend analysis of near-surface air temperatures from a U.S. Historical Climatological Network station on the Fort Apache Reservation at Whiteriver, Arizona, indicated that mean annual air temperatures have increased by an average of 2.48 degrees Fahrenheit from 1980 to 2023. Records from the same station also indicated that average monthly maximum temperatures recorded for March increased by 5.39 degrees Fahrenheit for the same time period.
Annual precipitation at the five precipitation stations used in this study decreased greatly from the 1980s to 2023. The largest total decrease was 10.07 inches, or 34.7 percent. However, only one of the two precipitation stations with longer term data available prior to 1980 had a significant negative trend when data from the entire period of record, from 1901 to 2023, were analyzed.
Trend analyses show a decrease in the annual maximum snow water equivalent and an earlier disappearance of the snowpack at two Natural Resources Conservation Service snow telemetry stations in the mountainous region just east of the Fort Apache Reservation from 1981 to 2023. Based on the trend analyses, the average annual maximum snow water equivalent has decreased by more than 40 percent at both stations, and the average date when the snowpack was fully melted at the stations in the spring has moved earlier in time from late April to early April or late March. However, a statistically significant trend was not determined for the early April snow water equivalent measured at a nearby Natural Resources Conservation Service snow course across its period of record, indicating that the history of mountain snowpack in this area is not fully understood. Analysis of snowfall data from a National Oceanic and Atmospheric Administration Cooperative Observer Program network station on the Fort Apache Reservation at McNary 2N, AZ (station 025412) indicated that, on average, the measured total annual snowfall at the station decreased 42.4 percent from 1935 to 2023.
Streamflow data from six U.S. Geological Survey streamgages on the Fort Apache Reservation were analyzed for trends. For most streamflow gages, statistically significant trends were not determined for tested parameters when the entire streamflow period of record was used for stations with records going back to at least the 1960s. However, when the data from 1980 to 2023 was tested, most of the streamflow parameters had statistically significant negative trends. All six streamgages showed a decrease in average annual runoff of at least 50 percent from 1980 to 2023; one streamgage showed an 81.8 percent decrease.
A similar statistical finding was observed in the analysis of the annual spring snowmelt peak from one of the six streamgages used in the study and located in an area receiving measurable amounts of snowmelt runoff. When data from the entire period of record (1958–2023) was used, no trend in streamflow was determined; however, a significant negative trend was determined from 1980 to 2023, indicating a decrease in average annual springtime runoff of 62.6 percent. Statistical analysis on the timing of the annual spring snowmelt peak at the same streamgage indicated the snowmelt peak is happening on average about 12 days earlier now (2023) than it did in the past. The trend results for the timing of the annual spring snowmelt peak were the same and statistically significant for both periods tested (1958–2023 and 1980–2023). Two of the streamflow records from the Fort Apache Reservation were compared to the Palmer Hydrological Drought Index computed for Arizona Climate Division 4 (East Central) by the National Centers for Environmental Information. The comparison showed that the streamflow records generally tracked the Palmer Hydrological Drought Index.
In interviews, Tribal community members living on the Fort Apache Reservation described the changes in climate that they observed during their lifetimes. Common themes reported were that air temperatures have become warmer, and the weather is less predictable with changes in seasonal patterns. Drier conditions, lower snowfall, shorter winters, and lower river levels were also reported. These community member observations align with the results of this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20265140","collaboration":"Prepared in cooperation with the White Mountain Apache Tribe of the Fort Apache Reservation, Arizona","usgsCitation":"Mason, J.P., 2026, Analyses of meteorological and hydrological records support Tribal members’ accounts of changing climate on the Fort Apache Reservation, east–central Arizona: U.S. Geological Survey Scientific Investigations Report 2026–5140, 58 p., https://doi.org/10.3133/sir20265140.","productDescription":"Report: x, 58 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180087","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":503253,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119367.htm","linkFileType":{"id":5,"text":"html"}},{"id":502810,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144FN7Q","text":"USGS data release","linkHelpText":"U.S. Historical Climatology Network version 2.5 dataset for station Whiteriver 1 SW, Arizona, from 1873 to 2024, used in Analysis of Meteorological and Hydrological Records Support Tribal Members’ Accounts of Changing Climate on the Fort Apache Reservation, east–central Arizona"},{"id":502808,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2026/5140/sir20265140.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2026-5140 XML"},{"id":502807,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20265140/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2026-5140 HTML"},{"id":502806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2026/5140/sir20265140.pdf","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2026-5140 PDF"},{"id":502805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2026/5140/coverthb.jpg"},{"id":502809,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2026/5140/images/"}],"country":"United States","state":"Arizona","otherGeospatial":"Fort Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.75,\n 34.5\n ],\n [\n -109.45,\n 34.5\n ],\n [\n -109.45,\n 33.5\n ],\n [\n -110.75,\n 33.5\n ],\n [\n -110.75,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue, Suite 221
Tucson, AZ 85719
Cenozoic volcanic rocks of the Arabia Plate cover about 140,000 square kilometers across a distance of about 3,000 kilometers from southern Yemen to southeastern Turkey. The majority of volcanic products are alkali basalts that erupted in restricted areas, commonly over periods of a million or more years, building mafic lava fields, each known in Arabic as a “harrat.” Harrat volcanism commenced following the Oligocene flood-lava effusions that blanketed the (now) Ethiopian highlands, southern Sudan, and western Yemen, and overlapped the latest Oligocene to early Miocene initial riftings of the Red Sea and Gulf of Aden, but the majority of harrat volcanism has been since approximately 13–10 million years ago. Persistent harrat magmatism in restricted locations led to the development of intermediate and evolved magmas (hawaiites, mugearites, benmoreites, trachytes, comendites, and phonolites) mainly through intracrustal crystallization-differentiation. Most of these intermediate and evolved magmas erupt at sites of the greatest aggregate volcanic relief, reflecting sites of the greatest overall magmatic fluxes. Production of fractionated magmas at these sites negates “monogenetic” as an appropriate descriptor of harrat volcanism. This chapter summarizes the geologic, eruptive, and tectonic history and aspects of the petrogenesis of the Cenozoic Arabian alkalic province. Particular emphasis is placed on results of a joint study of Ḩarrat Rahat adjacent to the city of Al Madīnah al Munawwarah, Kingdom of Saudi Arabia, published as U.S. Geological Survey Professional Paper 1862 and Saudi Geological Survey Special Report SGS–SP–2021–1. A goal of this chapter is to provide an introduction to those unfamiliar with this vast, enigmatic, and fascinating region of distributed continental volcanism.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1890J","usgsCitation":"Sisson, T.W., and Calvert, A.T., 2026, Cenozoic distributed volcanism of the Arabia Plate—A review, chap. J of Poland, M.P., Ort, M.H., Stovall, W.K., Vaughan, R.G., Connor, C.B., and Rumpf, M.E., eds., Distributed volcanism—Characteristics, processes, and hazards: U.S. Geological Survey Professional Paper 1890, 28 p., https://doi.org/10.3133/pp1890J.","productDescription":"v, 28 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-154541","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":502814,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1890/j/pp1890J.XML","linkFileType":{"id":8,"text":"xml"},"description":"Professional Paper 1890-J XML"},{"id":502813,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/pp1890J/full","linkFileType":{"id":5,"text":"html"},"description":"Professional Paper 1890-J HTML"},{"id":502812,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1890/j/pp1890J.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Professional Paper 1890-J PDF"},{"id":502811,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1890/j/coverthb.jpg"},{"id":502815,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/pp/1890/j/images"}],"country":"Saudi Arabia","otherGeospatial":"Arabia Plate","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 34.23089949847653,\n 30.787465564261467\n ],\n [\n 47.57613705837829,\n 30.787465564261467\n ],\n [\n 47.57613705837829,\n 17.596830955973672\n ],\n [\n 34.23089949847653,\n 17.596830955973672\n ],\n [\n 34.23089949847653,\n 30.787465564261467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Volcano Science Center
U.S. Geological Survey
1300 SE Cardinal Court Bldg. 10
Vancouver, WA 98683
Unequal representation of focal research areas can arise during the initial stages of project development when investigators make decisions about what, when, and where to study. Regarding when research is conducted, publications on vertebrates are strongly skewed toward breeding-stage studies, leaving sizeable gaps in our knowledge pertaining to behavior and demography in nonbreeding stages. Here, we quantified how the focus on different annual cycle stages has changed over the past 64 years in the field of ornithology, and tested 3 hypotheses to explain underlying correlates of the focus on different stages. We surveyed field-based studies published in Ornithology from 1960 to 2024 and documented the annual cycle stages examined, regions of study, migratory strategies of focal species, and author affiliation for each paper. The tendency to conduct breeding-stage research in ornithology became more, rather than less, pronounced over the 64-year interval, and breeding-stage research was more common when field work focused on migratory species. Therefore, investigators, authors, and editors could likely increase representation of other annual-cycle stages by supporting, conducting, and publishing more studies in the tropics and more studies using remote tracking technologies. More nonbreeding and year-round studies are necessary to fully understand the ecology and evolution of species and develop the most effective strategies for conservation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithology/ukag011","usgsCitation":"Stewart, E.R., and Conway, C.J., 2026, Why are ornithological studies so focused on the breeding stage? A test of hypotheses: Ornithology, ukag011, 7 p., https://doi.org/10.1093/ornithology/ukag011.","productDescription":"ukag011, 7 p.","ipdsId":"IP-144243","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":504186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithology/ukag011","text":"Publisher Index Page"},{"id":503956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Stewart, Erin R.","contributorId":370971,"corporation":false,"usgs":false,"family":"Stewart","given":"Erin","middleInitial":"R.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":960830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":960831,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273879,"text":"70273879 - 2026 - The global proliferation of aquatic, benthic Microcoleus: Taxonomy, distribution, toxin production, ecology, and future directions","interactions":[],"lastModifiedDate":"2026-02-11T15:20:31.144819","indexId":"70273879","displayToPublicDate":"2026-04-15T08:14:14","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"The global proliferation of aquatic, benthic Microcoleus: Taxonomy, distribution, toxin production, ecology, and future directions","docAbstract":"There have been sporadic reports of aquatic, benthic Microcoleus proliferations in freshwater rivers, lakes, and reservoirs for four decades, with reports increasing in frequency over the last twenty years, suggesting a possible rise in their global distribution, frequency, and intensity. Microcoleus can produce anatoxins which are neurotoxic, and ingestion of toxic mats has caused hundreds of dog fatalities and raised serious human and ecological health concerns. This review synthesizes and evaluates current knowledge on Microcoleus distribution, taxonomy, toxin production, toxicity, ecology, environmental drivers, and biotic interactions. Toxin-producing Microcoleus have been reported in at least 18 countries, though many regions have not conducted toxin testing, suggesting a broader but under-reported distribution. Proliferations occur across diverse habitats, including cobble-bedded streams, large sandy rivers, reservoirs, and lakes. Microcoleus proliferations also occur on macrophytes, both in lakes and rivers. Genomic analyses currently classify anatoxin-producing Microcoleus into distinct species, with all known anatoxin-producers isolated from freshwater ecosystems. Anatoxin concentrations vary widely over space and time, within and among waterbodies. While studies on environmental drivers remain limited, research in cobble-bedded rivers suggests that moderate enrichment of dissolved inorganic nitrogen and low dissolved reactive phosphorus concentrations in the water column promote proliferation. Metagenomic approaches have revealed unique nutrient acquisition and storage strategies used by Microcoleus. Key knowledge gaps remain around the environmental and ecological triggers of proliferation, toxin production, genomic diversity and microbial interactions. Addressing these gaps through coordinated, global studies using robust datasets and consistent methods is critical to improve prediction, monitoring, and mitigation of this increasingly widespread public and ecological health threat.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2026.125441","usgsCitation":"Kelly, L.T., Beach, D.G., Blaszczak, J.R., Bouma-Gregson, K., Brown, S.M., Cheng, H., Davidson, J.L., Fastner, J., Francis, M., Garcia Jimenez, A., Genzoli, L., Goel, R., Gonzalez, D., Handley, K.M., Hilt, S., Humbert, J., Jamieson, R., Johnston, L., Junier, P., Lawrence, J., McCarron, P., Meissner, S., Mormando, J., Puddick, J., Quiblier, C., Rajpirathap, N., Schampera, C., Selwood, A., Shearer, K., Sohrab, A., Stancheva, R., Valadez-Cano, C., Zebrecky, J.M., and Wood, S.A., 2026, The global proliferation of aquatic, benthic Microcoleus: Taxonomy, distribution, toxin production, ecology, and future directions: Water Research, v. 294, 125441, 22 p., https://doi.org/10.1016/j.watres.2026.125441.","productDescription":"125441, 22 p.","ipdsId":"IP-183789","costCenters":[{"id":154,"text":"California Water Science 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Jordan M.","contributorId":366196,"corporation":false,"usgs":false,"family":"Zebrecky","given":"Jordan","middleInitial":"M.","affiliations":[],"preferred":false,"id":955405,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Wood, Susanna A.","contributorId":366197,"corporation":false,"usgs":false,"family":"Wood","given":"Susanna","middleInitial":"A.","affiliations":[],"preferred":false,"id":955406,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70275000,"text":"gip265 - 2026 - Mount Rainier volcanic hazard information","interactions":[],"lastModifiedDate":"2026-04-20T17:37:33.148135","indexId":"gip265","displayToPublicDate":"2026-04-14T15:46:56","publicationYear":"2026","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information 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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