The geologic map of the Greater Antilles and Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. This map was prepared to serve as a base map for a mineral resource assessment of the region. Several small-scale regional geologic maps of the region have been prepared in the past. This report supersedes an earlier version of the geologic map of the Greater Antilles and the Virgin Islands that was released as U.S. Geological Survey (USGS) Open-File Report 2019–1036.
For this report, the regional geologic overview shown on sheet 1 covers Cuba; the island of Hispaniola, which includes Haiti and Dominican Republic; Jamaica; the Cayman Islands; Puerto Rico; and the U.S. and British Virgin Islands. Sheet 2 shows the geology of Cuba and Cayman Islands, sheet 3 the geology of Jamaica, sheet 4 the geology of Hispaniola, and sheet 5 the geology of Puerto Rico and Virgin Islands. Accompanying the maps are three tables: table 1 lists the map units (in alphabetical order by map-unit label), their ages, and the countries or territories in which they can be found. These are listed in alphabetical order for ease in locating unit names from the symbols on the maps. Table 2 is a list of sources for the geologic map compilation of Puerto Rico. Table 3 shows formations in the Devil’s Race Course Group of Jamaica.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3534","programNote":"Mineral Resources Program","usgsCitation":"Wilson, F.H., and Labay, K.A., comps., 2025, Geologic map of the Greater Antilles and Virgin Islands: U.S. Geological Survey Scientific Investigations Map 3534, 5 sheets, scales 1:2,500,000, 1:1,000,000, 1:250,000, 1:650,000, 1:300,000, and 1:140,000, 102-p. pamphlet, https://doi.org/10.3133/sim3534. [Supersedes USGS Open-File Report 2019–1036.]","productDescription":"Pamphlet: vi, 102 p.; 5 Sheets: 53.68 x 35.41 inches or smaller; 3 Data Releases","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119640","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":499037,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118719.htm","linkFileType":{"id":5,"text":"html"}},{"id":493264,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QGKUBG","text":"USGS data release","linkHelpText":"Age determinations from various geochronological methods of rock samples in the Greater Antilles and Virgin Islands"},{"id":493263,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1ZN39XQ","text":"USGS data release","linkHelpText":"U-Pb isotopic data and zircon age determinations from the Island of Puerto Rico, United States"},{"id":493262,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13X7BHY","text":"USGS data release","linkHelpText":"Data release for the geologic map of the Greater Antilles and Virgin Islands"},{"id":493261,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_sheet5.pdf","text":"Sheet 5","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Sheet 5","linkHelpText":"- Geologic Map of Puerto Rico and the Virgin Islands"},{"id":493260,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_sheet4.pdf","text":"Sheet 4","size":"6.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Sheet 4","linkHelpText":"- Geologic Map of Hispaniola"},{"id":493259,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_sheet3.pdf","text":"Sheet 3","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Sheet 3","linkHelpText":"- Geologic Map of Jamaica"},{"id":493258,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_sheet2.pdf","text":"Sheet 2","size":"22.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Sheet 2","linkHelpText":"- Geologic Map of Cuba and the Cayman Islands"},{"id":493257,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_sheet1.pdf","text":"Sheet 1","size":"30.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Sheet 1","linkHelpText":"- Geologic Map of the Greater Antilles and Virgin Islands"},{"id":493255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3534/coverthb.jpg"},{"id":493256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3534/sim3534_pamphlet.pdf","text":"Pamphlet","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3534 Pamphlet"}],"country":"Cayman Islands, Cuba, Dominican Republic, Great Britain, Haiti, Jamaica, United States","otherGeospatial":"Greater Antilles, Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.41689796960137,\n 23.68158826700146\n ],\n [\n -85.41689796960137,\n 16.88696307754377\n ],\n [\n -63.546232446293374,\n 16.88696307754377\n ],\n [\n -63.546232446293374,\n 23.68158826700146\n ],\n [\n -85.41689796960137,\n 23.68158826700146\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Passive acoustic monitoring is a cost-effective, minimally invasive technology commonly used to study behavior and population dynamics of soniferous fish species. To understand the strengths and limitations of acoustic monitoring for this purpose at fish spawning aggregations (FSA) requires an assessment of the variability in aggregation-associated sounds (AAS) as a function of time, space, and proximity for spawning fishes of interest. Here, we evaluate temporal and spatial trends in the detection of AAS by Nassau Grouper (Epinephelus striatus) using an array of six hydrophones deployed across a large Nassau Grouper FSA at Little Cayman, Cayman Islands. We collected continuous data for nine days during a winter spawning season and subsequently used an automatic classifier to extract the embedded Nassau Grouper AAS. Using these data, we analyzed variability in spatiotemporal AAS detection rates across the array with a Bayesian mixed effects model. We found high variability in the detection of AAS across the spawning site, with positive correlations among neighboring hydrophone pairs trending toward negative correlations with distances exceeding 350 m. Indeed, temporal trends in AAS rates at the spawning site were approximately inverted at the two most distant hydrophones (~600 m). Across the hydrophone network, our model predicted strong positive effects of fish proximity, spawning behavior, and crepuscular periods on detected AAS. Our findings suggest hydrophone placement can strongly influence AAS detection rates and even basic temporal patterns in AAS across the spawning season. Given both the vagaries of movement and behavior of aggregating fish at spawning sites and the limits of AAS detection using standard monitoring tools, we suggest spawning site acoustic monitoring programs deploy hydrophone arrays of sufficient size to capture the site-wide trends in AAS rates if possible; this is particularly true if researchers hope to compare/contrast AAS rates between spawning sites or across seasons for the purpose of population assessment.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70081","usgsCitation":"Van Horn, C.J., Candelmo, A.C., Heppell, S.A., McCoy, C.R., Pattengill-Semmens, C.V., Waterhouse, L., Cherubin, L.M., Taylor, J., Michaels, W., Locascio, J., Ibrahim, A.K., and Semmens, B.X., 2025, Hydrophone placement yields high variability in detection of Epinephelus striatus calls at a spawning site.: Ecological Applications, v. 35, no. 5, e70081, 21 p., https://doi.org/10.1002/eap.70081.","productDescription":"e70081, 21 p.","ipdsId":"IP-170566","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70081","text":"Publisher Index Page"},{"id":494311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Little Cayman, Cayman Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.1384616529091,\n 19.741226725935803\n ],\n [\n -80.1384616529091,\n 19.647682249769503\n ],\n [\n -79.94337474038241,\n 19.647682249769503\n ],\n [\n -79.94337474038241,\n 19.741226725935803\n ],\n [\n -80.1384616529091,\n 19.741226725935803\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Horn, Cameron J.","contributorId":359810,"corporation":false,"usgs":false,"family":"Van Horn","given":"Cameron","middleInitial":"J.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":946323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Candelmo, Alli C.","contributorId":359814,"corporation":false,"usgs":false,"family":"Candelmo","given":"Alli","middleInitial":"C.","affiliations":[{"id":13188,"text":"Reef Environmental Education Foundation (REEF)","active":true,"usgs":false}],"preferred":false,"id":946325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heppell, Scott A.","contributorId":359816,"corporation":false,"usgs":false,"family":"Heppell","given":"Scott","middleInitial":"A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":946326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCoy, Croy R.M.","contributorId":359818,"corporation":false,"usgs":false,"family":"McCoy","given":"Croy","middleInitial":"R.M.","affiliations":[{"id":85923,"text":"Department of Environment","active":true,"usgs":false}],"preferred":false,"id":946327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pattengill-Semmens, Christine V.","contributorId":359819,"corporation":false,"usgs":false,"family":"Pattengill-Semmens","given":"Christine","middleInitial":"V.","affiliations":[{"id":13188,"text":"Reef Environmental Education Foundation (REEF)","active":true,"usgs":false}],"preferred":false,"id":946328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waterhouse, Lynn 0000-0002-7455-7632","orcid":"https://orcid.org/0000-0002-7455-7632","contributorId":348524,"corporation":false,"usgs":true,"family":"Waterhouse","given":"Lynn","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":946329,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cherubin, Laurent M.","contributorId":359820,"corporation":false,"usgs":false,"family":"Cherubin","given":"Laurent","middleInitial":"M.","affiliations":[{"id":65664,"text":"Harbor Branch Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":946330,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Taylor, J. Christopher","contributorId":359821,"corporation":false,"usgs":false,"family":"Taylor","given":"J. Christopher","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":946331,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Michaels, William","contributorId":359822,"corporation":false,"usgs":false,"family":"Michaels","given":"William","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":946332,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Locascio, James","contributorId":359823,"corporation":false,"usgs":false,"family":"Locascio","given":"James","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":946333,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ibrahim, Ali K.","contributorId":359812,"corporation":false,"usgs":false,"family":"Ibrahim","given":"Ali","middleInitial":"K.","affiliations":[{"id":65664,"text":"Harbor Branch Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":946324,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Semmens, Brice X.","contributorId":359824,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","middleInitial":"X.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":946334,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70270735,"text":"70270735 - 2025 - Impacts of flowering rush (Butomus umbellatus L.) on macrophyte diversity and composition in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2025-08-22T14:51:12.417579","indexId":"70270735","displayToPublicDate":"2025-08-06T07:45:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of flowering rush (Butomus umbellatus L.) on macrophyte diversity and composition in the Upper Mississippi River","docAbstract":"Flowering rush (Butomus umbellatus L.), a perennial plant native to Eurasia, made a widespread appearance in the Upper Mississippi River in the United States in 2020, following extremely high river discharge during the previous year. Flowering rush expanded rapidly and was found at 1–10% of sites (n = 6,630 total sites) across a 400 km river reach within the first 4 years of invasion. Flowering rush invaded at least 12 of 31 wetland vegetation classes, including submersed aquatic, rooted-floating, deep marsh, and shallow marsh. Analysis of long-term macrophyte data and our targeted field study revealed that plant diversity declined with greater abundance of flowering rush over a 4-year early invasion period, suggesting that native species were displaced. Furthermore, species correlation plots showed a significant negative correlation (r < -0.1) between flowering rush and several native species, including wild celery, water stargrass, and wild rice. Non-metric multi-dimensional scaling (NMDS) ordination placed flowering rush near the center of the plot, which may indicate tolerance to a wide range of environmental conditions such as water depth, flow, and substrate. Centering on the NMDS plot also shows that flowering rush invades many types of vegetated aquatic land cover classes, which was also supported by our geographic information systems analysis of land cover invasion. These habitat associations and ecological impacts of the recent, widespread invasion of flowering rush in the Upper Mississippi River can help inform restoration and management actions during early invasion. Continuing long-term data collection can break limitations on modeling cause-effect relationships and provide insights to the future ecological trajectory of the macrophyte community to this non-native invasive species.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-025-03643-z","usgsCitation":"Carhart, A., Larson, D.M., Froehly, J., Lund, E., Szura, S., and Fopma, S., 2025, Impacts of flowering rush (Butomus umbellatus L.) on macrophyte diversity and composition in the Upper Mississippi River: Biological Invasions, v. 27, 188, 16 p., https://doi.org/10.1007/s10530-025-03643-z.","productDescription":"188, 16 p.","ipdsId":"IP-176660","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":494516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.21798186280225,\n 45.16720641933907\n ],\n [\n -93.21798186280225,\n 41.95055183534416\n ],\n [\n -89.4311724348378,\n 41.95055183534416\n ],\n [\n -89.4311724348378,\n 45.16720641933907\n ],\n [\n -93.21798186280225,\n 45.16720641933907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2025-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Carhart, Alicia 0000-0002-9977-8124","orcid":"https://orcid.org/0000-0002-9977-8124","contributorId":223884,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":946927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Froehly, Jennifer","contributorId":360275,"corporation":false,"usgs":false,"family":"Froehly","given":"Jennifer","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":946928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, Eric","contributorId":221777,"corporation":false,"usgs":false,"family":"Lund","given":"Eric","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szura, Stephanie","contributorId":360278,"corporation":false,"usgs":false,"family":"Szura","given":"Stephanie","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946930,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fopma, Seth","contributorId":360281,"corporation":false,"usgs":false,"family":"Fopma","given":"Seth","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946931,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269823,"text":"fs20253036 - 2025 - Applying U.S. Geological Survey science to understand effects to water supply in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2026-02-03T14:46:41.794993","indexId":"fs20253036","displayToPublicDate":"2025-08-05T16:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3036","displayTitle":"Applying U.S. Geological Survey Science to Understand Effects to Water Supply in the Upper Colorado River Basin","title":"Applying U.S. Geological Survey science to understand effects to water supply in the Upper Colorado River Basin","docAbstract":"The Colorado River Basin is a vital source of water to more than 40 million people in the Western United States and Mexico, including in major cities like Denver, Las Vegas, Phoenix, Tucson, Los Angeles, and San Diego, and supports irrigation for about 16,000 square kilometers of agricultural land. Since 2000, the southwestern United States has been unusually dry due to low precipitation and warm air temperatures, contributing to extreme water level declines of the two large reservoirs on the Colorado River, Lake Mead and Lake Powell. In 2021, these reservoirs reached their lowest levels on record, resulting in unprecedented restrictions on water usage in the basin. As much as 90 percent of the annual runoff in the Colorado River Basin originates in areas upstream from Lake Powell (hereafter, these areas will be referred to collectively as the “Upper Basin”). Consequently, understanding the processes that can affect water supply in the Upper Basin could be crucial for supporting human, agricultural, and ecological needs across a large spatial scale.
The U.S. Geological Survey (USGS) does a wide variety of science in cooperation with resource managers, municipalities, tribes, and local, State, and Federal agencies to help improve understanding of processes, such as streamflow and water quality, potentially affecting water supply in the Upper Basin. This fact sheet describes three key potential factors affecting water supply in the Upper Basin—snow processes and water storage, wildfire and basin hydrology, and salinity concentrations and water quality—and highlights associated USGS research activities in the basin.
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
The U.S. Geological Survey (USGS) cooperates with resource managers, municipalities, tribes, and local, State, and Federal agencies to help improve understanding of processes potentially affecting water supply in the Colorado River Basin. This fact sheet describes three key potential factors affecting water supply in the upper portion of the basin—snow processes and water storage, wildfire and basin hydrology, and salinity concentrations and water quality—and highlights associated USGS research activities in the basin. The Colorado River Basin is an important water source for more than 40 million people in the Western United States and Mexico, providing water to major cities and irrigating agricultural land. However, since 2000, the region has faced prolonged drought conditions, leading to record low levels in Lake Mead and Lake Powell and resulting in water usage restrictions. The USGS plays a key role in studying the Colorado River Basin water supply. Understanding the processes that can affect water supply in the upper portion of the basin could be crucial for supporting human, agricultural, and ecological needs across a large spatial scale.
","publicationDate":"2025-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Cory A. 0000-0003-1461-7848 cawillia@usgs.gov","orcid":"https://orcid.org/0000-0003-1461-7848","contributorId":689,"corporation":false,"usgs":true,"family":"Williams","given":"Cory","email":"cawillia@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944727,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270729,"text":"70270729 - 2025 - Harmless tags or hazardous ads? Investigating the potential for ear tags to increase predation on neonatal ungulates","interactions":[],"lastModifiedDate":"2026-01-05T16:38:47.312452","indexId":"70270729","displayToPublicDate":"2025-08-05T12:31:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Harmless tags or hazardous ads? Investigating the potential for ear tags to increase predation on neonatal ungulates","docAbstract":"Studies involving individually marked animals provide insights predicated on the assumption marked individuals are accurate models of their unmarked counterparts. Taxa-specific and marker-specific examinations are needed to determine if marked animals are suitable models for the parameter(s) being measured. Our objective was to determine if brightly colored ear tags influenced the probability of predation for neonatal ungulates. We captured 94 neonatal pronghorn (Antilocapra americana (Ord, 1815)), fitted each neonate with a tracking collar, and attached a yellow ear tag to 49 (52.1%) of the captured neonates. We monitored the survival of each neonate during 2023–2024 in Oklahoma, USA. Predation was the leading cause of mortality during our monitoring period and accounted for 29 (82.9%) of the 35 mortalities with a known cause. Coyotes (Canis latrans Say, 1823) were the predominant predator of neonatal pronghorn in our study area. Presence of a yellow ear tag seemingly did not influence the probability of predation, even though coyotes can distinguish yellow objects from most natural backgrounds. A larger sample size may be needed to validate our results, but neonatal ungulates with an ear tag appear to be accurate models of neonatal ungulates without an ear tag when examining predation risk.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2025-0007","usgsCitation":"Turnley, M.T., Fairbanks, W.S., Lonsinger, R.C., Cherry, M.J., Dart, M.M., DeYoung, R.W., Hahn, D.P., Heffelfinger, L.J., Rickels, C.M., Tanner, E.P., Wang, H.G., and Chitwood, M.C., 2025, Harmless tags or hazardous ads? 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This dataset provides a unique opportunity to assess the application of fine spatial (5 m) and temporal (weekly) resolution VSWIR data to estimate root zone soil salinity; when combined with environmental variables such as elevation, these data can account for some of these factors. In this study, we utilized VSWIR and elevation datasets in a random forest regression to predict and map soil salinity in an intermittently tidal estuary, Devereux Slough, located in Santa Barbara County, California. The final model combined spectral indices with elevation to better capture soil salinity dynamics despite lower correlation (r = 0.85) than solely using elevation (r = 0.92). This research demonstrates the utility of remote sensing datasets, namely, elevation and the modified Anthocyanin Reflectance Index (mARI), for predicting root zone soil salinity in intermittently tidal coastal wetlands. 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We assembled a comprehensive global dataset of field measurements of BNF in all major N-fixing niches across natural terrestrial biomes derived from the analysis of 376 BNF studies. The dataset comprises 32 variables, including site location, biome type, N-fixing niche, sampling year, quantification method, BNF rate (kg N ha−1 y−1), the percentage of nitrogen derived from the atmosphere (%Ndfa), N fixer or N-fixing substrate abundance, BNF rate per unit of N fixer abundance, and species identity. Overall, the dataset combines 1,207 BNF rates for trees, shrubs, herbs, soil, leaf litter, woody litter, dead wood, mosses, lichens, and biocrusts, 152 herb %Ndfa values, 1,005 measurements of N fixer or N-fixing substrate abundance, and 762 BNF rates per unit of N fixer abundance for a total of 424 species across 66 countries. This dataset facilitates synthesis, meta-analysis, upscaling, and model benchmarking of BNF fluxes at multiple spatial scales.
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Past research has focused on preserving migration paths where habitat fragmentation and loss disrupt movement corridors. However, shifting residency-migration trade-offs are the stronger driver of migration loss in some populations. Suburban residential developments may provide ungulates with anthropogenic food sources and refuge from predators, which can increase population growth among short-distance migrants relative to long-distance migrants. This trend can increase wildlife vehicle collisions and other human–wildlife conflicts while simultaneously reducing hunting opportunities. Yet, individual animals vary in their tolerance of human disturbance. We investigated how interindividual variation relative to conflict and human habituation influences elk migration and space use on shared winter range. We used a clustering algorithm applied to GPS collar data to identify elk use of anthropogenic food resources in suburban habitat. Cluster locations identified all known anthropogenic subsidy locations during the study period. Elk that used suburban anthropogenic food sources also migrated 60% shorter distances between summer and winter ranges than elk with no known use of these food subsidies. Elk use of protected wintering grounds was spatially structured such that conflict-prone, short-distance migrants disproportionately used areas with more human activity. Clustering algorithms applied to GPS collar data may allow managers to identify foci of concentrated use that generates human–wildlife conflict, and where prion deposition and environmental contamination facilitate the spread of chronic wasting disease, particularly in suburban areas with anthropogenic food subsidies. The apparent spatial structuring of shared winter range according to the conflict potential and migration strategy of individual elk may also permit managers to assess relative recruitment among cryptic population segments using different migration strategies and facilitate targeted, adaptive management actions. These associations between conflict, human habituation, and migration shed light on the urbanization of wildlife species, inform efforts to manage human–wildlife conflict and disease spread, and emphasize that a multipronged approach beyond maintaining habitat corridors may be necessary to conserve long-distance migrations for species that can become human-habituated.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ECS2.70344","usgsCitation":"Cotterill, G.G., Cole, E., Cross, P., Dewey, S., Wise, B., and Graves, T., 2025, Elk personality and anthropogenic food subsidy: Managing conflict and migration loss: Ecosphere, v. 16, no. 8, e70344, 12 p., https://doi.org/10.1002/ECS2.70344.","productDescription":"e70344, 12 p.","ipdsId":"IP-159240","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":494437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70344","text":"Publisher Index Page"},{"id":493704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111,\n 43.7\n ],\n [\n -111,\n 43.4\n ],\n [\n -110.5,\n 43.4\n ],\n [\n -110.5,\n 43.7\n ],\n [\n -111,\n 43.7\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":945107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Eric K.","contributorId":302890,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":65572,"text":"U.S. Fish and Wildlife Service, National Elk Refuge","active":true,"usgs":false}],"preferred":false,"id":945108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":945109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewey, Sarah R.","contributorId":342391,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":945110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wise, Ben L.","contributorId":359279,"corporation":false,"usgs":false,"family":"Wise","given":"Ben L.","affiliations":[{"id":83136,"text":"Wyoming Game & Fish Department","active":true,"usgs":false}],"preferred":false,"id":945111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":945112,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269632,"text":"fs20253038 - 2025 - Global maps of critical mineral production in 2023","interactions":[],"lastModifiedDate":"2026-02-03T14:45:36.109669","indexId":"fs20253038","displayToPublicDate":"2025-08-05T09:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3038","displayTitle":"Global Maps of Critical Mineral Production in 2023","title":"Global maps of critical mineral production in 2023","docAbstract":"The global production of many mineral commodities, especially critical minerals, is concentrated in a few countries that have mineral resources and the infrastructure necessary to mine and process those resources. For this reason, the type and amount of mineral production differ by country. For example, many countries produce such metallic ores as gold and silver, whereas only a few countries produce magnesium, niobium, platinum-group metals, and rare earths. The concentration of mining and processing in certain countries necessitates the existence of a global supply chain.
A mineral supply chain is the sequence of mining and processing of minerals and manufacturing of products. Mineral supply chains are global in scale, complex, and dynamic. Supply chain data can be used to understand how a country’s mineral resources and various economic, technical, and environmental factors affect the complexity of global supply chains.
This fact sheet summarizes the world’s leading countries (those accounting for 5 percent or more of a commodity’s global production in 2023) for production of select mineral commodities (mainly critical minerals) in the mining and processing stages. These countries and the minerals they produce are synthesized on global maps to communicate the status of, and potential risk to, mineral commodity supply chains from geographic production concentration. Trade data from United Nations Statistics Division (2025) is used to support assessments of the observed production data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253038","usgsCitation":"Chung, J., Xun, S., and Textoris, S.D., 2025, Global maps of critical mineral production in 2023: U.S. Geological Survey Fact Sheet 2025–3038, 5 p., https://doi.org/10.3133/fs20253038.","productDescription":"5 p.","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-179511","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":494162,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118718.htm","linkFileType":{"id":5,"text":"html"}},{"id":493043,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3038/images/"},{"id":493042,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3038/fs20253038.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3038 XML"},{"id":493041,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253038/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3038 HTML"},{"id":493039,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3038/coverthb.jpg"},{"id":493040,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3038/fs20253038.pdf","text":"Report","size":"5.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3038 PDF"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"Fourier amplitude spectra from regional earthquakes in the eastern United States are used in a parametric inversion for source, path, and site effects. Five earthquakes are selected for analysis during the installation of the United States National Seismic Network (US), Earthscope’s USArray Transportable Array (TA), and other temporary arrays to maximize station coverage. A global search algorithm is used to solve for site response from 0.1 to 15 Hz, corner frequency, geometrical spreading (r-γ), and frequency dependent anelastic attenuation in the form Q(f) = Qof α. Tradeoff between moment and geometric spreading is handled by fixing the moment. The tradeoff between corner frequency and Q(f) is solved by selecting the value of corner frequency that minimizes an objective function defined over all stations. Values of site response and attenuation parameters show a strong spatial correlation with the physiographic provinces of the eastern United States. Site response for the Atlantic Coastal Plain is consistent with previous work using spectral ratios relative to a reference site, defined by strong resonance peaks correlated with the thickness of sediments. Site response for the other physiographic provinces is markedly different from the coastal plain, with a lack of distinct resonance peaks and a broad moderate high at frequences from 0.1 to 0.5 Hz consistent with the hard-rock geology of the regions. Like site response, Q(f) has a strong correlation with physiographic province, showing lower values on the coastal plain and higher values inland. Geometric spreading exponent, γ, decreases with increasing hypocenter distance from just above 1 at a few tens of kilometers to 0.9 at 500 km. The limited range in geometric spreading values is attributed to starting the Fourier transform window at the S‐wave arrival for all distances and averaging over multiple wave types.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120250066","usgsCitation":"Hartzell, S.H., Martinetti, L., Mendoza, C., and Schmitt, R.G., 2025, Site response and wave propagation effects in the eastern United States: Bulletin of the Seismological Society of America, v. 115, no. 5, p. 2485-2506, https://doi.org/10.1785/0120250066.","productDescription":"22 p.","startPage":"2485","endPage":"2506","ipdsId":"IP-174795","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":493930,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.07834108451145,\n 43.347066936734876\n ],\n [\n -83.07190566074532,\n 41.15850918749996\n ],\n [\n -84.72974599179413,\n 38.49572818331108\n ],\n [\n -87.6040403599389,\n 37.557442613196955\n ],\n [\n -90.35205007389611,\n 32.79825745697784\n ],\n [\n -81.70066250884963,\n 32.45943477635677\n ],\n [\n -76.33120640624651,\n 37.93006949063302\n ],\n [\n -74.11435019028751,\n 44.90250530044207\n ],\n [\n -74.96201722230823,\n 45.03628280801624\n ],\n [\n -78.07834108451145,\n 43.347066936734876\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinetti, Luis B.","contributorId":359446,"corporation":false,"usgs":false,"family":"Martinetti","given":"Luis B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":945457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mendoza, Carlos 0000-0002-2428-7064","orcid":"https://orcid.org/0000-0002-2428-7064","contributorId":343872,"corporation":false,"usgs":false,"family":"Mendoza","given":"Carlos","email":"","affiliations":[{"id":18923,"text":"Universidad Nacional Autonoma de Mexico","active":true,"usgs":false}],"preferred":false,"id":945458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945459,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269896,"text":"70269896 - 2025 - Contributions of Great Salt Lake playa- and industrially-sourced priority pollutant metals in dust contribute to possible health hazards in the communities of northern Utah","interactions":[],"lastModifiedDate":"2025-08-06T14:53:59.285549","indexId":"70269896","displayToPublicDate":"2025-08-05T07:48:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16135,"text":"GeoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Contributions of Great Salt Lake playa- and industrially-sourced priority pollutant metals in dust contribute to possible health hazards in the communities of northern Utah","docAbstract":"Communities and ecosystems of northern Utah, USA receive particulate pollution from anthropogenic activity and dust emissions from sources including the Great Salt Lake (“the Lake”) playa. In addition to affecting communities, anthropogenic pollution is delivered to the Lake's playa sediments, which are eroded during dust events. Yet, spatial variability in dust flux and composition and their risks to human health are poorly understood. We analyzed dust in 17 passive samplers proximal to the Lake during fall 2022 for dust flux, the dust fraction of particulate matter, 87Sr/86Sr, and elemental geochemistry. We evaluated spatial patterns of 11 priority pollutant metals and estimated the hypothetical non-cancer dust and soil ingestion health hazard for six age cohorts. We observed the highest dust fluxes proximal to the Lake's playa. The highest concentrations of and greatest number of metals occurred in and south of Ogden, UT. Sites to the northeast of Farmington Bay had the highest fluxes. Metal concentrations and 87Sr/86Sr suggest that the dust composition near Bountiful represents contributions from anthropogenic sources, whereas the dust composition to the northeast of Farmington Bay reflects the Lake's playa emissions. Evaluations of potential health hazards from dust ingestion suggest that children between birth and 6 years are vulnerable at higher ingestion rates. Thallium, As, Pb, Co and Cr contributed most to the estimated hazard. Among these, As and sometimes Pb are likely derived from the Lake's playa emissions. Thus, suppression of dust emissions from the Lake's playa may decrease possible health risks for children in northern Utah.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GH001462","usgsCitation":"Putman, A.L., Blakowski, M.A., DiViesti, D.N., Fernandez, D.P., McDonnell, M.C., Longley, P.C., and Jones, D.K., 2025, Contributions of Great Salt Lake playa- and industrially-sourced priority pollutant metals in dust contribute to possible health hazards in the communities of northern Utah: GeoHealth, v. 9, no. 8, e2025GH001462, 26 p., https://doi.org/10.1029/2025GH001462.","productDescription":"e2025GH001462, 26 p.","ipdsId":"IP-172297","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":494432,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gh001462","text":"Publisher Index Page"},{"id":493641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"northern Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.2658188558911,\n 41.97119727006901\n ],\n [\n -113.2658188558911,\n 40.20518704347239\n ],\n [\n -111.08665526028199,\n 40.20518704347239\n ],\n [\n -111.08665526028199,\n 41.97119727006901\n ],\n [\n -113.2658188558911,\n 41.97119727006901\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakowski, Molly A. 0000-0003-4196-2161","orcid":"https://orcid.org/0000-0003-4196-2161","contributorId":316614,"corporation":false,"usgs":true,"family":"Blakowski","given":"Molly","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DiViesti, Destry N. 0000-0002-9220-4734","orcid":"https://orcid.org/0000-0002-9220-4734","contributorId":316616,"corporation":false,"usgs":true,"family":"DiViesti","given":"Destry","middleInitial":"N.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Diego P.","contributorId":138701,"corporation":false,"usgs":false,"family":"Fernandez","given":"Diego","email":"","middleInitial":"P.","affiliations":[{"id":12499,"text":"Univ. of Utah","active":true,"usgs":false}],"preferred":false,"id":944905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonnell, Morgan C. 0000-0001-6946-9286","orcid":"https://orcid.org/0000-0001-6946-9286","contributorId":296906,"corporation":false,"usgs":true,"family":"McDonnell","given":"Morgan","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Longley, Patrick C. 0000-0001-8767-5577","orcid":"https://orcid.org/0000-0001-8767-5577","contributorId":268147,"corporation":false,"usgs":true,"family":"Longley","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944907,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944908,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269910,"text":"70269910 - 2025 - High resolution mapping of submerged sediment size and suitable salmon spawning habitat using topo-bathymetric Lidar in the Santiam Basin, Oregon","interactions":[],"lastModifiedDate":"2025-08-06T14:47:01.818797","indexId":"70269910","displayToPublicDate":"2025-08-05T07:41:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"High resolution mapping of submerged sediment size and suitable salmon spawning habitat using topo-bathymetric Lidar in the Santiam Basin, Oregon","docAbstract":"The distribution of river-bed grain sizes plays a foundational role in river morphology and ecology. River-bed grain size is a key driver of channel form and process, and has first order effects on aquatic macroinvertebrate assemblages, fish nesting, and biogeochemical processes. Despite this importance, tools to spatially quantify grain-size distributions, particularly submerged grain-size distributions, are lacking. Efforts to address this knowledge gap include developing optical and sonographic tools, however, these approaches have limitations, especially in shallow rivers and over large spatial extents. This study quantifies submerged grain size at high resolution (1 m2) across 260 km of geomorphically diverse river corridors in the Santiam River Basin, Oregon, by pairing bathymetric Lidar point clouds with georeferenced pebble counts. Results suggest that derivatives of Lidar point clouds are able to accurately estimate measured median grain size across seven of the eight river reaches investigated, including reaches above and below high-head dams. Spatial analysis of predicted grain-sizes in the context of Chinook salmon spawning habitat suggests that suitable size sediment patches in the upper, unregulated reaches the study basin is typically small and unorganized. In contrast, the larger rivers downstream of high-head dams typically have larger areas of suitable spawning gravels. This method may be useful for quantification of fish and macroinvertebrates habitats, surface grain-size metrics for sediment transport models, and monitoring of natural and anthropogenic changes in river systems.
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Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
More than 10 years following the onset of the sea star wasting disease (SSWD) epidemic, affecting over 20 asteroid species from Mexico to Alaska, the causative agent has been elusive. SSWD killed billions of the most susceptible species, sunflower sea stars (Pycnopodia helianthoides), initiating a trophic cascade involving unchecked urchin population growth and the widespread loss of kelp forests. Identifying the causative agent underpins the development of recovery strategies. Here we induced disease and subsequent mortality in exposure experiments using tissue extracts, coelomic fluid and effluent water from wasting sunflower sea stars, with no mortality in controls. Deep sequencing of diseased sea star coelomic fluid samples from experiments and field outbreaks revealed a dominant proportion of reads assigned to the bacterium Vibrio pectenicida. Fulfilling Koch’s postulates, V. pectenicida strain FHCF-3, cultured from the coelomic fluid of a diseased sunflower sea star, caused disease and mortality in exposed sunflower sea stars, demonstrating that it is a causative agent of SSWD. This discovery will enable recovery efforts for sea stars and the ecosystems affected by their decline by facilitating culture-based experimental research and broad-scale screening for pathogen presence and abundance in the laboratory and field.
","language":"English","publisher":"Nature","doi":"10.1038/s41559-025-02797-2","usgsCitation":"Prentice, M.B., Crandall, G., Chan, A.M., Davis, K.M., Hershberger, P., Finke, J.F., Hodin, J., McCracken, A., Kellogg, C.T., Carvalho, R., Prentice, C., Zhong, K.X., Harvell, D., Suttle, C.A., and Gehman, A.M., 2025, Vibrio pectenicida strain FHCF-3 is a causative agent of sea star wasting disease: Nature Ecology & Evolution, v. 9, p. 1739-1751, https://doi.org/10.1038/s41559-025-02797-2.","productDescription":"13 p.","startPage":"1739","endPage":"1751","ipdsId":"IP-174859","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":496267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2025-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Prentice, Melanie B.","contributorId":361921,"corporation":false,"usgs":false,"family":"Prentice","given":"Melanie","middleInitial":"B.","affiliations":[{"id":86390,"text":"The University of British Columbia, Vancouver, Canada; The Hakai Institute","active":true,"usgs":false}],"preferred":false,"id":949664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crandall, Grace","contributorId":361922,"corporation":false,"usgs":false,"family":"Crandall","given":"Grace","affiliations":[{"id":86393,"text":"University of Washington; Seattle, USA.","active":true,"usgs":false}],"preferred":false,"id":949665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chan, Amy M.","contributorId":361923,"corporation":false,"usgs":false,"family":"Chan","given":"Amy","middleInitial":"M.","affiliations":[{"id":86394,"text":"The University of British Columbia, Vancouver, Canada","active":true,"usgs":false}],"preferred":false,"id":949666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Katherine M.","contributorId":361924,"corporation":false,"usgs":false,"family":"Davis","given":"Katherine","middleInitial":"M.","affiliations":[{"id":86390,"text":"The University of British Columbia, Vancouver, Canada; 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Burlington, USA.","active":true,"usgs":false}],"preferred":false,"id":949671,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kellogg, Colleen T.","contributorId":361927,"corporation":false,"usgs":false,"family":"Kellogg","given":"Colleen","middleInitial":"T.","affiliations":[{"id":86396,"text":"The Hakai Institute; Campbell River, Canada.","active":true,"usgs":false}],"preferred":false,"id":949672,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carvalho, Rute","contributorId":361928,"corporation":false,"usgs":false,"family":"Carvalho","given":"Rute","affiliations":[{"id":86396,"text":"The Hakai Institute; Campbell River, Canada.","active":true,"usgs":false}],"preferred":false,"id":949673,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prentice, Carolyn","contributorId":361929,"corporation":false,"usgs":false,"family":"Prentice","given":"Carolyn","affiliations":[{"id":86396,"text":"The Hakai Institute; Campbell River, Canada.","active":true,"usgs":false}],"preferred":false,"id":949674,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zhong, Kevin X.","contributorId":361930,"corporation":false,"usgs":false,"family":"Zhong","given":"Kevin","middleInitial":"X.","affiliations":[{"id":86394,"text":"The University of British Columbia, Vancouver, Canada","active":true,"usgs":false}],"preferred":false,"id":949675,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Harvell, Drew","contributorId":149982,"corporation":false,"usgs":false,"family":"Harvell","given":"Drew","email":"","affiliations":[{"id":17869,"text":"Department of Ecology & Evolutionary Biology, Cornell University, Ithaca, NY 14853","active":true,"usgs":false}],"preferred":false,"id":949676,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Suttle, Curtis A.","contributorId":361931,"corporation":false,"usgs":false,"family":"Suttle","given":"Curtis","middleInitial":"A.","affiliations":[{"id":86394,"text":"The University of British Columbia, Vancouver, Canada","active":true,"usgs":false}],"preferred":false,"id":949677,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Gehman, Alyssa-Lois M.","contributorId":361932,"corporation":false,"usgs":false,"family":"Gehman","given":"Alyssa-Lois","middleInitial":"M.","affiliations":[{"id":86390,"text":"The University of British Columbia, Vancouver, Canada; The Hakai Institute","active":true,"usgs":false}],"preferred":false,"id":949678,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70271149,"text":"70271149 - 2025 - Three decades of declines restructure butterfly communities in the Midwestern United States","interactions":[],"lastModifiedDate":"2025-08-29T13:36:55.913684","indexId":"70271149","displayToPublicDate":"2025-08-04T08:31:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Three decades of declines restructure butterfly communities in the Midwestern United States","docAbstract":"Insects are declining worldwide, yet gaps remain in our understanding of how declines are distributed across species within communities. Using three decades of butterfly monitoring data aggregated from the Midwestern United States, we found that no butterfly species increased in abundance from 1992 to 2023. 59 out of 136 species declined (annual mean trend: −1.2 to −6.9% per year) with losses distributed across all functional groups including residents, migrants, rare, and common species. Community composition changed such that abundance is now more even across species, driven by more severe losses in abundance—but not richness—of common species compared to rare species. These widespread declines are likely cascading across ecosystems. Conservation efforts that focus on entire communities could mitigate butterfly biodiversity loss.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2501340122","usgsCitation":"Leuenberger, W., Doser, J.W., Belitz, M.W., Ries, L., Haddad, N.M., Thogmartin, W.E., and Zipkin, E.F., 2025, Three decades of declines restructure butterfly communities in the Midwestern United States: PNAS, v. 122, no. 33, e2501340122, 8 p., https://doi.org/10.1073/pnas.2501340122.","productDescription":"e2501340122, 8 p.","ipdsId":"IP-173907","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":495176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2501340122","text":"Publisher Index Page"},{"id":495078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, 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\"}}]}","volume":"122","issue":"33","noUsgsAuthors":false,"publicationDate":"2025-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Leuenberger, Wendy","contributorId":352549,"corporation":false,"usgs":false,"family":"Leuenberger","given":"Wendy","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":947588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doser, Jeffrey W.","contributorId":360759,"corporation":false,"usgs":false,"family":"Doser","given":"Jeffrey","middleInitial":"W.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":947589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Michael W.","contributorId":360761,"corporation":false,"usgs":false,"family":"Belitz","given":"Michael","middleInitial":"W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":947590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ries, Leslie","contributorId":231062,"corporation":false,"usgs":false,"family":"Ries","given":"Leslie","affiliations":[{"id":38074,"text":"Univ. of Maryland","active":true,"usgs":false}],"preferred":false,"id":947591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haddad, Nick M.","contributorId":360764,"corporation":false,"usgs":false,"family":"Haddad","given":"Nick","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":947592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":947593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zipkin, Elise F.","contributorId":360766,"corporation":false,"usgs":false,"family":"Zipkin","given":"Elise","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":947594,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270312,"text":"70270312 - 2025 - Sea star wasting disease mystery finally solved","interactions":[],"lastModifiedDate":"2025-09-09T14:58:09.330382","indexId":"70270312","displayToPublicDate":"2025-08-04T08:04:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Sea star wasting disease mystery finally solved","docAbstract":"A decade after a marine epidemic killed off sea stars and triggered ecosystem-wide effects along the Pacific Coast of North America, researchers have identified the bacterial pathogen that is responsible for sea star wasting disease.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41559-025-02789-2","usgsCitation":"Lafferty, K.D., 2025, Sea star wasting disease mystery finally solved: Nature Ecology and Evolution, v. 9, p. 1552-1553, https://doi.org/10.1038/s41559-025-02789-2.","productDescription":"2 p.","startPage":"1552","endPage":"1553","ipdsId":"IP-179119","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":494099,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2025-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":945996,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70270065,"text":"70270065 - 2025 - Coral restoration can drive rapid increases in reef accretion potential","interactions":[],"lastModifiedDate":"2025-08-08T14:51:53.917168","indexId":"70270065","displayToPublicDate":"2025-08-04T07:46:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Coral restoration can drive rapid increases in reef accretion potential","docAbstract":"Coral-reef degradation is disrupting the balance between reef accretion and erosion and threatening the persistence of essential coral-reef habitats. In south Florida, most reefs are already net eroding, and without intervention, valuable ecosystem services may be lost. Coral restoration holds the potential to reverse those trends; however, typical restoration monitoring does not adequately capture key geo-ecological functions. We addressed this knowledge gap using carbonate budgets and Structure-from-Motion models to evaluate the impact of coral restoration on reef-accretion potential and structural complexity at eight offshore and three inshore coral reefs in the Lower Florida Keys. Within 2–6 years following outplanting, restoration of rapidly growing A. cervicornis populations increased reef-accretion potential to 2.8 mm y− 1 and drove significant increases in structural complexity. There was no measurable impact of restoring slower-growing, massive corals on reef-accretion potential inshore; however, whereas the severe 2023 coral-bleaching event immediately following our study caused near-complete mortality of A. cervicornis, 59% of massive corals survived, highlighting potential trade-offs between coral growth and survival on future restoration efficacy. We conclude that although restoration can produce rapid, small-scale increases in reef-accretion potential, there remain important uncertainties about how and whether ecosystem-scale benefits of restoration on important geo-ecological reef functions can persist long term.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-04818-3","usgsCitation":"Toth, L., Johnson, S.A., Lyons, E.O., Spadaro, J., Stathakopoulos, A., Bloomer, S., Mallon, J., Jenkins, C., Williams, S., Combs, I., Craig, Z., and Muller, E., 2025, Coral restoration can drive rapid increases in reef accretion potential: Scientific Reports, v. 15, 28353, 15 p., https://doi.org/10.1038/s41598-025-04818-3.","productDescription":"28353, 15 p.","ipdsId":"IP-176248","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":494441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-04818-3","text":"Publisher Index Page"},{"id":493839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Florida","otherGeospatial":"south Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.6585939793311,\n 25.015548783169194\n ],\n [\n -81.6585939793311,\n 24.57435107315807\n ],\n [\n -80.43635167922672,\n 24.57435107315807\n ],\n [\n -80.43635167922672,\n 25.015548783169194\n ],\n [\n -81.6585939793311,\n 25.015548783169194\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Selena Anne-Marie 0000-0003-1015-1788","orcid":"https://orcid.org/0000-0003-1015-1788","contributorId":296373,"corporation":false,"usgs":true,"family":"Johnson","given":"Selena","email":"","middleInitial":"Anne-Marie","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, Erin O. 0000-0001-9829-6476","orcid":"https://orcid.org/0000-0001-9829-6476","contributorId":316708,"corporation":false,"usgs":true,"family":"Lyons","given":"Erin","email":"","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spadaro, Jason","contributorId":359407,"corporation":false,"usgs":false,"family":"Spadaro","given":"Jason","affiliations":[{"id":13147,"text":"Mote Marine 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threats: Habitat degradation from channel narrowing and invasive vegetation in three dryland rivers","interactions":[],"lastModifiedDate":"2026-02-20T22:23:05.443123","indexId":"70274016","displayToPublicDate":"2025-08-02T15:17:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Shrinking channels, growing threats: Habitat degradation from channel narrowing and invasive vegetation in three dryland rivers","docAbstract":"Water development and the proliferation of invasive riparian vegetation have led to widespread habitat loss and simplification of rivers in the western United States, contributing to the imperilment of native fishes. Here, we quantify channel narrowing and vegetation encroachment, which are conspicuous indicators of riverine habitat alteration, along ∼400 km of three dryland tributaries of the upper Colorado River. We conducted a comparative analysis of aerial photographs between the 1930s and 2010s/2020s time periods using visual interpretation and used Light Detection and Ranging (LiDAR) data along with Object-Based Image Analysis (OBIA) to quantify canopy cover of woody riparian species. All three rivers underwent substantial channel narrowing, coinciding with a general decrease in spring floods over time. However, the extent of narrowing varied among the rivers (78 %, 73 %, and 29 %) with greater narrowing corresponding to larger reductions in spring flows. In contrast, contemporary woody cover was similarly high among all three rivers (39 %, 41 %, and 36 %), and a woody vegetation analysis we conducted for one river indicated a substantial increase in vegetation along the active channel (4 %–74 %). These findings underscore a common pattern observed in rivers throughout the basin, where river channels often undergo narrowing and encroachment by invasive vegetation following dam construction and/or decreases in flows, ultimately leading to habitat simplification, with negative implications for native fishes and other riparian biota. Our findings also emphasize that, even in the presence of nonnative vegetation establishment, preserving or restoring large magnitude and long duration floods can help conserve diverse habitat in dryland rivers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.126714","usgsCitation":"Miller, B.J., McKinstry, M.C., Wilcock, P.R., Macfarlane, W.W., Bassett, S., Budy, P., Pennock, C.A., 2025, Shrinking channels, growing threats: Habitat degradation from channel narrowing and invasive vegetation in three dryland rivers: Journal of Environmental Management, v. 392, 126714, 12 p., https://doi.org/10.1016/j.jenvman.2025.126714.","productDescription":"126714, 12 p.","ipdsId":"IP-180680","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.20458933342701,\n 37.628183776979654\n ],\n [\n -111.20458933342701,\n 36.4333212502403\n ],\n [\n -107.18146321534954,\n 36.4333212502403\n ],\n [\n -107.18146321534954,\n 37.628183776979654\n ],\n [\n -111.20458933342701,\n 37.628183776979654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Benjamin J. 0009-0009-8097-0763","orcid":"https://orcid.org/0009-0009-8097-0763","contributorId":366731,"corporation":false,"usgs":false,"family":"Miller","given":"Benjamin","middleInitial":"J.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":956170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinstry, Mark C.","contributorId":366732,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","middleInitial":"C.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":956171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilcock, Peter R.","contributorId":366733,"corporation":false,"usgs":false,"family":"Wilcock","given":"Peter","middleInitial":"R.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":956172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Macfarlane, William W.","contributorId":366734,"corporation":false,"usgs":false,"family":"Macfarlane","given":"William","middleInitial":"W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":956173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bassett, Steven 0000-0002-3826-3960","orcid":"https://orcid.org/0000-0002-3826-3960","contributorId":211628,"corporation":false,"usgs":false,"family":"Bassett","given":"Steven","affiliations":[{"id":38280,"text":"The Nature Conservancy, Minneapolis MN","active":true,"usgs":false}],"preferred":false,"id":956174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":956175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pennock, Casey A.","contributorId":366745,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey","middleInitial":"A.","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":956176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269796,"text":"sir20255065 - 2025 - Analysis of summer water temperatures of the lower Virgin River near Mesquite, Nevada, 2019–21","interactions":[],"lastModifiedDate":"2026-02-03T14:42:44.427211","indexId":"sir20255065","displayToPublicDate":"2025-08-01T13:50:56","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5065","displayTitle":"Analysis of Summer Water Temperatures of the Lower Virgin River Near Mesquite, Nevada, 2019–21","title":"Analysis of summer water temperatures of the lower Virgin River near Mesquite, Nevada, 2019–21","docAbstract":"The lower Virgin River is a sandy, shallow reach of the Virgin River that flows from northern Arizona to Lake Mead in Nevada. The Virgin River hosts several native fish species, including two endangered fish, woundfin (Plagopterus argentissimu) and Virgin River chub (Gila seminuda). All native fish species in the lower Virgin River have experienced reductions in population sizes in the last several decades. Reduced stream flow (especially during summer low-flow conditions) often results in increased water temperatures, which can increase mortality, reduce breeding, limit population connectivity, and favor non-native fish species. This study investigated summer water temperatures and flow in the lower Virgin River near Mesquite, Nev., between Littlefield, Ariz., and Bunkerville, Nev., to evaluate how hydrologic conditions could be affecting native fish species. The 3-year monitoring project involved collection of continuous temperature and discrete discharge measurements at 15 sites from 2019 to 2021 during the summer months from June to September. Results indicate that the lower Virgin River is often greater than 5 degrees Celsius (°C) above the established critical thermal maximum of 31 °C, that the cooling effect of the Littlefield springs dissipates quickly downstream, and that water temperature is affected primarily by atmospheric conditions. Discharge and water temperature are poorly related at normal stable flow conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255065","collaboration":"Prepared in cooperation with the Bureau of Land Management and Nevada Department of Wildlife","usgsCitation":"Earp, K.J., 2025, Analysis of summer water temperatures of the lower Virgin River near Mesquite, Nevada, 2019–21: U.S. Geological Survey Scientific Investigations Report 2025–5065, 23 p., https://doi.org/10.3133/sir20255065.","productDescription":"viii, 23 p.","onlineOnly":"Y","ipdsId":"IP-104326","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":493355,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5065/sir20255065.XML"},{"id":493352,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5065/sir20255065.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5065"},{"id":493351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5065/coverthb.jpg"},{"id":493354,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5065/images"},{"id":493353,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255065/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5065"}],"country":"United States","state":"Arizona, Nevada","city":"Mesquite","otherGeospatial":"lower Virgin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.89637038515828,\n 36.91617741482898\n ],\n [\n -114.22669808506164,\n 36.80414574994599\n ],\n [\n -114.25778641886733,\n 36.70566397893374\n ],\n [\n -113.95393733380085,\n 36.75799180706565\n ],\n [\n -113.89637038515828,\n 36.91617741482898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road, Suite 3
Carson City, Nevada 89701
No abstract available.
","largerWorkTitle":"State of the climate in 2024: Global climate","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-25-0102.1","usgsCitation":"Harlan, M.E., Meyer, M.F., Levenson, E.S., Cooley, S., and Kraemer, B.M., 2025, Lake water storage and level, chap. of State of the climate in 2024: Global climate, v. 106, p. 70-71, https://doi.org/10.1175/BAMS-D-25-0102.1.","productDescription":"2 p.","startPage":"70","endPage":"71","ipdsId":"IP-176782","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":500840,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-05385776","text":"External Repository"},{"id":500653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harlan, Merritt Elizabeth 0000-0002-4019-4888","orcid":"https://orcid.org/0000-0002-4019-4888","contributorId":302672,"corporation":false,"usgs":true,"family":"Harlan","given":"Merritt","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":950640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Michael Frederick 0000-0002-8034-9434 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8034-9434","contributorId":304191,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"Frederick","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":950641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levenson, Eric S. 0000-0002-0615-0160","orcid":"https://orcid.org/0000-0002-0615-0160","contributorId":362612,"corporation":false,"usgs":false,"family":"Levenson","given":"Eric","middleInitial":"S.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":950642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooley, Sarah","contributorId":349565,"corporation":false,"usgs":false,"family":"Cooley","given":"Sarah","affiliations":[],"preferred":false,"id":950643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraemer, Benjamin M. 0000-0002-3390-9005","orcid":"https://orcid.org/0000-0002-3390-9005","contributorId":360959,"corporation":false,"usgs":false,"family":"Kraemer","given":"Benjamin","middleInitial":"M.","affiliations":[{"id":33350,"text":"University of Freiburg","active":true,"usgs":false}],"preferred":false,"id":950644,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273115,"text":"70273115 - 2025 - Variable partitioning of lithium in rhyolitic melt during decompression and ascent","interactions":[],"lastModifiedDate":"2025-12-16T15:54:26.382187","indexId":"70273115","displayToPublicDate":"2025-08-01T09:48:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Variable partitioning of lithium in rhyolitic melt during decompression and ascent","docAbstract":"The partitioning behavior of Li in magmatic systems is increasingly being investigated due to the economic importance of Li in the transition to sustainable energy resources (e.g., batteries). However, at upper crustal pressures, it remains uncertain whether Li preferentially partitions into the vapor or liquid (brine) phase or remains in the silicate melt. This complicates our ability to determine where Li resides—silicate melt, minerals, or fluid phase—upon eruption, a crucial factor for understanding its postdepositional movement and concentration into a brine or volcano-sedimentary deposit. Here, we present a novel investigation into the behavior of Li within natural evolved melts during continuous magma decompression and ascent using melt embayments (open melt inclusions). Mineral-hosted melt embayments preserve records of the evolving composition of the exterior melt, including degassing pathways and ascent timescales, when paired with appropriate diffusion coefficients. Lithium concentration profiles were measured in quartz-hosted melt embayments from the rapidly quenched eruptive phases of five rhyolitic, caldera-forming eruptions to investigate the behavior of Li during magma decompression and ascent, where vapor partitioning and ascent dynamics were previously established by investigating H2O and CO2 profiles. We find that in four systems, embayments contain lower interior Li concentrations than the coerupted melt inclusions; the fifth system contains the same Li concentrations in embayments and melt inclusions. However, many of these embayments contain gradients, with 84% preserving Li enrichment near the melt-bubble interface, as compared to their interior concentration. We interpret these characteristics to represent two distinct stages of Li partitioning during magma decompression and ascent, in contrast to existing literature that proposes only one type of partitioning behavior. The first stage is interpreted as melt depletion of Li, likely driven by partitioning into an exsolved supercritical fluid phase, supported by the strong correlation between the extent of Li depletion and Cl concentration in the melt, as well as the decompression rate. This behavior then fundamentally shifts, where Li reenriches in the melt, postulated to be driven by the unmixing of the supercritical fluid phase at shallow pressures. For the one system that did not develop Li gradients through decompression, we attribute this to the lower values of Na and Cl in the melt, potentially inhibiting the partitioning of Li into a fluid phase. Importantly, the behavior of Li during decompression is not consistent within or between volcanic centers, highlighting the need for systematic experimental investigation in variable composition melts at pressures relevant to conduit dynamics. This knowledge would improve our ability to model Li profiles to understand magma decompression, and predict where Li resides (e.g., stored in volcanic glass, gas, or crystals) upon eruption prior to any later extraction.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.5171","usgsCitation":"Myers, M., Spallanzani, R., Schwartz, D., Mercer, C.N., and Hosseini, B., 2025, Variable partitioning of lithium in rhyolitic melt during decompression and ascent: Economic Geology, v. 120, no. 5, p. 1191-1206, https://doi.org/10.5382/econgeo.5171.","productDescription":"16 p.","startPage":"1191","endPage":"1206","ipdsId":"IP-169836","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.5171","text":"Publisher Index Page"},{"id":497573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Madison 0000-0003-2271-4445","orcid":"https://orcid.org/0000-0003-2271-4445","contributorId":331812,"corporation":false,"usgs":false,"family":"Myers","given":"Madison","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":952376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spallanzani, Roberta","contributorId":364231,"corporation":false,"usgs":false,"family":"Spallanzani","given":"Roberta","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":952377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, Darin","contributorId":364233,"corporation":false,"usgs":false,"family":"Schwartz","given":"Darin","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":952378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":952379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hosseini, Behnaz","contributorId":364237,"corporation":false,"usgs":false,"family":"Hosseini","given":"Behnaz","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":952380,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269827,"text":"70269827 - 2025 - Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows","interactions":[],"lastModifiedDate":"2025-08-18T15:24:32.344447","indexId":"70269827","displayToPublicDate":"2025-08-01T09:34:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1728,"text":"GSA Today","active":true,"publicationSubtype":{"id":10}},"title":"Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows","docAbstract":"In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG611A.1","usgsCitation":"Rengers, F.K., Kean, J.W., Williams, C.A., Henneberg, M.F., Banta, J.R., Schroder, E., Sponaugle, C., Callery, D., Walter, E., Blake, T., and Staley, D.M., 2025, Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows: GSA Today, v. 35, no. 8, p. 16-21, https://doi.org/10.1130/GSATG611A.1.","productDescription":"6 p.","startPage":"16","endPage":"21","ipdsId":"IP-168644","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494429,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/gsatg611a.1","text":"Publisher Index Page"},{"id":493567,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Glenwood Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.3,\n 39.5167\n ],\n [\n -107.0833,\n 39.5167\n ],\n [\n -107.0833,\n 39.6667\n ],\n [\n -107.3,\n 39.6667\n ],\n [\n -107.3,\n 39.5167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science 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0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":187481,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banta, John R. 0000-0002-2226-7270","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":222710,"corporation":false,"usgs":true,"family":"Banta","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schroder, Eric 0000-0002-3902-2704","orcid":"https://orcid.org/0000-0002-3902-2704","contributorId":358993,"corporation":false,"usgs":false,"family":"Schroder","given":"Eric","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":944738,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sponaugle, Cara","contributorId":358994,"corporation":false,"usgs":false,"family":"Sponaugle","given":"Cara","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":944739,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Callery, David","contributorId":358996,"corporation":false,"usgs":false,"family":"Callery","given":"David","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":944740,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walter, Erin 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statistics at ungaged locations in New York, excluding Long Island","docAbstract":"Models to estimate low-streamflow statistics at ungaged locations in New York, excluding Long Island and including hydrologically connected basins from bordering States, were developed for the first time by the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation. A total of 224 basin characteristics were developed for 213 unaltered streamgages (locations where the human effects on streamflow were limited), across the following categories: basin geometry, climate, land cover, soils, surficial geology, and other characteristics. The basins with unaltered streamgages were evaluated for potential redundancy, and streamgages in close proximity and with similar drainage areas were flagged and removed from the testing and cross-validation datasets to prevent data leaking from the training dataset to the testing dataset.
Random forest regression models were created by using basin characteristics as predictor variables and by developing a workflow to train, tune, and test the model. Models were developed to estimate the ungaged lowest annual 7-day and 30-day average streamflow that occurs (on average) once every 10 years (7Q10 and 30Q10). The top four basin characteristics used for the 7Q10 and 30Q10 models were drainage area, total stream length, perimeter of the basin, and length of the longest flow path. Results for the 7Q10 and 30Q10 models had coefficients of determination (R2) of 0.796 and 0.853, respectively. The output model results were bias-corrected for ungaged locations across New York and are available within the interactive StreamStats tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255060","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Stagnitta, T.J., Woda, J.C., and Graziano, A.P., 2025, Random forest regression models for estimating low-streamflow statistics at ungaged locations in New York, excluding Long Island: U.S. Geological Survey Scientific Investigations Report 2025–5060, 23 p., https://doi.org/10.3133/sir20255060.","productDescription":"Report: v, 23 p.; 2 Data Releases","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167540","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":492987,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P146MTRS","text":"USGS data release","linkHelpText":"Random forest regression model archive for estimating low-streamflow statistics at ungaged locations in New York, excluding Long Island"},{"id":492986,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NOM6FR","text":"USGS data release","linkHelpText":"Low-flow statistics for New York State, excluding Long Island, computed through March 2022"},{"id":492985,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5060/images/"},{"id":492988,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245055","text":"Scientific Investigations Report 2024–5055","linkHelpText":"- Low-Flow Statistics for Selected Streams in New York, Excluding Long Island"},{"id":492984,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5060/sir20255060.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5060 XML"},{"id":492983,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255060/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5060 HTML"},{"id":492981,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5060/coverthb.jpg"},{"id":492982,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5060/sir20255060.pdf","text":"Report","size":"8.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5060 PDF"},{"id":492989,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://streamstats.usgs.gov/ss/","text":"StreamStats"}],"country":"United States","state":"New York","otherGeospatial":"New York excluding Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.8668360740237,\n 40.82174116460561\n ],\n [\n -73.64101370770591,\n 40.97341618058218\n ],\n [\n -73.641675229166,\n 41.369110620239354\n ],\n [\n -73.44442715633755,\n 41.42737341824312\n ],\n [\n -73.23400688811246,\n 42.735562128301694\n ],\n [\n -73.28689303884832,\n 45.063167069767246\n ],\n [\n -74.92263898531354,\n 45.049241271408505\n ],\n [\n -76.59790269295956,\n 44.152600935032865\n ],\n [\n -76.27472597825448,\n 43.63979148650773\n ],\n [\n -76.9594903941915,\n 43.33322253590592\n ],\n [\n -78.50182350844328,\n 43.459456447836146\n ],\n [\n -79.39789785747713,\n 43.19859290777666\n ],\n [\n -78.90328998597391,\n 42.86522759603616\n ],\n [\n -79.82520290314585,\n 42.24436339597355\n ],\n [\n -79.76467975802953,\n 41.964093469327736\n ],\n [\n -75.37056382699097,\n 42.00382656329654\n ],\n [\n -74.98586389700988,\n 41.54435731278656\n ],\n [\n -73.999903714982,\n 41.001270702844295\n ],\n [\n -73.96336292917533,\n 40.82357491793678\n ],\n [\n -73.8668360740237,\n 40.82174116460561\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349