In May 2021, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four spectral bands (red, band 1; green, band 2; blue, band 3; and near infrared, band 4) with a ground resolution of 20 centimeters, are available as 16-bit unsigned-integer GeoTIFF files in Sankey and others (2024) (available online at https://doi.org/10.5066/P9BBGN6G). The image files are projected in the State Plane Coordinate System, using the central Arizona zone (202) with the North American Datum of 1983 National Adjustment of 2011. The assessed spatial accuracy for these data is based on 47 ground-control points that were independent from the ground-control points used by the contractor for aerotriangulation and is reported at the 95-percent confidence level as 0.514 meter (m) and a root mean square error of 0.297 m. The intended uses of this dataset are primarily in support of scientific research and monitoring applications. Examples of these applications include high-resolution spatial and temporal change detection of the river channel, geomorphic landforms, riparian vegetation, and backwater and nearshore habitat, as well as other ecosystem-wide mapping. These imagery data also serve as reference material for field science mission planning, as base data for field data collection including community science activities, and as a highly detailed guide for technical boat operation during science activities such as reconnaissance for nighttime missions and navigating rapids during low flows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1202","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Sankey, J.B., Bransky, N.D., Pigue, L.M., Kohl, K.A., and Gushue, T.M., 2025, Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2021 airborne image acquisition: U.S. Geological Survey Data Report 1202, https://doi.org/10.3133/dr1202.","productDescription":"Report: HTML Document; Data Release","onlineOnly":"Y","ipdsId":"IP-162668","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":483089,"rank":2,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1202/dr1202.XML"},{"id":483585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":483091,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1202/full"},{"id":483090,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1202/images"},{"id":483526,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1027","description":"Durning, L.E., Sankey, J.B., Davis, P.A., and Sankey, T.T., 2016, Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2013 airborne image acquisition: U.S. Geological Survey Data Series 1027, https://doi.org/10.3133/ds1027.","linkHelpText":"- Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2013 airborne image acquisition"},{"id":483066,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/780/","description":"Davis, P.A., 2013, Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection: U.S. Geological Survey Data Series 780, https://pubs.usgs.gov/ds/780/.","linkHelpText":"- Natural-color and color-infrared image mosaics of the Colorado River corridor in Arizona derived from the May 2009 airborne image collection"},{"id":483527,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"http://pubs.usgs.gov/of/2012/1139/","description":"Davis, P.A., 2012, Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009—Image-mosaic production and comparison with 2002 and 2005 image mosaics: U.S. Geological Survey Open-File Report 2012–1139, 82 p. (Available at http://pubs.usgs.gov/of/2012/1139/.)","linkHelpText":"- Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009—Image-mosaic production and comparison with 2002 and 2005 image mosaics"},{"id":483065,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P93Y4FMJ","description":"Sankey, J.B., Bransky, N.B., Kohl, K.A., Gushue, T.M., Bedford, A.F., and Durning, L.E., 2025, Digital elevation model (DEM) and digital surface model (DSM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2002, 2009, 2013 and 2021), including accuracy assessment data: U.S. Geological Survey data release, https://doi.org/10.5066/P93Y4FMJ.","linkHelpText":"- Digital elevation model (DEM) and digital surface model (DSM) data for the Colorado River corridor in Grand Canyon National Park and Glen Canyon National Recreation Area (2002, 2009, 2013 and 2021), including accuracy assessment data"},{"id":483064,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BBGN6G","text":"USGS Data Release","description":"Sankey, J.B., Bransky, N., Pigue, L., Kohl, K., and Gushue, T.M., 2024, Four Band Image Mosaic of the Colorado River Corridor in Arizona—2021, including Accuracy Assessment Data: U.S. Geological Survey data release, https://doi.org/10.5066/P9BBGN6G.","linkHelpText":"Four band image mosaic of the Colorado River Corridor in Arizona—2021, including accuracy assessment data"},{"id":483525,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7TX3CHS","description":"Durning, L.E., Sankey, J.B., Davis, P.A., and Sankey, T.T., 2016, Four band Image mosaic of the Colorado River Corridor in Arizona--2013, including accuracy assessment data: U.S. Geological Survey data release, https://doi.org/10.5066/F7TX3CHS","linkHelpText":"- Four band Image mosaic of the Colorado River Corridor in Arizona--2013, including accuracy assessment data"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Colorado River, Glen Canyon Dam, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.25503634497424,\n 37.07331588090071\n ],\n [\n -115.01927028989792,\n 37.07331588090071\n ],\n [\n -115.01927028989792,\n 35.44030487638608\n ],\n [\n -111.25503634497424,\n 35.44030487638608\n ],\n [\n -111.25503634497424,\n 37.07331588090071\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Wildfires are a rapidly increasing threat to boreal forests. While our understanding of the drivers behind wildfires and their environmental impact is growing, it is mostly limited to the observational period. Here we focus on the boreal forests of southern Siberia and exploit a U–Th-dated stalagmite from Botovskaya Cave, located in the upper Lena region of southern Siberia, to document wildfire activity and vegetation dynamics during parts of two warm periods: the Last Interglacial (LIG; specifically part of the Last Interglacial maximum between 124.1 and 118.8 ka) and the Holocene (10–0 ka). Our record is based on levoglucosan (Lev), a biomarker sensitive to biomass burning, and on lignin oxidation products (LOPs) that discriminate between open and closed forest and hard- or softwood vegetation. In addition, we used carbonate carbon stable isotope ratios (δ13C), which reflect a dominant control of the host rock, to evaluate soil respiration and local infiltration changes. Our LOP data suggest that, during the Last Interglacial, the region around Botovskaya Cave was characterised by open forest, which by ca. 121.5 ka underwent a transition from fire-resistant hardwood to fire-prone softwood. The Lev record indicates that fire activity was high and increased towards the end of Last Interglacial just before 119 ka. In contrast, the Holocene was characterised by a closed-forest environment with mixed hard- and softwood vegetation. Holocene fire activity varied but at a much lower level than during the Last Interglacial. We attribute the changes in wildfire activity during the intervals of interest to the interplay between vegetation and climate. The open forests of the Last Interglacial were more likely to ignite than their closed Holocene equivalents, and their flammability was aided by warmer and drier summers and a stronger seasonal temperature contrast due to the increase in seasonal insolation difference compared to the Holocene. Our comparison of the last two interglacial intervals suggests that, with increasing global temperatures, the boreal forest of southern Siberia may become progressively more vulnerable to higher wildfire activity.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-21-661-2025","usgsCitation":"Margerum, J., Homann, J., Umbo, S., Nehrke, G., Hoffmann, T., Vaks, A., Kononov, A., Osintsev, A., Giesche, A., Mason, A., Lechleitner, F., Henderson, G., Kwiecien, O., and Breitenbach, S., 2025, Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in Southern Siberia: Climate of the Past, v. 21, no. 3, p. 661-677, https://doi.org/10.5194/cp-21-661-2025.","productDescription":"17 p.","startPage":"661","endPage":"677","ipdsId":"IP-165953","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":488363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-21-661-2025","text":"Publisher Index Page"},{"id":483662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Botovskaya Cave, Siberia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 104.97249739324332,\n 55.0006548103033\n ],\n [\n 104.97249739324332,\n 54.87985401356909\n ],\n [\n 105.12004339826586,\n 54.87985401356909\n ],\n [\n 105.12004339826586,\n 55.0006548103033\n ],\n [\n 104.97249739324332,\n 55.0006548103033\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Margerum, Jade","contributorId":352494,"corporation":false,"usgs":false,"family":"Margerum","given":"Jade","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homann, Julia","contributorId":352495,"corporation":false,"usgs":false,"family":"Homann","given":"Julia","affiliations":[{"id":84241,"text":"Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":931489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Umbo, Stuart","contributorId":352496,"corporation":false,"usgs":false,"family":"Umbo","given":"Stuart","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nehrke, Gernot","contributorId":352497,"corporation":false,"usgs":false,"family":"Nehrke","given":"Gernot","affiliations":[{"id":84242,"text":"Alfred Wegener Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Section Marine BioGeoSciences, 27570 Bremerhaven, Germany","active":true,"usgs":false}],"preferred":false,"id":931491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffmann, Thorsten","contributorId":352498,"corporation":false,"usgs":false,"family":"Hoffmann","given":"Thorsten","affiliations":[{"id":84241,"text":"Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":931492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vaks, Anton","contributorId":352499,"corporation":false,"usgs":false,"family":"Vaks","given":"Anton","affiliations":[{"id":84243,"text":"Geological Survey of Israel, 32 Yeshayahu Leibowitz Street, 9692100 Jerusalem, Israel","active":true,"usgs":false}],"preferred":false,"id":931493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kononov, Aleksandr","contributorId":352500,"corporation":false,"usgs":false,"family":"Kononov","given":"Aleksandr","affiliations":[{"id":84244,"text":"Irkutsk Nation al Research Technical University, Irkutsk, 664074, Russia; Institute of the Earth's Crust, Russian Academy of Sciences, Siberian Branch, Irkutsk, 664033, Russia","active":true,"usgs":false}],"preferred":false,"id":931494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Osintsev, Alexander","contributorId":352501,"corporation":false,"usgs":false,"family":"Osintsev","given":"Alexander","affiliations":[{"id":84245,"text":"Speleoclub Arabika, St. Mamina-Sibiryaka 6a, 664058 Irkutsk, Russia","active":true,"usgs":false}],"preferred":false,"id":931495,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Giesche, Alena Maria 0000-0003-3673-7269","orcid":"https://orcid.org/0000-0003-3673-7269","contributorId":344659,"corporation":false,"usgs":true,"family":"Giesche","given":"Alena Maria","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":931496,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mason, Andrew","contributorId":352502,"corporation":false,"usgs":false,"family":"Mason","given":"Andrew","affiliations":[{"id":84247,"text":"Department of Earth Sciences, University of Oxford, South Parks Road, OX1 3AN Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":931497,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lechleitner, Franziska A.","contributorId":352503,"corporation":false,"usgs":false,"family":"Lechleitner","given":"Franziska A.","affiliations":[{"id":84248,"text":"Department of Chemistry, Biochemistry and Pharmaceutical Sciences & Oeschger Centre for Climate Change Research, Universität Bern, Freiestrasse 3, 3012 Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":931498,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Henderson, Gideon M.","contributorId":352504,"corporation":false,"usgs":false,"family":"Henderson","given":"Gideon M.","affiliations":[{"id":84247,"text":"Department of Earth Sciences, University of Oxford, South Parks Road, OX1 3AN Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":931499,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kwiecien, Ola","contributorId":352505,"corporation":false,"usgs":false,"family":"Kwiecien","given":"Ola","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931500,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Breitenbach, Sebastian F.M.","contributorId":352506,"corporation":false,"usgs":false,"family":"Breitenbach","given":"Sebastian F.M.","affiliations":[{"id":84240,"text":"Department of Earth and Environmental Sciences, Northumbria University, Newcastle-Upon-Tyne, NE1 8ST, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":931501,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70264658,"text":"sir20255013 - 2025 - Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2025-07-23T17:11:15.939504","indexId":"sir20255013","displayToPublicDate":"2025-03-19T11:57:37","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":"2025-5013","displayTitle":"Hydrogeologic Investigation, Framework, and Conceptual Flow Model of the Antlers Aquifer, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022","docAbstract":"The 1973 Oklahoma Groundwater Law (Oklahoma Statute §82–1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. Every 20 years, the Oklahoma Water Resources Board is required to update the hydrologic investigation on which the maximum annual yield determinations were based. The maximum annual yield allocated per acre of land is used to set the equal-proportionate share pumping rate. The maximum annual yield of 5,913,600 acre-feet per year and equal-proportionate-share of 2.1 acre-feet per acre per year currently (2025) in place for the Antlers aquifer were issued by the Oklahoma Water Resources Board on February 14, 1995. Because more than 20 years have elapsed since the 1995 final order for the Antlers aquifer was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an in-depth hydrologic study that included a hydrogeologic framework and conceptual groundwater-flow model for the 1980–2022 study period.
The results of an analysis of land use, long-term climate patterns, streamflow and base-flow patterns, historical groundwater use, as well as groundwater-level fluctuations across the Antlers aquifer are described. In addition, groundwater quality was analyzed for total dissolved solids concentrations and major ions for the Antlers aquifer. An updated hydrogeologic framework was developed that included refining the aquifer boundary in Oklahoma, the creation of new potentiometric surface and saturated thickness of fresh groundwater maps, one multiple-well aquifer test, slug tests, and an analysis of lithologic logs across the aquifer. A conceptual groundwater flow model and water budget were developed by incorporating estimates of recharge from precipitation, saturated-zone evapotranspiration, streambed seepage, lateral groundwater flows, vertical leakage, and withdrawals from groundwater wells.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 1.2 billion barrels of oil and 6.4 trillion cubic feet of gas in Oman.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243050","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., 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 conventional oil and gas resources of Oman, 2023: U.S. Geological Survey Fact Sheet 2024–3050, 4 p., https://doi.org/10.3133/fs20243050.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":483366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3050/coverthb.jpg"},{"id":483367,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3050/fs20243050.pdf","text":"Report","size":"1.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3050"},{"id":483368,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1VRJXRI","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Oman Provinces: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":483540,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3050/images"},{"id":483541,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3050/fs20243050.xml"},{"id":483544,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243050/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3050"}],"country":"Oman","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":137,\"properties\":{\"name\":\"Oman\"},\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[58.86114,21.11403],[58.48799,20.42899],[58.03432,20.48144],[57.82637,20.243],[57.66576,19.736],[57.7887,19.06757],[57.69439,18.94471],[57.23426,18.94799],[56.60965,18.57427],[56.51219,18.08711],[56.28352,17.87607],[55.66149,17.88413],[55.26994,17.63231],[55.2749,17.22835],[54.791,16.9507],[54.23925,17.04498],[53.57051,16.70766],[53.10857,16.65105],[52.78218,17.34974],[52.00001,19],[54.99998,19.99999],[55.66666,22],[55.20834,22.70833],[55.23449,23.11099],[55.52584,23.52487],[55.52863,23.9336],[55.98121,24.13054],[55.80412,24.2696],[55.88623,24.92083],[56.39685,24.92473],[56.84514,24.24167],[57.40345,23.87859],[58.13695,23.74793],[58.72921,23.56567],[59.1805,22.9924],[59.4501,22.66027],[59.80806,22.53361],[59.80615,22.31052],[59.44219,21.71454],[59.28241,21.43389],[58.86114,21.11403],[58.86114,21.11403]]],[[[56.39142,25.89599],[56.26104,25.71461],[56.07082,26.05546],[56.36202,26.39593],[56.48568,26.30912],[56.39142,25.89599],[56.39142,25.89599]]]]}}]}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
In this commentary, we aim to (1) describe ways that hydrological intensification and hydrological whiplash (sub-seasonal transitions between hydrological extremes) may impact water management decision-making, (2) introduce the complexities of identifying and quantifying hydrological extreme transitions, (3) discuss the processes controlling hydrological transitions and trends in hydrological extremes through time, (4) discuss considerations involved in modeling hydrological extreme transitions, and (5) motivate additional research by suggesting priority research questions that diverge from an assumption of independence between extreme events.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70113","usgsCitation":"Hammond, J., Anderson, B., Simeone, C., Brunner, M., Munoz-Castro, E., Archfield, S.A., Magee, E., and Armitage, R., 2025, Hydrological whiplash: Highlighting the need for better understanding and quantification of sub-seasonal hydrological extreme transitions: Hydrological Processes, v. 39, no. 3, e70113, 9 p., https://doi.org/10.1002/hyp.70113.","productDescription":"e70113, 9 p.","ipdsId":"IP-174142","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":484020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Bailey","contributorId":352305,"corporation":false,"usgs":false,"family":"Anderson","given":"Bailey","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simeone, Caelan 0000-0003-3263-6452","orcid":"https://orcid.org/0000-0003-3263-6452","contributorId":221008,"corporation":false,"usgs":true,"family":"Simeone","given":"Caelan","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brunner, Manuela","contributorId":352306,"corporation":false,"usgs":false,"family":"Brunner","given":"Manuela","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munoz-Castro, Eduardo","contributorId":352307,"corporation":false,"usgs":false,"family":"Munoz-Castro","given":"Eduardo","affiliations":[{"id":40606,"text":"WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland","active":true,"usgs":false}],"preferred":false,"id":930717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":930714,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magee, Eugene","contributorId":352308,"corporation":false,"usgs":false,"family":"Magee","given":"Eugene","affiliations":[{"id":84169,"text":"UK Centre for Ecology & Hydrology (UKCEH)","active":true,"usgs":false}],"preferred":false,"id":930718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Armitage, Rachael","contributorId":352309,"corporation":false,"usgs":false,"family":"Armitage","given":"Rachael","affiliations":[{"id":84169,"text":"UK Centre for Ecology & Hydrology (UKCEH)","active":true,"usgs":false}],"preferred":false,"id":930719,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266530,"text":"70266530 - 2025 - A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales","interactions":[],"lastModifiedDate":"2025-05-09T14:47:14.01538","indexId":"70266530","displayToPublicDate":"2025-03-19T09:42:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales","docAbstract":"The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as ‘inconclusive’ and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling for Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence of Pd at bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM’s results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM’s estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had been Pd positive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding of Pd dynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-93865-x","usgsCitation":"Gridder, J., Udell, B.J., Reichert, B., Foster, J., Kendall, W.L., Cheng, T., and Frick, W.F., 2025, A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales: Scientific Reports, v. 15, 9423, 10 p., https://doi.org/10.1038/s41598-025-93865-x.","productDescription":"9423, 10 p.","ipdsId":"IP-166127","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490111,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-93865-x","text":"Publisher Index Page"},{"id":485644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.26363777562113,\n 49.48504400263704\n ],\n [\n -97.26363777562113,\n 32.49418643417637\n ],\n [\n -70.38881830989425,\n 32.49418643417637\n ],\n [\n -70.38881830989425,\n 49.48504400263704\n ],\n [\n -97.26363777562113,\n 49.48504400263704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Gridder, John F.","contributorId":354814,"corporation":false,"usgs":false,"family":"Gridder","given":"John F.","affiliations":[{"id":84669,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":936476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udell, Bradley James 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":271174,"corporation":false,"usgs":true,"family":"Udell","given":"Bradley","email":"","middleInitial":"James","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":936477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":936478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Jeffery T.","contributorId":351633,"corporation":false,"usgs":false,"family":"Foster","given":"Jeffery T.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":936479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, William Louis 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":257230,"corporation":false,"usgs":false,"family":"Kendall","given":"William","email":"","middleInitial":"Louis","affiliations":[{"id":51981,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, 201 J.V.K. Wagar Building 1484 Campus Delivery, Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":936480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheng, Tina L.","contributorId":127716,"corporation":false,"usgs":false,"family":"Cheng","given":"Tina L.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":936481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frick, Winifred F. 0000-0002-9469-1839","orcid":"https://orcid.org/0000-0002-9469-1839","contributorId":337076,"corporation":false,"usgs":false,"family":"Frick","given":"Winifred","email":"","middleInitial":"F.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":936482,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270681,"text":"70270681 - 2025 - A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee","interactions":[],"lastModifiedDate":"2025-08-25T13:35:28.429518","indexId":"70270681","displayToPublicDate":"2025-03-19T09:36:42","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-166-2025","title":"A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee","docAbstract":"We have developed a comprehensive database for freshwater mussels for the Duck River drainage in Tennessee, including its largest tributary, the Buffalo River. This database is intended to serve as an expandable template that could be applied statewide. The Duck River is one of the most biologically diverse rivers in the world, with historically over 70 mussel species, and it has been selected as a priority watershed by multiple management and conservation entities. The database for this system compiles over 7,000 mussel records, spanning 200 years, from multiple Federal, State, academic, and private entities, representing 77 native species. The database is spatially explicit and includes temporal and methodological data for each record, and notes of negative survey data were made when possible. The database can facilitate the creation of distribution maps for each species and temporal maps of species richness to show watershed-wide trends. This project addresses the present lack of a centralized mussel database in Tennessee for a critical system. It will be available to facilitate species status assessments, inform conservation planning, and serve as a model for similar databases for other Tennessee watersheds.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css36499787","usgsCitation":"Womble, K.I., and Rosenberger, A.E., 2025, A comprehensive freshwater mussel database for the Duck River Drainage, Tennessee: Cooperator Science Series CSS-166-2025, ii, 100 p., https://doi.org/10.3996/css36499787.","productDescription":"ii, 100 p.","ipdsId":"IP-174003","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496393,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/css36499787","text":"Publisher Index Page"},{"id":494515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Duck River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88,\n 36.15\n ],\n [\n -88,\n 35\n ],\n [\n -86,\n 35\n ],\n [\n -86,\n 36.15\n ],\n [\n -88,\n 36.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Womble, Kristen Irwin","contributorId":360120,"corporation":false,"usgs":false,"family":"Womble","given":"Kristen","middleInitial":"Irwin","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":946812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":946813,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70264714,"text":"70264714 - 2025 - Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2025-03-20T14:36:34.442104","indexId":"70264714","displayToPublicDate":"2025-03-19T09:32:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin","docAbstract":"Salinity levels in streams and tributaries of the Colorado River Basin have been a major concern for the United States and Mexico for over 50 years as the water is used by millions of people for domestic and industrial purposes. Recently, the United States Geological Survey expanded stream monitoring networks including the number of sites where continuous (15-min) specific conductance is measured in the Colorado River Headwaters and Gunnison River Basin located east of the Colorado-Utah state line (hereafter, UCOL). The purpose of this study is to apply a proxy method to determine salinity and total dissolved solids concentrations from specific conductance and major-ion water type that is applicable to monitoring sites in the UCOL. Within the UCOL, carbonate rich waters originate from high-elevation mountain regions in the eastern UCOL, calcium sulfate rich waters are mainly found in the western half of the UCOL including the Gunnison River Basin, and waters of variable composition are found along the lower reaches of the Colorado River and Eagle River. It was found that the chemistry of sites with variable composition changes seasonally and is impacted by both geogenic and anthropogenic processes, potentially including seasonal application of deicing road salt. The specific conductance – water type proxy can be used to reliably (±10 %) predict salinity and total dissolved solids at 66 monitoring sites in the UCOL. The method is rapid, can generate high-resolution measurements, is cost-effective, and greatly expands the utility of specific conductance measurements. Furthermore, the high-resolution estimates provide an accurate approach to determining long-term salinity loads as short-term events are accurately accounted for.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2025.106358","usgsCitation":"McCleskey, R., Cravotta, C., Miller, M., Chapin, T.W., Tillman, F.D., and Keith, G.L., 2025, Specific conductance and water type as a proxy model for salinity and total dissolved solids measurements in the Upper Colorado River Basin: Applied Geochemistry, v. 184, 106358, 11 p., https://doi.org/10.1016/j.apgeochem.2025.106358.","productDescription":"106358, 11 p.","ipdsId":"IP-170952","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":483579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.8482146743099,\n 40.404889992338354\n ],\n [\n -109.03080773170848,\n 40.404889992338354\n ],\n [\n -109.03080773170848,\n 38.16700844876755\n ],\n [\n -104.8482146743099,\n 38.16700844876755\n ],\n [\n -104.8482146743099,\n 40.404889992338354\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":931414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":338312,"corporation":false,"usgs":false,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":81112,"text":"Cravotta Geochemical Consulting","active":true,"usgs":false}],"preferred":false,"id":931415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":931416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapin, Tanner William 0000-0003-3905-3241","orcid":"https://orcid.org/0000-0003-3905-3241","contributorId":297923,"corporation":false,"usgs":true,"family":"Chapin","given":"Tanner","email":"","middleInitial":"William","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931419,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266489,"text":"70266489 - 2025 - Spatial variation in landlocked Atlantic Salmon smolt survival associated with dam passage, avian predation, and stocking location","interactions":[],"lastModifiedDate":"2025-05-28T14:56:33.619943","indexId":"70266489","displayToPublicDate":"2025-03-19T09:24:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variation in landlocked Atlantic Salmon smolt survival associated with dam passage, avian predation, and stocking location","docAbstract":"We evaluated survival differences between upstream and downstream stocking for landlocked Atlantic Salmon Salmo salar smolts in a tributary to Lake Champlain.
We radio-tagged smolts and stocked them concurrently with 22,000 smolts at two release sites in 2 years. The downstream location (DS, river kilometer 16, no dam passage) was a historically used site in a dam tailrace, whereas the upstream site (US, river kilometer 27, two dams to pass) was in a side channel and stocked for the first time. We estimated survival, counted birds during stocking, and searched nesting colonies for transmitters.
Within stocking reaches, survival per kilometer for the DS release group was markedly lower than that for the US group (US 2021 and 2022 = 0.98, 0.98, respectively; DS 2021 and 2022 = 0.82, 0.69, respectively). At the DS site, we documented a tenfold increase in avian predators following stocking, whereas no increase was detected at the US site. Passage was >96% at both dams, but postpassage survival (per kilometer) was much lower at the second dam (2021 = 0.78, 2022 = 0.82) compared to the first dam (2021 = 0.96, 2022 = 0.97). Surprisingly, cumulative survival to Lake Champlain was higher for fish that were released upstream in 2022 (US = 43%; DS = 32%) despite dam passage and additional migratory distance. At least 20% (2021) and 7% (2022) of successful migrants were later consumed by birds in the river delta or in Lake Champlain.
Upstream stocking did not consistently result in lower cumulative survival, likely due to predators habituated to annually reoccurring stocking in a dam tailrace that increased stocking-related mortality at the DS release site. We highlight the importance of evaluating historically used stocking sites, as substantial loss of smolts could be avoided by simple changes to stocking practices. Avian predation was a major source of mortality, necessitating further studies to understand and address survival issues within Lake Champlain.
Seasonal snow is an important source of drinking water and recreation, and for agriculture in the Rocky Mountain region. Monitoring snow-water quality can inform on the effects to the albedo and energy balance of the snowpack, and the sources of natural and anthropogenic aerosol and gases. This study analyzed metals in the seasonal snowpack from water year (WY) 2018 for 49 sites. Calcium, lanthanum, and cerium concentrations support the importance of mineral dust to the southern Rocky Mountains. Mercury (Hg), zinc (Zn), and cadmium (Cd) concentrations showed a similar spatial pattern to mineral dust, whereas antimony (Sb) concentrations were highest in the northern Rocky Mountains. To assess the relative contributions from dust versus anthropogenic contaminant sources, enrichment factors (EF) were calculated, with values above 10 indicating anthropogenic contamination. For Cd, Hg, Sb, and Zn, EF values exceeded 10 at northern sites. These observations were compared to spatial trends of EF values of Hg from WY2009 to WY2018, regional monitoring networks, and back trajectory analyses. The agreement between these datasets revealed temporally consistent contaminant sources and/or transport processes to the northern Rocky Mountains snowpack. Sources include current and historical mining and smelting in the region. Strategies to limit the emissions of these metals to the Northern Rockies could benefit from focusing on remediation of contaminated sites, and continued monitoring and mitigation of active mining and smelting.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2025.126094","usgsCitation":"Arienzo, M., Gleason, K., Sexstone, G., Sexauer Gustin, M., Schwan, M., Choma, N., Dunham-Cheatham, S., McConnell, J.R., Weisberg, P., and Csank, A., 2025, Latitudinal gradients of snow contamination in the Rocky Mountains associated with anthropogenic sources: Environmental Pollution, v. 373, 126094, 12 p., https://doi.org/10.1016/j.envpol.2025.126094.","productDescription":"126094, 12 p.","ipdsId":"IP-173899","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":488496,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2025.126094","text":"Publisher Index Page"},{"id":484909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado , Idaho, Montana, New Mexico, Utah, Wyoming","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116,\n 49\n ],\n [\n -116,\n 36\n ],\n [\n -105,\n 36\n ],\n [\n -105,\n 49\n ],\n [\n -116,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"373","noUsgsAuthors":false,"publicationDate":"2025-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Arienzo, Monica","contributorId":191065,"corporation":false,"usgs":false,"family":"Arienzo","given":"Monica","affiliations":[],"preferred":false,"id":934289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleason, Kelly","contributorId":244890,"corporation":false,"usgs":false,"family":"Gleason","given":"Kelly","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":934290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sexauer Gustin, Mae","contributorId":353670,"corporation":false,"usgs":false,"family":"Sexauer Gustin","given":"Mae","affiliations":[{"id":84456,"text":"University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934292,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwan, Melissa","contributorId":353671,"corporation":false,"usgs":false,"family":"Schwan","given":"Melissa","affiliations":[{"id":84456,"text":"University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934293,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Choma, Nicole","contributorId":353672,"corporation":false,"usgs":false,"family":"Choma","given":"Nicole","affiliations":[{"id":84456,"text":"University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934294,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunham-Cheatham, Sarrah","contributorId":353673,"corporation":false,"usgs":false,"family":"Dunham-Cheatham","given":"Sarrah","affiliations":[{"id":84456,"text":"University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934295,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McConnell, Joseph R. 0000-0001-9051-5240","orcid":"https://orcid.org/0000-0001-9051-5240","contributorId":288526,"corporation":false,"usgs":false,"family":"McConnell","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":934296,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weisberg, Peter","contributorId":225093,"corporation":false,"usgs":false,"family":"Weisberg","given":"Peter","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":934297,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Csank, Adam","contributorId":295955,"corporation":false,"usgs":false,"family":"Csank","given":"Adam","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":934298,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70264723,"text":"70264723 - 2025 - Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures","interactions":[],"lastModifiedDate":"2025-07-09T15:58:44.092141","indexId":"70264723","displayToPublicDate":"2025-03-19T07:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures","docAbstract":"We use the deterministic earthquake simulator RSQSim to generate complex sequences of ruptures on fault systems used for hazard assessment. We show that the source motions combined with a wave propagation code create surface ground motions that fall within the range of epistemic uncertainties for the Next Generation Attenuation‐West2 set of empirical models. We show the model is well calibrated where there are good data constraints, and has good correspondence in regions with fewer data constraints. We show magnitude, distance, and mechanism dependence all arising naturally from the same underlying friction. The deterministic physics‐based approach provides an opportunity for better understanding the physical origins of ground motions. For example, we find that reduced stress drops in shallow layers relative to constant stress drop with depth lead to peak ground velocities in the near field that better match empirical models. The simulators may also provide better extrapolations into regimes that are poorly empirically constrained by data because physics, rather than surface shaking data parameterizations, is underlying the extrapolations. Having shown the model is credible, we apply it to a problem where observations are lacking. We examine the case of crustal faults above a shallow subduction interface seen to break coseismically in simulations of the New Zealand fault system. These types of events were left out of consideration in the most recent New Zealand national seismic hazard model due to the modeling complexity and lack of observational data to constrain ground‐motion models (GMMs). Here, we show that in the model, by breaking up the coseismic crustal and interface rupturing fault motions into two separate subevents, and then recombining the resulting ground‐motion measures in a square‐root‐of‐sum‐of‐squares incoherent manner, we reproduce well the ground‐motion measures from the full event rupture. This provides a new method for extrapolating GMMs to more complex multifault ruptures.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240141","usgsCitation":"Shaw, B.E., Milner, K., and Goulet, C.A., 2025, Deterministic physics-based earthquake sequence simulators match empirical ground-motion models and enable extrapolation to data poor regimes: Application to multifault multimechanism ruptures: Seismological Research Letters, v. 96, no. 4, p. 2431-2444, https://doi.org/10.1785/0220240141.","productDescription":"14 p.","startPage":"2431","endPage":"2444","ipdsId":"IP-170334","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483583,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaw, Bruce E.","contributorId":194146,"corporation":false,"usgs":false,"family":"Shaw","given":"Bruce","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":931438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin Ross 0000-0002-9118-6378","orcid":"https://orcid.org/0000-0002-9118-6378","contributorId":352491,"corporation":false,"usgs":true,"family":"Milner","given":"Kevin Ross","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":931439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goulet, Christine A 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":336587,"corporation":false,"usgs":true,"family":"Goulet","given":"Christine","email":"","middleInitial":"A","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":931440,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271961,"text":"70271961 - 2025 - Effects of invasive American bullfrogs and their removal on Northwestern pond turtles","interactions":[],"lastModifiedDate":"2025-09-26T14:56:47.95774","indexId":"70271961","displayToPublicDate":"2025-03-19T07:51:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Effects of invasive American bullfrogs and their removal on Northwestern pond turtles","docAbstract":"The American bullfrog (Rana catesbeiana) is an invasive species globally significant for its role as a generalist predator in freshwater systems. Native turtles are among the species eaten by bullfrogs, and turtle populations are slow to recover from this impact. We examined the effects of bullfrogs and their removal on Northwestern pond turtles (Actinemys marmorata) at four sites in Yosemite National Park. From 2016 to 2022, we monitored turtle populations in two sites where bullfrogs were present and two where they have been absent. We removed 12,317 bullfrogs, larvae, and whole egg masses from one site and 4067 from the other, reaching near complete eradication by 2019. We captured just large adult turtles where bullfrogs were present compared with all sizes where bullfrogs were absent. Prior to near complete eradication, juvenile turtles were only found with bullfrogs when they were recovered from bullfrog stomachs. Turtles at bullfrog present sites were 26–36 % larger and 76–97 % heavier than turtles from bullfrog absent sites. Turtle abundance and densities were also 2–100 times higher at bullfrog absent sites. We captured the first juvenile turtles at bullfrog present sites only after reaching near complete bullfrog eradication in 2019. Altogether, our study shows a prolonged lack of juvenile turtle recruitment where bullfrogs were present but offers hope that bullfrog control may succeed in recovering turtle populations by easing predation pressure on hatchlings and juveniles. Our results indicate that bullfrog eradication efforts may be necessary to ensure persistence of at-risk species like native turtles.
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Each US-RIIS record has information on taxonomy, dates of introduction (where available; version 2.0 for 47 percent of the records), invasion status (invasive or introduced), use for biocontrol (if applicable), and a citation for the information source(s). The US-RIIS was designed to be compatible with country contributions to the Global Register of Introduced and Invasive Species Initiative, which compiles annotated and verified country-wide inventories of introduced and invasive species. Within the US-RIIS, the density of introduced species per 10,000 square kilometers among the localities ranges markedly, from 3 in Alaska to 1,988 in Hawaii (11 in the L48). The comparative taxonomic composition of the largest groups in the sublists also varies: the Alaska sublist has a majority of flowering plants; Hawaii has a majority of insects; and the L48 is about equally divided between insects and flowering plants. 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U.S. Geological Survey
Box 25046, MS 302
Denver, CO 80225-0046
The importance of connectivity for freshwater organisms is widely recognised, yet in-stream barriers associated with population declines and increased risk of extinction remain globally ubiquitous. Despite their negative consequences, these barriers can protect aquatic communities by limiting the spread of invasive species, leading to conflicting management goals in some regions. Selective fish passage is a solution for the conflicting goals of passing native, desirable species while restricting the spread of invasives. Approaches that can target groups of species sharing similar attributes (i.e. guilds) are likely to be more efficient than those that target species individually, particularly in taxonomically diverse systems. We explored the guild structure of 220 Great Lakes freshwater fishes based on morphological, phenological, physiological and behavioural attributes associated with passage and movement. We identified five distinct guilds as well as the attributes most important for defining these groupings: maximum total length, trophic level, relative eye size, spawning temperature, spawning season, presence/absence of ampullary electroreceptors and the presence/absence of hearing specialisations. The approaches outlined in this work can be generalised to enhance selective fish passage in aquatic ecosystems worldwide.
","language":"English","publisher":"Wiley","doi":"10.1111/faf.12888","usgsCitation":"Benoit, D., Zielinski, D., Swanson, R., Jackson, D., McLaughlin, R.L., Castro-Santos, T., Goodwin, R., Pratt, T., and Muir, A., 2025, Designing sortable guilds for multispecies selective fish passage: Fish and Fisheries, v. 26, no. 3, p. 414-424, https://doi.org/10.1111/faf.12888.","productDescription":"11 p.","startPage":"414","endPage":"424","ipdsId":"IP-171460","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488341,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/faf.12888","text":"Publisher Index Page"},{"id":483580,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Benoit, David","contributorId":352446,"corporation":false,"usgs":false,"family":"Benoit","given":"David","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":931311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zielinski, Daniel","contributorId":245798,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":931312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, Reid G","contributorId":264164,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid G","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":931313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Donald","contributorId":352449,"corporation":false,"usgs":false,"family":"Jackson","given":"Donald","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":931314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLaughlin, Robert L.","contributorId":143707,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":931315,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":931316,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goodwin, R. Andrew 0000-0002-6846-0287","orcid":"https://orcid.org/0000-0002-6846-0287","contributorId":352492,"corporation":false,"usgs":false,"family":"Goodwin","given":"R. Andrew","affiliations":[{"id":37304,"text":"U.S. Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":931317,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pratt, Thomas C.","contributorId":177870,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas C.","affiliations":[],"preferred":false,"id":931318,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Muir, Andrew M.","contributorId":103933,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew M.","affiliations":[],"preferred":false,"id":931319,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272248,"text":"70272248 - 2025 - Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks","interactions":[],"lastModifiedDate":"2025-11-20T16:04:16.55833","indexId":"70272248","displayToPublicDate":"2025-03-18T08:53:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Decadal stability in stream fish communities and contemporary ecological drivers of species occupancy in two Appalachian U.S. National Parks","docAbstract":"Objective
Although conserving fish biodiversity in lotic systems is challenging, protected areas can provide refuge from certain environmental stressors. In the Appalachian region, USA, the National Park Service manages Delaware Water Gap National Recreation Area (DEWA) and New River Gorge National Park & Preserve (NERI), which contain abundant and diverse freshwater resources. To assess the effectiveness of these protected areas in conserving stream fishes, we evaluated decadal changes and ecological drivers of species occupancy and detection.
Methods
Using fish assemblage data from backpack electrofishing surveys conducted in both parks during 2013–2014 and 2022–2023, we quantified temporal differences in species occupancy and detection probabilities using a Bayesian hierarchical multispecies occupancy modeling approach. For the 2022–2023 survey, we included habitat variables as predictors of occupancy and detection.
Results
Community composition and occupancy probabilities for species in both parks remained similar through time, with the most recent occupancy estimates ranging from 0.07 (90% CI = 0.02, 0.14) for Variegate Darter Etheostoma variatum and Rainbow Darter E. caeruleum to 0.73 (90% credible interval = 0.59, 0.85) for Blacknose Dace Rhinichthys atratulus. Changes in occupancy were more prominent at Delaware Water Gap National Recreation Area than New River Gorge National Park & Preserve, with Yellow Perch Perca flavescens having a posterior mean difference of −0.17 [90% credible interval = −0.35, −0.01] and American Eel Anguilla rostrata having a high posterior probability (>80%) of occupancy increasing by at least 1%. Habitat variables were related to community structure, but effects varied in significance, magnitude, and direction among species and parks. Conversely, species-specific detection probabilities were comparatively less affected by environmental and sampling effort predictors.
Conclusions
Between 2013 and 2023, occupancy estimates for 44 fish species across two protected, ecologically diverse landscapes remained relatively stable. Furthermore, we highlight the efficacy of national parks in maintaining freshwater fish biodiversity amidst rapid global change.
Many species have a variety of adaptations to winter weather, but these adaptations could become maladaptive if winter snowfall and temperatures are more variable. Snowshoe hares (Lepus americanus) molt from a brown summer coat to a white winter coat, but reductions in snow cover could result in phenotypic mismatch, which in turn could reduce survival. Hare populations near the southern extent of their range might be especially sensitive to phenotypic mismatch because of variable winter weather, but variation in winter coat coloration could allow for these populations to persist in inconsistent snow cover conditions. Using capture data (n = 59 individual hares) spanning 8 years, we document the prevalence of three atypical winter coat color phenotypes (brown bodies, brown-ringed eyes, and brown ears) in a snowshoe hare population in Pennsylvania. The majority of hares in our study (84.7%) exhibited at least one of these atypical winter phenotypes, with a high probability of hares having brown-ringed eyes or brown ears, and four hares remaining brown during the winter. The presence and high prevalence of non-white winter phenotypes could be beneficial for hares in this population if winters are mild with low snow cover. If these phenotypes have a genetic basis, there may be evolutionary potential for hares to persist near the southern extent of their range, even in the face of changing winters.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70217","usgsCitation":"Gigliotti, L., Boyd, E.S., and Diefenbach, D.R., 2025, Atypical winter coat coloration of snowshoe hares near the southern extent of their range: Ecosphere, v. 16, no. 3, e70217, 7 p., https://doi.org/10.1002/ecs2.70217.","productDescription":"e70217, 7 p.","ipdsId":"IP-170108","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":492471,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70217","text":"Publisher Index Page"},{"id":492128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Monroe County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.4944445855176,\n 41.110769966630414\n ],\n [\n -75.4944445855176,\n 40.90104058418078\n ],\n [\n -75.14502818574874,\n 40.90104058418078\n ],\n [\n -75.14502818574874,\n 41.110769966630414\n ],\n [\n -75.4944445855176,\n 41.110769966630414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Gigliotti, Laura Christine 0000-0002-6390-4133","orcid":"https://orcid.org/0000-0002-6390-4133","contributorId":348259,"corporation":false,"usgs":true,"family":"Gigliotti","given":"Laura Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Emily S.","contributorId":342971,"corporation":false,"usgs":false,"family":"Boyd","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":942732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942733,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274323,"text":"70274323 - 2025 - Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin","interactions":[],"lastModifiedDate":"2026-03-26T16:48:00.112596","indexId":"70274323","displayToPublicDate":"2025-03-17T11:37:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin","docAbstract":"Historical and ongoing anthropogenic activities coupled with advancements in analytical techniques have led to the detection of large numbers of contaminants in the Laurentian Great Lakes. Consequently, identifying and prioritizing chemicals likely to cause ecological harm represents a challenge for natural resource managers. Previous prioritization efforts have focused on contaminants in sediment, water, and passive samplers, which may not be representative of compounds that bioaccumulate in aquatic organisms. Consequently, this study adopted a stepwise method to prioritize chemicals of potential concern detected in dreissenid mussels from samples collected across the Great Lakes from 2009–2018. The stepwise method considered environmental fate, detection frequency, and exceedance of toxicity quotients based on ecotoxicological effect concentrations. Overall, 153 compounds out of 267 analyzed were detected in dreissenid mussels, 47 of which had water quality effect concentrations, 56 had apical effect concentrations (Tier 1 ECOTOX or apical screening), 17 had nonapical effect concentrations (Tier 2 ECOTOX, Cytotoxic Burst, and ToxCast) and 33 had estimated effect concentrations (quantitative structure-activity relationship, estimated screening, and pharmacological potency). Of the compounds with water quality effect concentrations, nine were designated as high priority, including the herbicide atrazine and five polycyclic aromatic hydrocarbons that were previously identified as potentially hazardous within other matrices. Similar contaminants were identified as high priority in a related study of native unionid mussels in the Great Lakes. A total of 27 compounds were low priority, suggesting that these contaminants do not warrant further action based on this dataset. Overall, these findings will facilitate the development of management strategies to mitigate the effects of contaminants on aquatic organisms within the Great Lakes.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf072","usgsCitation":"Fuller, N., Kimbrough, K., Edwards, M., Maloney, E., Corsi, S., Pronschinske, M.A., DeCicco, L., Frisch, J.R., Baldwin, A.K., Hummel, S.L., Vinas, N., and Villeneuve, D.L., 2025, Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin: Environmental Toxicology and Chemistry, v. 44, no. 7, p. 2070-2087, https://doi.org/10.1093/etojnl/vgaf072.","productDescription":"18 p.","startPage":"2070","endPage":"2087","ipdsId":"IP-153495","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgaf072","text":"Publisher Index 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The current (2019) biosecurity protocols used for prevention were evaluated, and new biodiversity surveys were completed for terrestrial vegetation and arthropods and included the first formal reptile surveys. Results from field efforts add to existing knowledge and may identify new species arrivals to Wake.
One goal of this project was to update and compile established species information for the atoll and create species identification guides for the three taxonomic groups surveyed. We made these flora and fauna species identification guides by compiling results of the recent (2019) and historical surveys. The guides can be used as resident desktop references, as a baseline for assessing future natural resource surveys, and to assist with guiding management actions. We refer herein to biosecurity and integrated pest management plan materials, which we created simultaneously to inform current (2019) biosecurity and to identify some of the top invasive species at Wake. This study was done in cooperation with the USAF, and surveys were performed for the 611th Civil Engineer Squadron Natural Resources Program, ACES PROJECT #YGFZ170002 under agreement number F2MUAA7116GW02 between the USAF and the USGS Western Ecological Research Center.
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The history-matching approach to parameter estimation with models enables a powerful offshoot analysis of data worth—using the uncertainty of a model forecast as a metric for the worth of data. Adding observation data will either have no impact on forecast uncertainty or will reduce it. Removing existing data will either have no impact on forecast uncertainty or will increase it. The history-matching framework makes it possible to perform this quantitative analysis leveraging the connections among observations, model parameters, and model forecasts. We show this behavior on a specific groundwater flow model of the Mississippi Alluvial Plain and show where the analysis can be informative for considering the potential design of an observation network based on existing or potential observations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255007","usgsCitation":"Fienen, M.N., Schachter, L.A., and Hunt, R.J., 2025, A model uncertainty quantification protocol for evaluating the value of observation data: U.S. Geological Survey Scientific Investigations Report 2025–5007, 12 p., https://doi.org/10.3133/sir20255007.","productDescription":"vi; 12 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171702","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":483399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5007/sir20255007.pdf","text":"Report","size":"7.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025–5007"},{"id":483398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5007/coverthb.jpg"},{"id":483404,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255007/full","text":"Report"},{"id":483400,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5007/sir20255007.XML","text":"Report","description":"SIR 2025–5007"},{"id":483403,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5007/images"},{"id":492790,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118495.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, Wisconsin 53726
The impacts of white-nose syndrome (WNS) on many bat species in eastern North America have been well documented because of the length of time that the causative agent, Pseudogymnoascus destructans (Pd), has been present and the ability to monitor bat hibernacula in that region. However, the disease outcomes for bat species in western North America are less known because of the more recent arrival of Pd and the challenges associated with monitoring hibernating bat populations in parts of the western US. We report on mortality events involving Yuma myotis (Myotis yumanensis) bats at two locations in King and Benton counties, Washington, US, that were attributed to WNS during the late winters of 2020–21 and 2024, respectively. All bats that were grossly examined had depleted subcutaneous white adipose tissue, tested positive for the presence of Pd, had histopathologic lesions consistent with WNS, and did not exhibit evidence of other disease processes that may have contributed to death. Mortality was likely higher than what was documented because the locations of the Pd-contaminated hibernacula from which the bats originated were inaccessible or unknown and thus could not be surveyed. These findings indicate that Yuma myotis may be highly susceptible to WNS, and close monitoring is warranted to understand how WNS will affect population trends in this (and other) western bat species.
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Center","active":true,"usgs":true}],"preferred":true,"id":931975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":931976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berlowski-Zier, Brenda M. 0000-0002-7922-8352 bberlowski-zier@usgs.gov","orcid":"https://orcid.org/0000-0002-7922-8352","contributorId":4288,"corporation":false,"usgs":true,"family":"Berlowski-Zier","given":"Brenda","email":"bberlowski-zier@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":931977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"George, Kyle 0000-0001-9898-4236 kgeorge@usgs.gov","orcid":"https://orcid.org/0000-0001-9898-4236","contributorId":173441,"corporation":false,"usgs":true,"family":"George","given":"Kyle","email":"kgeorge@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":931978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haman, Katherine H.","contributorId":173443,"corporation":false,"usgs":false,"family":"Haman","given":"Katherine","email":"","middleInitial":"H.","affiliations":[{"id":27230,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":931979,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ballmann, Anne 0000-0002-0380-056X 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endangered species. Mexican wolves (Canis lupus baileyi) are an endangered subspecies of gray wolves that historically occupied large portions of the American Southwest and Mexico. Recently, the Mexican wolf population in the United States has been growing rapidly and traditional approaches for population monitoring (e.g., capture and radio collaring) are becoming difficult and expensive as wolves expand into new areas. We developed predictive models of pup-rearing habitat (i.e., den and rendezvous sites) that could help guide future population monitoring efforts. We located 255 den sites and 129 rendezvous sites in Arizona and New Mexico, USA (1998–2023) using tracking collars and site visits. We sampled habitat conditions in wolf-occupied regions of Arizona and New Mexico and fit logistic regressions to these data following a use–available study design to estimate resource selection functions (RSF) for den and rendezvous sites. We hypothesized wolves would select areas that offered greater physical protection, lower human-disturbance, and access to reliable water sources for pup-rearing but that the relative importance of these features would differ between the denning and rendezvous site seasons. Mexican wolves selected den sites at higher elevations in steeper and rougher terrain that were closer to permanent waterbodies but farther from rural roads. Selection of rendezvous sites was also associated with higher elevations and proximity to waterbodies but varied with availability of green leaf biomass on the landscape. While still highly predictive, our rendezvous site model was less predictive than our den model (Spearman's correlation averaged 0.81 [SE = 0.05] vs. 0.90 [SE = 0.03], respectively), possibly because water and green leaf biomass are more spatially diffuse and variable because of monsoonal rains during the rendezvous site season. Our results suggest that terrain features associated with physical protection and access to reliable water were most important in characterizing suitable pup-rearing habitat for Mexican wolves. By predicting suitable den and rendezvous site habitat across portions of the Mexican Wolf Experimental Population Area, our models can help guide future population monitoring by reducing the total search area when surveying for wolves and increase the probability of detecting all members of a pack.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70017","usgsCitation":"Bassing, S., Oakleaf, J., Cain, J.W., Greenleaf, A., Gardner, C., and Ausband, D.E., 2025, Predicting pup-rearing habitat for Mexican wolves: Journal of Wildlife Management, v. 89, no. 5, e70017, 19 p., https://doi.org/10.1002/jwmg.70017.","productDescription":"e70017, 19 p.","ipdsId":"IP-169774","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486238,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":488960,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70017","text":"Publisher Index Page"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.15656068155297,\n 37.15236143729469\n ],\n [\n -114.79334387076136,\n 36.19839033323856\n ],\n [\n -114.82092420356022,\n 32.28431539821898\n ],\n [\n -111.22371663071222,\n 31.529018437535207\n ],\n [\n -108.37781874007106,\n 31.259432273304338\n ],\n [\n -108.00163404937481,\n 31.805280742585737\n ],\n [\n -103.03648352957026,\n 31.93273826397835\n ],\n [\n -103.13422840316065,\n 37.15236143729469\n ],\n [\n -114.15656068155297,\n 37.15236143729469\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bassing, Sarah B.","contributorId":355638,"corporation":false,"usgs":false,"family":"Bassing","given":"Sarah B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":937834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oakleaf, John K.","contributorId":355639,"corporation":false,"usgs":false,"family":"Oakleaf","given":"John K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greenleaf, Allison R.","contributorId":355640,"corporation":false,"usgs":false,"family":"Greenleaf","given":"Allison R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Colby M.","contributorId":355641,"corporation":false,"usgs":false,"family":"Gardner","given":"Colby M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937839,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265779,"text":"70265779 - 2025 - A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records","interactions":[],"lastModifiedDate":"2025-04-15T15:17:05.760533","indexId":"70265779","displayToPublicDate":"2025-03-17T10:11:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records","docAbstract":"Great Aleutian underthrusting earthquakes produced destructive tsunamis impacting Hawaiʻi in 1946 and 1957. Prior modeling of the 1957 tsunami deposit and runup records on eastern Aleutian and Hawaiian Islands jointly with tide-gauge observations across the Pacific Ocean constrained a rupture model with shallow slip up to 26 m along 600 km of the plate boundary. Here we implement this modeling approach to older deposits and show alternating deep and shallow megathrust slip up to 26, 32, and 22 m for great earthquakes along the same segment in the 18th, 15th, and 14th centuries. All three modeled prehistoric Aleutian earthquakes produce tsunami inundation in Hawaiʻi with the most severe, 14th century event having impacts exceeding the 1957 event. The along-dip variability of these four ruptures spanning seven centuries provides insights on earthquake cycles for engineering design and hazard assessment. The 15th century and 1957 rupture models provide evidence for recurrence of tsunami earthquakes, which can produce disproportionately large tsunamis for a given moment magnitude due to reduced rigidity in the shallow megathrust. The 14th and 18th century events likely ruptured deeper regions that did not slip in 1957, suggesting potential for corresponding deeper failure in the next great eastern Aleutian earthquake.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-025-57802-w","usgsCitation":"Yamazaki, Y., Cheung, K.F., Lay, T., La Selle, S., Witter, R., and Jaffe, B., 2025, A 700-year rupture sequence of great eastern Aleutian earthquakes from tsunami modeling of stratigraphic records: Nature Communications, v. 16, 2638, 16 p., https://doi.org/10.1038/s41467-025-57802-w.","productDescription":"2638, 16 p.","ipdsId":"IP-169333","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488253,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-57802-w","text":"Publisher Index Page"},{"id":484585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Hawaii","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -146.41033794940356,\n 60.59031062994006\n ],\n [\n -179.99,\n 60.59031062994006\n ],\n [\n -179.99,\n 18\n ],\n [\n -146.41033794940356,\n 18\n ],\n [\n -146.41033794940356,\n 60.59031062994006\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 172.7792582818936,\n 55.23104605282941\n ],\n [\n 172.7792582818936,\n 48.90879653399284\n ],\n [\n 179.99,\n 48.90879653399284\n ],\n [\n 179.99,\n 55.23104605282941\n ],\n [\n 172.7792582818936,\n 55.23104605282941\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Yamazaki, Yoshiki","contributorId":216792,"corporation":false,"usgs":false,"family":"Yamazaki","given":"Yoshiki","email":"","affiliations":[{"id":39517,"text":"University of Hawaii at Mano","active":true,"usgs":false}],"preferred":false,"id":933512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheung, Kwok Fai","contributorId":329690,"corporation":false,"usgs":false,"family":"Cheung","given":"Kwok","email":"","middleInitial":"Fai","affiliations":[{"id":78685,"text":"University of Hawai'i at Manoa","active":true,"usgs":false}],"preferred":false,"id":933513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lay, Thorne","contributorId":328838,"corporation":false,"usgs":false,"family":"Lay","given":"Thorne","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":933514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":933515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":933516,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":335664,"corporation":false,"usgs":false,"family":"Jaffe","given":"Bruce E.","affiliations":[{"id":80462,"text":"former USGS PCMSC employee","active":true,"usgs":false}],"preferred":false,"id":933517,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264717,"text":"70264717 - 2025 - Climate and dispersal ability limit future habitats for Gila monsters in the Mojave Desert","interactions":[],"lastModifiedDate":"2025-03-20T14:58:11.540958","indexId":"70264717","displayToPublicDate":"2025-03-17T09:50:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Climate and dispersal ability limit future habitats for Gila monsters in the Mojave Desert","docAbstract":"Describing future habitat for sensitive species can be helpful in planning conservation efforts to ensure species persistence under new climatic conditions. The Gila monster (Heloderma suspectum) is an iconic lizard of the southwestern United States. The northernmost range of Gila monsters is the Mojave Desert, an area experiencing rapid human population growth and urban sprawl. To understand current and potential future habitat for Gila monsters in the Mojave Desert, we fit ensemble species distribution models using known locations and current environmental variables known to be important to the species' biology. We then projected future suitable habitat under different climate forecasts based on IPCC emission scenarios. To ensure that Gila monsters would be able to disperse to newly suitable habitat, we fit Brownian Bridge movement models using telemetry data from two locations in Nevada. This model indicated that Gila monsters prefer to move through areas with a moderate slope and higher shrub cover. Modeled current suitable habitat for Gila monsters in Nevada was primarily in rugged bajadas and lower elevations at the bases of mountain ranges. Predictions of potential future habitat suggested that overall habitat suitability through 2082 would remain relatively stable throughout the study area in the lower emissions scenario, but in the high emissions scenario potential habitat is greatly reduced in many lower-elevation areas. Future habitat areas at higher elevations under the high emissions scenario showed moderate increases in suitability, though occupancy would likely be limited by Gila monster dispersal capabilities. Finally, we determined how well the protected area network of our study area encompassed future Gila monster habitat to highlight potential opportunities to protect this important species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71008","usgsCitation":"Hromada, S.J., Jones, J., Stalker, J., Wood, D.A., Vandergast, A.G., Tracy, C.R., Gienger, C., and Nussear, K.E., 2025, Climate and dispersal ability limit future habitats for Gila monsters in the Mojave Desert: Ecology and Evolution, v. 15, e71008, 15 p., https://doi.org/10.1002/ece3.71008.","productDescription":"e71008, 15 p.","ipdsId":"IP-166958","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71008","text":"Publisher Index Page"},{"id":483582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.33194255435204,\n 37.76713352893536\n ],\n [\n -117.13833621353872,\n 37.76713352893536\n ],\n [\n -117.13833621353872,\n 33.75898076102743\n ],\n [\n -113.33194255435204,\n 33.75898076102743\n ],\n [\n -113.33194255435204,\n 37.76713352893536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":931420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jason L.","contributorId":352480,"corporation":false,"usgs":false,"family":"Jones","given":"Jason L.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":931421,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stalker, Jocelyn B.","contributorId":352484,"corporation":false,"usgs":false,"family":"Stalker","given":"Jocelyn B.","affiliations":[{"id":84237,"text":"Austin Peay State University","active":true,"usgs":false}],"preferred":false,"id":931422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":931423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":931424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tracy, C. 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However, the organic content of these rocks has likely suffered from the radiation environment on the surface of Mars to an extent yet to be quantified. For the first time, a 1000 sols long ageing experiment was conducted at the surface of Mars, i.e. under actual Martian conditions, relying on the 100 % organic Ertalyte target carried by Perseverance. White at landing, the Ertalyte target has turned brown with time, while its Raman signal changed, with a modification of the background (its maximum has shifted from 1500 to 2000 cm−1) and a reduction of the contribution of the Raman signal of Ertalyte (by a factor of 5 over the first 500 sols). Given the intrinsic resistance of the Ertalyte to UV exposure, which is not anticipated for most Martian organic materials, these results suggest that exposure at the surface of Mars will make the detection of Martian organic molecules challenging.
","language":"English","publisher":"European Association of Geochemistry","doi":"10.7185/geochemlet.2509","usgsCitation":"Bernard, S., Beyssac, O., Manrique, J., Lopez Reyes, G., Ollila, A., Le Mouelic, S., Beck, P., Pilleri, P., Forni, O., Julve-Gonzales, S., Veneranda, M., Reyes Rodriguez, I., Madariaga Mota, J., Aramenda, J., Castro, K., Clave, E., Royer, C., Fornaro, T., Bousquet, B., Sharma, S., Johnson, J., Cloutis, E., Gabriel, T.S., Meslin, P., Gasnault, O., Cousin, A., Wiens, R., and Maurice, S., 2025, Ageing of organic materials at the surface of Mars: A Raman study aboard Perseverance: Geochemical Perspectives Letters, v. 34, p. 25-30, https://doi.org/10.7185/geochemlet.2509.","productDescription":"6 p.","startPage":"25","endPage":"30","ipdsId":"IP-169947","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":488337,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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