The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNdi = ‐2.2 ± 0.8) and zircon Lu-Hf (εHfi = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHfi in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2025.108060","usgsCitation":"Benson, E.K., Watts, K., and Hillenbrand, I.W., 2025, Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California: LITHOS, v. 508-509, 108060, 18 p., https://doi.org/10.1016/j.lithos.2025.108060.","productDescription":"108060, 18 p.","ipdsId":"IP-173126","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.lithos.2025.108060","text":"Publisher Index Page"},{"id":484582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.29333455287775,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 36.19312110709426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"508-509","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265433,"text":"fs20243051 - 2025 - Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023","interactions":[],"lastModifiedDate":"2025-08-07T20:41:25.073086","indexId":"fs20243051","displayToPublicDate":"2025-04-09T11:40:00","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":"2024-3051","displayTitle":"Assessment of Undiscovered Oil and Gas Resources of the Los Angeles Basin Province, 2023","title":"Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 61 million barrels of oil and 240 billion cubic feet of gas in the Los Angeles Basin Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243051","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Tennyson, M.E., Mercier, T.J., Le, P.A., Cicero, A.D., Drake, R.M., II, Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., and Timm, K.K., 2025, Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023: U.S. Geological Survey Fact Sheet 2024–3051, 4 p., https://doi.org/10.3133/fs20243051.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-157105","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":493748,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118519.htm","linkFileType":{"id":5,"text":"html"}},{"id":484350,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3051/images"},{"id":484349,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P148FWYT","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Los Angeles Basin Province: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":484393,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243051/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3051"},{"id":484351,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3051/fs20243051.xml"},{"id":484194,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3051/coverthb.jpg"},{"id":484195,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3051/fs20243051.pdf","text":"Report","size":"720 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3051"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.46009478730042,\n 33.23344855361785\n ],\n [\n -117.32296349710847,\n 34.45004669658452\n ],\n [\n -118.16445095964868,\n 34.54765057900826\n ],\n [\n -118.9934719412617,\n 34.38834329310062\n ],\n [\n -119.62926246851423,\n 34.37291032933257\n ],\n [\n -120.4458169692015,\n 34.44490648556631\n ],\n [\n -120.67021362587857,\n 34.45004669658452\n ],\n [\n -119.3736996095206,\n 34.151392287418204\n ],\n [\n -118.6007777920766,\n 33.84650135234095\n ],\n [\n -118.17691744057491,\n 33.58207150936819\n ],\n [\n -117.46009478730042,\n 33.23344855361785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
We investigated how visitors to federal, state, and local parks and protected areas (PPAs) respond to weather and air quality conditions in the Pacific Northwest (PNW), United States. Specifically, we modeled the relationship between weekly visitation and mean weekly minimum and maximum temperature, precipitation, Air Quality Index (AQI), and particulate matter 2.5 concentration (PM2.5, often used as an indicator of wildfire smoke) during an extended peak visitation season from 2017 to 2021 in 91 PNW PPAs. We used mobile device data from StreetLight Data Inc. to estimate weekly vehicular visitation. Our findings indicate that increasing precipitation corresponded with decreased weekly visitation to all three types of PPAs and rising minimum temperatures corresponded with increased visitation. We found that rising maximum temperatures corresponded with increased visitation in federal and local PPAs, but corresponded with decreased visitation in local PPAs once temperatures reach a maximum threshold. We did not observe a maximum threshold effect in federal or state settings. Further, we found that the effect of air quality and smoke on visitation varies based on the metric used: increased PM2.5 concentrations (possibly indicating the presence of wildfire smoke) in federal and local PPAs corresponded with decreased visitation, while increased AQI in federal PPAs corresponded with increased visitation. These findings indicate that visitors may respond differently to different types of air pollution. Our results have implications for adapting peak- and shoulder- season visitor use management to current and future climate change within and beyond PPAs of the PNW.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pclm.0000537","usgsCitation":"Minehart, K., D'Antonio, A., and Wilkins, E.J., 2025, The mountains are calling, but will visitors go? 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\"}}]}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Minehart, Kira 0009-0006-6007-0782","orcid":"https://orcid.org/0009-0006-6007-0782","contributorId":353124,"corporation":false,"usgs":false,"family":"Minehart","given":"Kira","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Antonio, Ashley","contributorId":353127,"corporation":false,"usgs":false,"family":"D'Antonio","given":"Ashley","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkins, Emily J. 0000-0003-3055-4808","orcid":"https://orcid.org/0000-0003-3055-4808","contributorId":328409,"corporation":false,"usgs":true,"family":"Wilkins","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":933008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265511,"text":"sir20255026 - 2025 - Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey","interactions":[],"lastModifiedDate":"2025-08-07T20:39:55.109963","indexId":"sir20255026","displayToPublicDate":"2025-04-09T10:00:00","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":"2025-5026","displayTitle":"Time of Travel of Releases From Lake Wallenpaupack to the U.S. Geological Survey’s Streamgage Monitoring Location on the Delaware River at Montague, New Jersey","title":"Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey","docAbstract":"In 2016, the U.S. Geological Survey (USGS) carried out a hydraulic study within the upper Delaware River Basin for the purpose of determining the time of travel for water releases from the Brookfield Renewable U.S. hydroelectric plant at Lake Wallenpaupack, Pennsylvania, to reach the USGS streamgage located on the Delaware River at Montague, New Jersey (site number 01438500). From September 19 to October 14, 2016, Brookfield Renewable initiated repeated releases of approximately 650 cubic feet per second (ft3/s) and 1,440 ft3/s. Hydraulic signals from the releases were tracked at nine key locations between Lake Wallenpaupack and the USGS streamgage at Montague, New Jersey (01438500). Gage height data were recorded at streamgages at major confluences of the Lackawaxen and Delaware Rivers, Mongaup and Delaware Rivers, and the Neversink and Delaware Rivers. The time of travel to the USGS streamgage at Montague, New Jersey, was determined to be 1,185 minutes during the approximately 650 ft3/s releases and 960 minutes during the approximately 1,440 ft3/s releases. Elevated streamflow between Lake Wallenpaupack and the Montague streamgage from runoff events prior to the dam releases was found to decrease calculated time of travel identified during the study. The results from this study can be used as a guide to estimate time of travel while considering the water level of downstream streamflow, the volume of water being released, and other outside influences, such as precipitation and snowmelt.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255026","collaboration":"Prepared in cooperation with the Office of the Delaware River Master","usgsCitation":"Polcino, J., Trainor, J.J., and Collenburg, J.V., 2025, Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey: U.S. Geological Survey Scientific Investigations Report 2025–5026, 20 p., https://doi.org/10.3133/sir20255026.","productDescription":"vii, 20 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150895","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":484348,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5026/images/"},{"id":484347,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5026/sir20255026.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5026 XML"},{"id":484346,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255026/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5026 HTML"},{"id":484345,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5026/sir20255026.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5026 PDF"},{"id":484344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5026/coverthb.jpg"},{"id":493747,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118518.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River, Lake Wallenpaupack","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.28276534144987,\n 41.608544510962616\n ],\n [\n -75.28276534144987,\n 41.13145977502657\n ],\n [\n -74.30523052576332,\n 41.13145977502657\n ],\n [\n -74.30523052576332,\n 41.608544510962616\n ],\n [\n -75.28276534144987,\n 41.608544510962616\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The impoundment of Lake Conroe in 1973 created an important water resource for greater Houston, Texas. The U.S. Geological Survey, in cooperation with the San Jacinto River Authority, analyzed water-quality data collected from 1974 to 2021 at upreservoir, mid-reservoir, and downreservoir sites in Lake Conroe. Water-column and seasonal variability of selected water-quality constituents (physiochemical properties, major ions, nutrients, and trace metals) were assessed, as well as thermal stratification. Water-quality trends were evaluated for 1974–2021 and 1993–2021.
Near-surface water (1–3 feet below the water surface) was warmer and contained higher dissolved-oxygen concentrations compared to near-bottom water (2–3 feet above the reservoir bottom). Dissolved-oxygen concentrations were lowest in summer and highest in winter. Specific conductance was higher near the bottom and varied seasonally, being lowest in winter and highest in summer. Values of pH were generally higher at the surface, with some variability between sites and seasons. Water transparency was higher downreservoir and seasonally lowest in summer.
Major-ion concentrations varied minimally within the water column and seasonally, except for sulfate, which was higher in winter and lower in summer. Most nutrient and trace metal concentrations were highest near the bottom during summer, notably at deeper sites. Thermal stratification in Lake Conroe begins in spring and peaks in summer and was limited to the deeper parts of the reservoir. The seasonal variability observed in dissolved constituent concentrations was driven by thermal stratification. Trend analyses for 1974–2021 indicated positive trends in water temperature, dissolved oxygen, pH, potassium, sodium, and silica. Negative trends were detected for calcium and magnesium near the reservoir bottom. During 1993–2021, positive trends were detected for near-surface dissolved-oxygen concentration, specific conductance, pH, all major ions excluding sulfate, and near-surface ammonia plus organic nitrogen concentration. Negative trends were determined for ammonia, iron, and manganese concentrations. Water transparency generally decreased over time.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"We present major and trace element whole-rock geochemistry of 94 samples from the Bronson Hill arc (BHA) and Connecticut Valley–Gaspé trough (CVGT). These data, when combined with recent zircon U-Pb geochronology and a reexamination of existing whole-rock geochemistry, enable a new analysis of the tectonic history of the ancient Laurentian-Ganderian margin in the northern Appalachians of New England, USA, and southeastern Canada. The whole-rock geochemical data from the Ordovician BHA in western New Hampshire indicate that metamorphosed extrusive and intrusive rocks share the same temporally variable geochemical fingerprint. Mafic and felsic rocks form a bimodal distribution and plot as island arc magmas on geochemical discrimination diagrams. Approximately 80% of mafic greenstone and amphibolite samples plot as island arc tholeiites with a subset of samples that trend toward a more within-plate basalt geochemical signature. Where ages are known, older felsic rocks (ca. 475–460 Ma) in the BHA tend to be more sodic and less potassic than their younger (ca. 460–445 Ma) counterparts, and the geochemical results trend from volcanic arc granites toward syn-collisional granites through time. Prior to recent geochronology, it was thought that an age gap existed between the island arc magmas and the syn collisional granites. This led to the separation of felsic plutons into the predominantly older trondhjemitic magmas assigned to the Ammonoosuc Volcanics and a younger suite of granites designated as the Oliverian Plutonic Suite. This age gap was thought to represent a flip in subduction polarity which would also account for observed changes in pluton chemistry. With the addition of more recent U-Pb isotopic age data, we now know there is a continuum of ages, and a polarity flip is no longer required. When the isotopic ages are combined with the new geochemical data presented here, they suggest that as the BHA approached and collided with Laurentia ca. 455 Ma, continental material was assimilated into the magma, and there was a transition from trondhjemite to granodiorite and granite magmas in felsic rocks and from island arc tholeiite toward more alkali-rich basalt with a continental signature in mafic magmas. The similarities in whole-rock and trace element geochemistry, rock type, and range of isotopic ages from the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic Suite, suggest they originated from the same magma source and were part of one evolving island arc system that persisted throughout the Ordovician, and the need to separate the Oliverian Plutonic Suite from the Ammonoosuc Volcanics is not necessary.
Most magmatism in the BHA ceased ca. 440 Ma. Following the Taconic orogeny, Silurian basin development was widespread along the length of the Laurentian-Ganderian suture. In New England and Québec, this resulted in the formation of the CVGT. The BHA and the CVGT are generally studied separately: the BHA in the context of arc-continent collision during the Taconic orogeny, and the CVGT as it relates to post-orogenic extension or the distal effects of the Salinic disturbance. When viewed collectively, the igneous geochemistry of the BHA and CVGT reveals an overlap between the waning stages of Taconic orogenesis and the onset of Silurian to Devonian basin development in the northern Appalachians. Metamorphosed bimodal volcanic and intrusive rocks are present in the CVGT (ca. 434–407 Ma) and Silurian cover sequence, which unconformably overlies the BHA. Mafic rocks in the CVGT are mostly tholeiitic basalts with a subset of alkali basalt in the Waits River Formation. Tectonic discrimination diagrams show that the mafic rocks are a mix of mid-ocean ridge basalt to within-plate basalt. The felsic rocks in the CVGT are mostly metamorphosed volcanic rocks that vary from island arc granite to within-plate granite. The geochemical signature of the CVGT is consistent with a post-collisional intra-arc basin, where slab breakoff or crustal attenuation played a key role before transitioning to a deepening foreland basin at the beginning of the Acadian orogeny.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02768.1","usgsCitation":"Valley, P.M., Walsh, G., Merschat, A.J., and McAleer, R.J., 2025, Geochemical and tectonic evolution of the Ordovician Bronson Hill arc and Silurian and Devonian Connecticut Valley–Gaspé trough: Eastern Vermont and western New Hampshire, USA: Geosphere, v. 21, no. 3, p. 418-445, https://doi.org/10.1130/GES02768.1.","productDescription":"28 p.","startPage":"418","endPage":"445","ipdsId":"IP-158690","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":490653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02768.1","text":"Publisher Index Page"},{"id":489369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.625,\n 43.75\n ],\n [\n -72.625,\n 43.125\n ],\n [\n -72.125,\n 43.125\n ],\n [\n -72.125,\n 43.75\n ],\n [\n -72.625,\n 43.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":938935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":265307,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":938936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":938937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":938938,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265600,"text":"70265600 - 2025 - Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","interactions":[],"lastModifiedDate":"2025-11-18T16:42:55.698486","indexId":"70265600","displayToPublicDate":"2025-04-09T08:20:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5984,"text":"Reviews in Fisheries Science and Aquaculture","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","title":"Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","docAbstract":"ulturally, economically, and nutritionally valuable inland fisheries face many new challenges on top of chronic disturbances. In the upper midwestern United States, declines in cool- and coldwater fisheries have been observed, including ogaa/walleye Sander vitreus. In response to population declines, agencies have implemented rehabilitation efforts, and the frequency and intensity of efforts have increased recently given declines. Evaluating intervention outcomes is critical for institutional learning and to understand strategy effectiveness, but is difficult to do when multiple interventions are applied concurrently and in the absence of replication or controls. This review documents walleye rehabilitation efforts in the upper Midwest U.S., where a rehabilitation effort was defined as a coordinated effort with the stated intention to restore a self-sustaining population such that it required limited-to-no further intervention. We discuss: (1) strategies used; (2) similarities and differences in metrics of success; (3) factors leading to success; and (4) recommendations that may increase future successful rehabilitation. Strategies included harvest regulation changes, stocking, fish community manipulations, habitat enhancement, and partner discussions. Overall, evaluations of environmental, habitat, and fish community factors causing walleye population declines were not included in most rehabilitation plans before implementation. This review highlights an increased need for ecosystem-based fisheries management principles and cultivating ecological conditions that favor walleye as a potential path for future rehabilitation plans. Lessons drawn from rehabilitation plans are applicable to global inland fisheries to inform the conservation of declining fish populations.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23308249.2025.2487714","usgsCitation":"Embke, H.S., Feiner, Z.S., Hansen, G., Mrnak, J., Rounds, C., Sass, G., Shaw, S., and Shultz, A.D., 2025, Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation: Reviews in Fisheries Science and Aquaculture, v. 33, no. 4, p. 579-597, https://doi.org/10.1080/23308249.2025.2487714.","productDescription":"19 p.","startPage":"579","endPage":"597","ipdsId":"IP-158666","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":484503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":933074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feiner, Zachary S.","contributorId":342575,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary","email":"","middleInitial":"S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":933075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen","contributorId":174810,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":933076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mrnak, Joseph T.","contributorId":348717,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joseph T.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":933077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rounds, Christopher I.","contributorId":349471,"corporation":false,"usgs":false,"family":"Rounds","given":"Christopher I.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":933078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sass, Greg G.","contributorId":244466,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":933079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaw, Stephanie L.","contributorId":342852,"corporation":false,"usgs":false,"family":"Shaw","given":"Stephanie L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":933080,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shultz, Aaron D.","contributorId":303739,"corporation":false,"usgs":false,"family":"Shultz","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16233,"text":"Great Lakes Indian Fish and Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":933081,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271313,"text":"70271313 - 2025 - Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","interactions":[],"lastModifiedDate":"2025-09-04T15:13:46.061817","indexId":"70271313","displayToPublicDate":"2025-04-09T08:06:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","docAbstract":"The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.
","language":"English","publisher":"MDPI","doi":"10.3390/w17081120","usgsCitation":"Nelson, K., Quinn, N., and Traum, J.A., 2025, Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management: Water, v. 17, no. 8, 1120, 26 p., https://doi.org/10.3390/w17081120.","productDescription":"1120, 26 p.","ipdsId":"IP-175116","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":495188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17081120","text":"Publisher Index Page"},{"id":495166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.73121499117096,\n 38.53799288965703\n ],\n [\n -120.87600359152006,\n 36.83520659574968\n ],\n [\n -119.56082081779095,\n 35.04449080764874\n ],\n [\n -118.38309238355373,\n 35.35382368503207\n ],\n [\n -120.95162530913443,\n 38.878303068488464\n ],\n [\n -121.73121499117096,\n 38.53799288965703\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nelson, Kirk","contributorId":360939,"corporation":false,"usgs":false,"family":"Nelson","given":"Kirk","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":947952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Nigel","contributorId":360940,"corporation":false,"usgs":false,"family":"Quinn","given":"Nigel","affiliations":[{"id":86123,"text":"Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":947953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947954,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265532,"text":"70265532 - 2025 - Variable phenology but consistent loss of ice cover of 1213 Minnesota lakes","interactions":[],"lastModifiedDate":"2025-08-04T15:36:27.834214","indexId":"70265532","displayToPublicDate":"2025-04-09T07:59:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Variable phenology but consistent loss of ice cover of 1213 Minnesota lakes","docAbstract":"Lake ice cover is declining globally with important implications for lake ecosystems. Ice loss studies often rely on small numbers of lakes with long-term data. We analyzed variation and trends in ice cover phenology from 1,213 lakes over 74 years (1949-2022) in Minnesota (USA), during which ice cover duration declined at a rate of 2 days per decade (14 days total) and became more variable. Despite variation in phenology, just 10-20% of lakes differed from statewide phenological trends. Accounting for synchronous annual variation and estimating trends over long time periods (e.g., >40 years) were critical for obtaining robust estimates of ice loss. The constant rates estimated here were consistent with recent global estimates (1.7-1.9 days per decade) and suggest that, even if present, accelerating rates of ice loss would be difficult to detect in the midst of shorter-term periods of warming and increasing variability.","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.70015","usgsCitation":"Walsh, J., Rounds, C., Vitense, K., Masui, H., Blumenfeld, K., Boulay, P., Thomas, S., Honsey, A.E., Blinick, N.S., Rude, C.L., Bacon, J., LaRoque, A., Leao, T., and Hansen, G., 2025, Variable phenology but consistent loss of ice cover of 1213 Minnesota lakes: Limnology and Oceanography Letters, v. 10, no. 4, p. 506-515, https://doi.org/10.1002/lol2.70015.","productDescription":"10 p.","startPage":"506","endPage":"515","ipdsId":"IP-171385","costCenters":[{"id":324,"text":"Great Lakes Science 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2327 University Way, Suite 2
Bozeman, MT 59715
High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Understanding long-term coastal evolution requires historical data, yet accessing reliable information becomes increasingly challenging for extended periods. While vertical aerial imagery has been extensively used in coastal studies since the mid-20th century, and satellite-derived shoreline measurements are now revolutionizing shoreline change studies, ground-based images, such as historical photographs and picture postcards, provide an alternative source of shoreline data for earlier periods when other datasets are scarce. Despite their frequent use for documenting qualitative morphological changes, these valuable historical data sources have rarely supported quantitative assessments of coastal evolution. This study demonstrates the potential of historical ground-oblique images for quantitatively assessing shoreline position and long-term change. Using Conceição-Duquesa Beach (Cascais, Portugal) as a case study, we analyze shoreline evolution over 92 years by applying a novel methodology to historical photographs and postcards. The approach combines image registration, shoreline detection, coordinate transformation, and rectification while accounting for positional uncertainty. Results reveal a significant counterclockwise rotation of the shoreline between the 20th and 21st centuries, exceeding estimated uncertainty thresholds. This study highlights the feasibility of using historical ground-based imagery to reconstruct shoreline positions and quantify long-term coastal change. The methodology is straightforward, adaptable, and offers a promising avenue for extending the temporal range of shoreline datasets, advancing our understanding of coastal evolution.
","language":"English","publisher":"MDPI","doi":"10.3390/rs17081326","usgsCitation":"Valverde, F., Taborda, R., East, A.E., and Ponte Lira, C., 2025, Historical coast snaps: Using centennial imagery to track shoreline change: Remote Sensing, v. p., no. 8, 1326, 25, https://doi.org/10.3390/rs17081326.","productDescription":"1326, 25","ipdsId":"IP-174741","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488216,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17081326","text":"Publisher Index Page"},{"id":484510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Portugal","city":"Cascais","otherGeospatial":"Conceição-Duquesa urban beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -9.42387719442334,\n 38.70744120223975\n ],\n [\n -9.42387719442334,\n 38.69407237227725\n ],\n [\n -9.383850065079855,\n 38.69407237227725\n ],\n [\n -9.383850065079855,\n 38.70744120223975\n ],\n [\n -9.42387719442334,\n 38.70744120223975\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"p.","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Valverde, Fatima","contributorId":353271,"corporation":false,"usgs":false,"family":"Valverde","given":"Fatima","affiliations":[{"id":38277,"text":"University of Lisbon","active":true,"usgs":false}],"preferred":false,"id":933235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taborda, Rui","contributorId":353272,"corporation":false,"usgs":false,"family":"Taborda","given":"Rui","affiliations":[{"id":38277,"text":"University of Lisbon","active":true,"usgs":false}],"preferred":false,"id":933236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ponte Lira, Cristina","contributorId":353273,"corporation":false,"usgs":false,"family":"Ponte Lira","given":"Cristina","affiliations":[{"id":38277,"text":"University of Lisbon","active":true,"usgs":false}],"preferred":false,"id":933238,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268660,"text":"70268660 - 2025 - Identifying gaps in regulatory prevention measures for nonindigenous aquatic species in the United States","interactions":[],"lastModifiedDate":"2025-07-08T16:01:52.883086","indexId":"70268660","displayToPublicDate":"2025-04-08T10:58:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Identifying gaps in regulatory prevention measures for nonindigenous aquatic species in the United States","docAbstract":"Nonindigenous aquatic species (NAS) present in trade can become costly invaders once introduced and established in a new environment. Preventing NAS introduction is considered the most effective strategy to avoid potential negative ecological, economic, and human health impacts associated with certain species. The United States government enacts regulatory prevention measures carried out by numerous federal agencies with designated authority over certain species, taxonomic groups, and pathways of introduction. We examined 18 case study species across eight taxonomic groups and eight pathways of introduction using a gap analysis approach to identify current gaps in regulatory prevention that may hinder the United States from achieving a more “ideal state” of management in which no NAS or pathways of introduction are unregulated. We found that outside of pathway regulations for ballast water and biofouling, the majority of amphibian, fish, reptile, crustacean, and mollusk species are subject to little to no regulation aside from a few specific species that are highly regulated. We also found large knowledge gaps surrounding the diversity of species and quantities of individual organisms introduced into the United States through the hitchhiking and cultural release pathways. We highlight that the current regulatory approach in the United States is a “blocklist” approach where a select list of species is disallowed as compared to an “allowlist” (approved list of species allowed only) or “conditional list” (between a “blocklist” and “allowlist”) used by Australia and New Zealand. Increased documentation of the diversity and quantities of NAS entering the United States and a better understanding of the contribution of the hitchhiking and cultural release pathways to NAS introductions could help inform regulatory prevention.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2025.16.2.01","usgsCitation":"Hendrickson, Z., Martin, C.M., and Daniel, W., 2025, Identifying gaps in regulatory prevention measures for nonindigenous aquatic species in the United States: Management of Biological Invasions, v. 16, no. 2, p. 313-339, https://doi.org/10.3391/mbi.2025.16.2.01.","productDescription":"27 p.","startPage":"313","endPage":"339","ipdsId":"IP-157855","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":492059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2025.16.2.01","text":"Publisher Index Page"},{"id":491809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Hendrickson, Zoey","contributorId":350114,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Zoey","affiliations":[{"id":48710,"text":"University of South Alabama","active":true,"usgs":false}],"preferred":false,"id":941595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Charles M.","contributorId":55490,"corporation":false,"usgs":false,"family":"Martin","given":"Charles","email":"","middleInitial":"M.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":941596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, Wesley 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219312,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":941597,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265480,"text":"sir20255009 - 2025 - Application of Hydrologic Simulation Program—FORTRAN (HSPF) as part of an integrated hydrologic model for the Salinas Valley, California","interactions":[],"lastModifiedDate":"2025-08-07T20:33:11.257584","indexId":"sir20255009","displayToPublicDate":"2025-04-08T10:50:17","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":"2025-5009","displayTitle":"Application of Hydrologic Simulation Program—FORTRAN (HSPF) as Part of an Integrated Hydrologic Model for the Salinas Valley, California","title":"Application of Hydrologic Simulation Program—FORTRAN (HSPF) as part of an integrated hydrologic model for the Salinas Valley, California","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Monterey County Water Resources Agency, conducted studies to help evaluate the surface-water and groundwater resources of the Salinas Valley study area, consisting of the entire Salinas River watershed and several smaller, adjacent coastal watersheds draining into Monterey Bay. The Salinas Valley study area is a highly productive agricultural region that depends on the coordinated use of surface water and groundwater to meet demand for irrigation and public water supply. To continue to meet these demands, a better understanding of the historical water balance and the effects of water-resource development on the long-term sustainability of water resources in the Salinas Valley study area is needed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255009","collaboration":"Prepared in cooperation with the Monterey County Water Resources Agency","programNote":"Water Resource Mission Area—Water Availability and Use Science Program","usgsCitation":"Hevesi, J.A., Henson, W., Hanson, R.T., Jachens, E.R., Bond, S., Earll, M.M., and Herbert, D., 2025, Application of Hydrologic Simulation Program—FORTRAN (HSPF) as part of an integrated hydrologic model for the Salinas Valley, California: U.S. Geological Survey Scientific Investigations Report 2025–5009, 148 p., https://doi.org/10.3133/sir20255009.","productDescription":"Report: xii, 148 p.; Data Release","numberOfPages":"148","onlineOnly":"Y","ipdsId":"IP-129397","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":493743,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118516.htm","linkFileType":{"id":5,"text":"html"}},{"id":484307,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FJAWC4","text":"USGS data release","description":"Hevesi, J., Henson, W., Hanson, R.T., Earll, M.M., Herbert, D.M., and Jachens, E.R., 2025, Salinas Valley watershed model—Application of Hydrologic Simulation Program—FORTRAN (HSPF): U.S. Geological Survey data release, https://doi.org/10.5066/P9FJAWC4","linkHelpText":"Salinas Valley watershed model—Application of Hydrologic Simulation Program—FORTRAN (HSPF)"},{"id":484309,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5009/sir20255009.XML","description":"SIR 2025-5009 XML"},{"id":484304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5009/coverthb.jpg"},{"id":484310,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5009/images"},{"id":484308,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255009/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5009 HTML"},{"id":484306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5009/sir20255009.pdf","text":"Report","size":"38.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5009 PDF"}],"country":"United States","state":"California","otherGeospatial":"Salinas Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.67652901886302,\n 36.776695068396975\n ],\n [\n -121.78751170378024,\n 36.79802674348818\n ],\n [\n -121.86963889061894,\n 36.607609833119014\n ],\n [\n -121.92291057937909,\n 36.64679949204769\n ],\n [\n -121.97840192183737,\n 36.575530747588786\n ],\n [\n -120.9440432984108,\n 35.507662585291214\n ],\n [\n -120.48235532915595,\n 35.54921011874251\n ],\n [\n -120.6510490102299,\n 35.98505610457029\n ],\n [\n -121.40351161396718,\n 36.65036120011224\n ],\n [\n -121.67652901886302,\n 36.776695068396975\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Understanding fine-scale habitat selection of endangered Kootenai River white sturgeon (Acipenser transmontanus) is an important component for monitoring and recovery efforts. Fine-scale habitat selection and quantifying temporal changes in suitable habitat contributes to the work of addressing recruitment failure within the Kootenai River population. Habitat suitability indices were developed using over 96 000 acoustic telemetry sturgeon detections and two-dimensional hydrodynamic model simulations near Bonners Ferry, Idaho, USA. The selected habitat was assessed to develop habitat suitability indices for sturgeon; females undergoing spawn migrations and non-spawners. The most frequented locations were 8–9 m deep and water velocities of 0.3–0.7 m·s−1. These observations suggest sturgeon with different spawning capabilities selected similar habitat. Weighted usable area was calculated to understand temporal variability in habitat quality, which showed a positive relationship with increases in flow. Results help understand the habitat limiting factors in regulated hydrologic regimes; provide biologists insight for monitoring efforts in discrete habitat conditions; guidance for water managers and the regulation of upstream water resources; and guidance to restoration practitioners for in-stream structure designs.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0244","usgsCitation":"Dudunake, T., Kenworthy, M.K., Smith, T., Stephenson, S., and Hardy, R.S., 2025, Influence of local river hydraulics on Kootenai River white sturgeon (Acipenser transmontanus) habitat selection during four spawning years, 2017–2020: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, 16 p., https://doi.org/10.1139/cjfas-2024-0244.","productDescription":"16 p.","ipdsId":"IP-150378","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":488244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0244","text":"Publisher Index Page"},{"id":484574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.30893853974553,\n 48.70438566677956\n ],\n [\n -116.33409421325345,\n 48.70438566677956\n ],\n [\n -116.33409421325345,\n 48.691255343773804\n ],\n [\n -116.30893853974553,\n 48.691255343773804\n ],\n [\n -116.30893853974553,\n 48.70438566677956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudunake, Taylor 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":191564,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenworthy, Megan Kearney 0000-0001-7108-3016","orcid":"https://orcid.org/0000-0001-7108-3016","contributorId":304286,"corporation":false,"usgs":true,"family":"Kenworthy","given":"Megan","email":"","middleInitial":"Kearney","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Troy","contributorId":353368,"corporation":false,"usgs":false,"family":"Smith","given":"Troy","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, Sarah","contributorId":353369,"corporation":false,"usgs":false,"family":"Stephenson","given":"Sarah","affiliations":[{"id":51972,"text":"British Columbia Ministry of Forests","active":true,"usgs":false}],"preferred":false,"id":933388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":933389,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265482,"text":"70265482 - 2025 - How quickly do brook trout lose long-term thermal acclimation?","interactions":[],"lastModifiedDate":"2025-04-08T15:42:42.223359","indexId":"70265482","displayToPublicDate":"2025-04-08T08:37:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"How quickly do brook trout lose long-term thermal acclimation?","docAbstract":"Abundances of coldwater adapted stream fish populations are declining largely due to anthropogenic influences, including increased temperature. To persist in streams with unsuitable thermal habitat, fish must move to coldwater patches, acclimate, or adapt to water temperatures above thermal optima. Brook trout, a coldwater adapted salmonid, has previously displayed physiological plasticity and the ability for reversible thermal acclimation when reared at higher temperatures. However, because stream temperatures are not static, it is important to explore the rate at which thermal acclimation occurs to evaluate whether prior thermal experience will influence future thermal performance. To determine the temporal scale in loss of thermal acclimation as water temperatures cool, we acclimated brook trout to three thermal regimes: +0 °C (ambient; mimicking the daily average water temperature of a nearby long-term study site), as well as +2 °C and +4 °C above ambient. After 2 years of being reared under those conditions, fish from the warmer treatments were moved to a common, colder temperature (ambient). We then used critical thermal maximum to measure the loss in acclimation response of fish from each treatment over time. We found that regardless of initial acclimation temperature, thermal tolerance of warm acclimated fish decreased rapidly for 1 week, then gradually decreased, and was completely lost within 42 days. This gradual loss of acclimation may be valuable to persistence in warmer streams and will be important to include in models of the impact climate change has on brook trout and other aquatic ectotherms with significant thermal plasticity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2025.104103","usgsCitation":"O'Donnell, M., Regish, A.M., McCormick, S., and Letcher, B., 2025, How quickly do brook trout lose long-term thermal acclimation?: Journal of Thermal Biology, v. 129, 104103, 7 p., https://doi.org/10.1016/j.jtherbio.2025.104103.","productDescription":"104103, 7 p.","ipdsId":"IP-173670","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Whatley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.6617758519881,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.46221452312392\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":299019,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":932809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, S.D.","contributorId":353071,"corporation":false,"usgs":false,"family":"McCormick","given":"S.D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":932811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265472,"text":"sir20255012 - 2025 - Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022","interactions":[],"lastModifiedDate":"2025-04-16T14:15:30.417956","indexId":"sir20255012","displayToPublicDate":"2025-04-07T14:02:42","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":"2025-5012","displayTitle":"Sediment Nutrient Dynamics in Selected Milwaukee Metropolitan Area Streams, Wisconsin, 2022","title":"Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022","docAbstract":"The U.S. Geological Survey and Milwaukee Metropolitan Sewerage District in Wisconsin have an ongoing partnership to monitor water quality in streams in the Milwaukee metropolitan area and to assess the effects of stream restoration on habitat and water quality. Because sediment nutrient dynamics can improve or further impair water quality, we measured sediment nitrogen and phosphorus concentrations, potential nitrogen removal, and potential phosphorus retention at 32 streams sites in the Milwaukee metropolitan area in summer 2022. Four of the sites were in rehabilitated stream reaches. Based on the results from this project, we provided a rating of good, fair, or poor for the sediment nutrient dynamics at each site.
Sediment nitrogen removal and phosphorus retention in stream reaches increased as the proportion of fine particles increased. Bioavailable nitrogen and phosphorus concentrations increased in stream reaches as particle size decreased, especially at locations with more silt and clay. Particle size typically decreased from upstream to downstream, and several of the sites with finer particles were in downstream parts of the study area, especially in the Milwaukee Estuary sites. The sites that had more fine sediment and higher bioavailable nutrients also had elevated rates of nitrification and denitrification enzyme activity, which is a measurement of the potential nitrogen removal when nitrogen and carbon do not limit the denitrifying bacteria. Additionally, sites with fine sediment typically had the highest potential to retain phosphorus as fine sediment provides many binding sites for phosphorus. The binding sites can become saturated with phosphorus, however, increasing the potential for the phosphorus to be released to stream water. Five of the 32 sampled sites were potentially saturated with phosphorus. Sites that contained more agricultural land in their drainage areas were at higher risk of having sediment that was saturated or near-saturation; however, the sites that had more agricultural land in their drainage areas also had higher nitrification rates. Results from this study indicate that stream rehabilitation projects that promote sediment deposition and accumulation of organic matter in the stream channel can increase nitrogen removal and phosphorus retention.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255012","usgsCitation":"Kreiling, R.M., Bartsch, L.A., Gierke, K.J., Perner, P.M., Fitzpatrick, F.A., and Olds, H.T., 2025, Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022: U.S. Geological Survey Scientific Investigations Report 2025–5012, 34 p., https://doi.org/10.3133/sir20255012.","productDescription":"Report: vi, 34 p.; Data Release; Dataset","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168307","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":484256,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255012/full"},{"id":484255,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5012/images/"},{"id":484253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5012/sir20255012.pdf","text":"Report","size":"24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5012"},{"id":484258,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":484257,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14KFDFC","text":"USGS data release","linkHelpText":"Milwaukee Metropolitan Sewerage District nutrient connections project—In-stream nutrient cycling, 2022 data"},{"id":484254,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5012/sir20255012.XML"},{"id":484252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5012/coverthb.jpg"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.86648934255896,\n 43.18238733374105\n ],\n [\n -88.05617136083607,\n 43.18238733374105\n ],\n [\n -88.05617136083607,\n 42.87118189515698\n ],\n [\n -87.82769074791146,\n 42.88302863937423\n ],\n [\n -87.86648934255896,\n 43.18238733374105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Freshwater forested wetlands account for ~76% (918 M ha) of the total global wetland extent. However, freshwater forested wetlands are difficult to distinguish from upland forest due to canopy coverage, the abundance of wetland-nonwetland mosaics, seasonal hydropatterns, and fewer readily observable connections to large surface water bodies relative to marshes and other emergent habitats. Therefore, freshwater forested wetland ecosystems are often misclassified as upland forests in carbon accounting models, underestimating soil organic carbon (SOC) storage. This study highlights freshwater forested wetland SOC accounting challenges and presents SOC densities/stocks from a global literature synthesis across different freshwater forested wetland types. We reviewed 374 forested wetland articles, compiling and calculating carbon densities by depth from 90 freshwater forested wetland studies to construct a database of 334 study sites including nine countries. The median (± median absolute deviation) SOC stock was 91.2 ± 46.4 Mg C ha−1 and 235.3 ± 125.6 Mg C ha−1 in the top 30 cm and 100 cm of soil, respectively. The tidal freshwater forested wetland had highest SOC stock (341.6 ± 98.4 Mg C ha−1) in the upper 100 cm soil profile followed by rainforest (285.6 ± 75.8 Mg C ha−1), non-tidal swamps (229.3 ± 120.4 Mg C ha−1), and floodplain forested wetlands (176.6 ± 84 Mg C ha−1). Within the conterminous United States forest type groups, the Tsuga/Picea group had the highest median SOC stocks (353.6 ± 82.9 Mg ha−1) in the top 100 cm of soil followed by Quercus/Pinus (246.6 ± 82.3 Mg ha−1) and Quercus/Liquidambar/Taxodium (207.9 ± 87.7 Mg ha−1) groups, likely driven by variability in litter degradability, wetland hydroperiod, geomorphic positions, and regional climatic factors. This literature synthesis highlights SOC accounting in freshwater forested wetland carbon pools when estimating carbon stocks and fluxes. Results can be used to improve carbon modeling outcomes, as well as inform regional, national, and global management of wetland carbon resources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2025.1528440","usgsCitation":"Sapkota, Y., Berkowitz, J., Stagg, C., and Busby, R., 2025, A synthesis of freshwater forested wetland soil organic carbon storage: Frontiers in Forests and Global Change, v. 8, 1528440, 15 p., https://doi.org/10.3389/ffgc.2025.1528440.","productDescription":"1528440, 15 p.","ipdsId":"IP-176238","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2025.1528440","text":"Publisher Index Page"},{"id":484639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Sapkota, Yadav","contributorId":353419,"corporation":false,"usgs":false,"family":"Sapkota","given":"Yadav","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Jacob F.","contributorId":353422,"corporation":false,"usgs":false,"family":"Berkowitz","given":"Jacob F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":214880,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":933530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busby, Ryan R.","contributorId":353425,"corporation":false,"usgs":false,"family":"Busby","given":"Ryan R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273025,"text":"70273025 - 2025 - Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","interactions":[],"lastModifiedDate":"2025-12-15T14:46:55.827369","indexId":"70273025","displayToPublicDate":"2025-04-07T08:38:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","title":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","docAbstract":"The freshwater copepod Salmincola californiensis is an ectoparasite of Pacific salmon and trout (Oncorhynchus spp.). High levels of infection by this parasite can significantly damage gills and result in blood loss, affecting the fitness and survival of hosts, and it may hinder recovery efforts of threatened and endangered salmonids. Juvenile salmonids that rear in reservoirs have been reported to experience higher rates of infection than their stream-dwelling counterparts. To date, the relationship between reservoir environmental conditions and infection rates remains poorly understood. Here, we evaluated sampling methods designed to capture S. californiensis copepodids, the free-swimming infectious life stage of this parasitic copepod, and develop predictive models of parasite abundance in reservoirs. We used light traps to collect 675 zooplankton samples from various sites and depths in Cougar, Lookout Point, and Fall Creek reservoirs, Oregon, USA during five months in 2020. We tested several predictive models of parasite abundance using environmental covariates obtained concurrently during plankton surveys (e.g., temperature, ambient light and water clarity, reservoir plankton profiles, and water flow). Our models showed a strong influence of water temperature on abundance of copepodids, with maximum initial abundance occurring at the mean water temperature 15.2 °C. At that temperature, August abundance was estimated to be 58.6 copepodids per site in Cougar Reservoir, 43.8 copepodids per site in Fall Creek Reservoir, and 3.5 copepodids per site in Lookout Point Reservoir. Water temperature and reservoir outflow both affected population growth of copepodids: increased water temperature was associated with an increase in population growth rate while an increased reservoir outflow was associated with a decrease in population growth rate. The efficacy of our sampling method was influenced by percent of moon fullness, whether the sample site was above or below the thermocline, water temperature, and number of juvenile sculpin fishes (Cottus spp.) captured in the trap. The mean probability of detecting a single copepodid if one was present was 0.042, but detection probability increased to 0.29 under ideal trap set conditions of warmer water, location above the thermocline, and a full moon. Biologists and managers could use these methods to assess the presence and abundance of S. californiensis in other locations, or to inform reservoir operations to reduce potential salmonid infections.
","language":"English","publisher":"Peer J","doi":"10.7717/peerj.19228","usgsCitation":"Antonelli, K., Murphy, C.A., Pollock, A.M., and Arismendi, I., 2025, Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon: Aquatic Biology, v. 13, e19228, 24 p., https://doi.org/10.7717/peerj.19228.","productDescription":"e19228, 24 p.","ipdsId":"IP-172281","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497701,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.19228","text":"Publisher Index Page"},{"id":497471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"upper Willamette River reservoirs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.32050813525171,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.19989455893608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Antonelli, Kelsi","contributorId":341106,"corporation":false,"usgs":false,"family":"Antonelli","given":"Kelsi","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollock, Amanda M.M.","contributorId":363932,"corporation":false,"usgs":false,"family":"Pollock","given":"Amanda","middleInitial":"M.M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265494,"text":"70265494 - 2025 - Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","interactions":[],"lastModifiedDate":"2025-04-08T15:11:34.579076","indexId":"70265494","displayToPublicDate":"2025-04-07T08:01:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","docAbstract":"The accumulation area ratio (AAR) of a glacier reflects its current state of equilibrium, or disequilibrium, with climate and its vulnerability to future climate change. Here, we present an inventory of glacier-specific annual accumulation areas and equilibrium line altitudes (ELAs) for over 3000 glaciers in Alaska and northwest Canada (88% of the regional glacier area) from 2018 to 2022 derived from Sentinel-2 imagery. We find that the 5 year average AAR of the entire study area is 0.41, with an inter-annual range of 0.25–0.49. More than 1000 glaciers, representing 8% of the investigated glacier area, were found to have effectively no accumulation area. Summer temperature and winter precipitation from ERA5-Land explained nearly 50% of the inter-annual ELA variability across the entire study region (R2 = 0.47). An analysis of future climate scenarios (SSP2-4.5) projects that ELAs will rise by ∼170 m on average by the end of the 21st century. Such changes would result in a loss of 25% of the modern accumulation area, leaving a total of 1900 glaciers (22% of the investigated area) with no accumulation area. These results highlight the current state of glacier disequilibrium with modern climate, as well as glacier vulnerability to projected future warming.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/jog.2024.65","usgsCitation":"Zeller, L., McGrath, D.J., Sass, L., Florentine, C., and Downs, J., 2025, Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska: Journal of Glaciology, v. 71, e28, 13 p., https://doi.org/10.1017/jog.2024.65.","productDescription":"e28, 13 p.","ipdsId":"IP-163494","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":488628,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/jog.2024.65","text":"Publisher Index Page"},{"id":484323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":932825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":932826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Downs, Jacob 0000-0002-5588-7767","orcid":"https://orcid.org/0000-0002-5588-7767","contributorId":336920,"corporation":false,"usgs":false,"family":"Downs","given":"Jacob","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":932827,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265447,"text":"70265447 - 2025 - Estimating indicators of cyanobacterial harmful algal blooms in New York State","interactions":[],"lastModifiedDate":"2025-04-07T14:54:27.747567","indexId":"70265447","displayToPublicDate":"2025-04-07T07:50:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Estimating indicators of cyanobacterial harmful algal blooms in New York State","docAbstract":"Cyanobacteria harmful algal blooms (cyanoHABs) are a global concern for aquatic ecosystem and human health. Limited funding for monitoring programs and inconsistent determination of cyanoHAB occurrence present challenges for identifying commonly effective variables for characterizing cyanoHABs and the development of generalized models. We compiled a combination of water quality measurements, lake morphology, climatology, remote sensing data, and observations of cyanoHAB occurrence across New York State and used this dataset to develop two sets of predictive models. The first model predicted chlorophyll a, a common indicator of algal biomass, and assessed the importance of variables for modeled predictions. The most important variables were then used in a second set of models to classify cyanoHAB occurrence. The irradiance attenuation coefficient (Kd), which was estimated from Secchi depth measurements, and total phosphorus were the two most important variables for predicting chlorophyll a. The second model examined several variables for their ability to classify cyanoHAB occurrence. Predicted cyanoHAB occurrence based on thresholds of chlorophyll a, Kd, or total nitrogen all had moderate agreement and were able to correctly classify approximately 70% of observed cyanoHABs. Our analysis indicated that multiple data types were important for predicting chlorophyll a statewide and that simple widely available water quality parameters could classify cyanoHABs occurrence with reasonable accuracy. Identifying variables that can be monitored with increased frequency and decreased latency to detect cyanoHAB occurrence will better inform water managers and provide valuable additional data for further refining predictive models of the likelihood of cyanoHABs occurrence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113403","usgsCitation":"Savoy, P., Gorney, R.M., and Graham, J.L., 2025, Estimating indicators of cyanobacterial harmful algal blooms in New York State: Ecological Indicators, v. 173, 113403, 11 p., https://doi.org/10.1016/j.ecolind.2025.113403.","productDescription":"113403, 11 p.","ipdsId":"IP-171481","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":488558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113403","text":"Publisher Index Page"},{"id":484244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca Michelle 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","email":"","middleInitial":"Michelle","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932742,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265460,"text":"70265460 - 2025 - Fast or slow: An evaluation of Ti-in-quartz diffusion coefficients through comparisons of quartz and plagioclase diffusion times","interactions":[],"lastModifiedDate":"2025-04-07T14:18:54.313669","indexId":"70265460","displayToPublicDate":"2025-04-06T09:14:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Fast or slow: An evaluation of Ti-in-quartz diffusion coefficients through comparisons of quartz and plagioclase diffusion times","docAbstract":"Diffusion geochronometry using Ti-in-quartz has become a valuable method in understanding the evolution of silicic magmas. However, four different options for Ti diffusivity (DTi) currently exist, spanning three orders of magnitude, resulting in substantially different estimated times and interpretations. We present Ti-in-quartz diffusion times for the Cerro Galán Ignimbrite using the Cherniak et al. [2007] (10.1016/j.chemgeo.2006.09.001), Audétat et al. [2021] (10.1130/g48785.1), Audétat et al. [2023] (10.1038/s41467-023-39912-5), and Jollands et al. [2020] (10.1130/g47238.1) DTi value and (1) compare these against plagioclase diffusion times derived from the same samples, (2) consider evidence for Ti diffusion in quartz under relevant magmatic timescales, and (3) compute derived quartz growth rates for crystals from the Cerro Galán Ignimbrite. On all accounts, we find that the Cherniak et al. [2007] diffusion coefficient yields diffusion times that agree much better with independent evidence than those derived using slower DTi values [Jollands et al. 2020; Audétat et al. 2021; 2023].
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol/rjfq2443","usgsCitation":"Wang, S., Gualda, G., Lubbers, J.E., and Kent, A., 2025, Fast or slow: An evaluation of Ti-in-quartz diffusion coefficients through comparisons of quartz and plagioclase diffusion times: Volcanica, v. 8, no. 1, p. 189-202, https://doi.org/10.30909/vol/rjfq2443.","productDescription":"14 p.","startPage":"189","endPage":"202","ipdsId":"IP-166925","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol/rjfq2443","text":"Publisher Index Page"},{"id":484239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Sophia","contributorId":353043,"corporation":false,"usgs":false,"family":"Wang","given":"Sophia","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":932766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gualda, Guilherme","contributorId":353044,"corporation":false,"usgs":false,"family":"Gualda","given":"Guilherme","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":932767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubbers, Jordan Edward 0000-0002-3566-5091","orcid":"https://orcid.org/0000-0002-3566-5091","contributorId":330466,"corporation":false,"usgs":true,"family":"Lubbers","given":"Jordan","email":"","middleInitial":"Edward","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kent, Adam","contributorId":353047,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":932769,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265471,"text":"70265471 - 2025 - Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images","interactions":[],"lastModifiedDate":"2025-04-07T15:08:27.841513","indexId":"70265471","displayToPublicDate":"2025-04-06T08:01:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images","docAbstract":"CubeSats provide a wealth of high-frequency observations at a meter-scale spatial resolution. However, most current methods of inferring water depth from satellite data consider only a single image. This approach is sensitive to the radiometric quality of the data acquired at that particular instant in time, which could be degraded by various confounding factors, such as sun glint or atmospheric effects. Moreover, using single images in isolation fails to exploit recent improvements in the frequency of satellite image acquisition. This study aims to leverage the dense image time series from the SuperDove constellation via an ensembling framework that helps to improve empirical (regression-based) bathymetry retrieval. Unlike previous studies that only ensembled the original spectral data, we introduce a neural network-based method that instead ensembles the water depths derived from multi-temporal imagery, provided the data are acquired under steady flow conditions. We refer to this new approach as NN-depth ensembling. First, every image is treated individually to derive multitemporal depth estimates. Then, we use another NN regressor to ensemble the temporal water depths. This step serves to automatically weight the contribution of the bathymetric estimates from each time instance to the final bathymetry product. Unlike methods that ensemble spectral data, NN-depth ensembling mitigates against propagation of uncertainties in spectral data (e.g., noise due to sun glint) to the final bathymetric product. The proposed NN-depth ensembling is applied to temporal SuperDove imagery of reaches from the American, Potomac, and Colorado rivers with depths of up to 10 m and evaluated against in situ measurements. The proposed method provided more accurate and robust bathymetry retrieval than single-image analyses and other ensembling approaches.","language":"English","publisher":"MDPI","doi":"10.3390/rs17071309","usgsCitation":"Niroumand-Jadidi, M., Legleiter, C.J., and Bovolo, F., 2025, Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images: Remote Sensing, v. 17, no. 7, 1309, 19 p., https://doi.org/10.3390/rs17071309.","productDescription":"1309, 19 p.","ipdsId":"IP-149931","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17071309","text":"Publisher Index Page"},{"id":484247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Niroumand-Jadidi, Milad 0000-0002-9432-3032","orcid":"https://orcid.org/0000-0002-9432-3032","contributorId":292943,"corporation":false,"usgs":false,"family":"Niroumand-Jadidi","given":"Milad","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":932783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":932784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bovolo, Francesca 0000-0003-3104-7656","orcid":"https://orcid.org/0000-0003-3104-7656","contributorId":292944,"corporation":false,"usgs":false,"family":"Bovolo","given":"Francesca","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":932785,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}