The U.S. Geological Survey—in cooperation with the San Antonio Water System and the Edwards Aquifer Authority—used data collected during four different periods (March 1955–August 1964, October 1995–September 1996, March 2001–June 2002, and March 2017–October 2022) as part of a new study to refine previously derived relations between the altitude of the water surface of Medina Lake and recharge to the Edwards aquifer and the upper zone of the Trinity aquifer in the form of seepage losses from Medina Lake and the immediately downstream Diversion Lake. Any seepage losses that occur within the conservation pools of Medina and Diversion Lakes infiltrate the Edwards aquifer and the upper zone of the Trinity aquifer as recharge. To quantify recharge to the Edwards aquifer and the upper zone of the Trinity aquifer from Medina and Diversion Lakes, daily water budgets were used to calculate monthly and annual recharge (method 1). A new statistical analysis culminated in a new log-log weighted least-squares (WLS) regression equation that relates recharge from Medina and Diversion Lakes to the Medina Lake stage. Recharge estimates obtained by using the new log-log WLS regression equation (method 2), as well as the recharge estimated by using a method published in 1978 (referred to as the “Puente method”) (method 3), were compared with the calculated recharge during March 2017–September 2022. During March 2017–September 2022, the WLS estimated recharge was 224,310 acre-feet, 0.5 percent less than the calculated recharge of 225,400 acre-feet. The Puente method estimated recharge was 342,080 acre-feet, about 52 percent more than the calculated recharge. The analysis of the three methods indicates that WLS estimated recharge provides a more accurate accounting of actual recharge to the Edwards aquifer and the upper zone of the Trinity aquifer compared to the Puente method.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2025.125810","usgsCitation":"Eggers, M., Sigler, W., Kiekover, N., Bradley, P., Smalling, K., Parker, A., Peterson, R., and LaFave, J., 2025, Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA: Environmental Pollution, v. 369, 125810, 17 p., https://doi.org/10.1016/j.envpol.2025.125810.","productDescription":"125810, 17 p.","ipdsId":"IP-167347","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":489772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2025.125810","text":"Publisher Index Page"},{"id":482274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Adam","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":927921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiekover, Nicklas 0009-0007-3910-9272","orcid":"https://orcid.org/0009-0007-3910-9272","contributorId":351129,"corporation":false,"usgs":false,"family":"Kiekover","given":"Nicklas","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":927922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":927923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":927924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parker, Albert E.","contributorId":203235,"corporation":false,"usgs":false,"family":"Parker","given":"Albert E.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":927925,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peterson, Robert K.D.","contributorId":351130,"corporation":false,"usgs":false,"family":"Peterson","given":"Robert K.D.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":927926,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFave, John","contributorId":351131,"corporation":false,"usgs":false,"family":"LaFave","given":"John","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":927927,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266342,"text":"70266342 - 2025 - A new groundwater energy transport model for the MODFLOW hydrologic simulator","interactions":[],"lastModifiedDate":"2025-05-05T14:11:27.139592","indexId":"70266342","displayToPublicDate":"2025-02-14T09:08:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"A new groundwater energy transport model for the MODFLOW hydrologic simulator","docAbstract":"Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13470","usgsCitation":"Morway, E.D., Provost, A.M., Langevin, C.D., Hughes, J.D., Russcher, M.J., Chen, C., and Lin, Y., 2025, A new groundwater energy transport model for the MODFLOW hydrologic simulator: Groundwater, v. 63, no. 3, p. 409-421, https://doi.org/10.1111/gwat.13470.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-172581","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":487945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13470","text":"Publisher Index Page"},{"id":485372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":935684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Provost, Alden M. 0000-0002-4443-1107 aprovost@usgs.gov","orcid":"https://orcid.org/0000-0002-4443-1107","contributorId":2830,"corporation":false,"usgs":true,"family":"Provost","given":"Alden","email":"aprovost@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russcher, Martijn J. 0000-0001-8799-6514","orcid":"https://orcid.org/0000-0001-8799-6514","contributorId":272524,"corporation":false,"usgs":false,"family":"Russcher","given":"Martijn","email":"","middleInitial":"J.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":935688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Chieh-Ying","contributorId":354439,"corporation":false,"usgs":false,"family":"Chen","given":"Chieh-Ying","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":935689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, Yu-Feng 0000-0001-6454-0901","orcid":"https://orcid.org/0000-0001-6454-0901","contributorId":302351,"corporation":false,"usgs":false,"family":"Lin","given":"Yu-Feng","email":"","affiliations":[{"id":65462,"text":"Illinois Water Resources Center, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":935690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263500,"text":"sir20245127 - 2025 - Groundwater age estimates for the Mississippi River Valley alluvial aquifer based on tracer data collected during 2018–20","interactions":[],"lastModifiedDate":"2025-07-21T18:22:10.201666","indexId":"sir20245127","displayToPublicDate":"2025-02-13T14:55:22","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":"2024-5127","displayTitle":"Groundwater Age Estimates for the Mississippi River Valley Alluvial Aquifer Based on Tracer Data Collected During 2018–20","title":"Groundwater age estimates for the Mississippi River Valley alluvial aquifer based on tracer data collected during 2018–20","docAbstract":"This study characterized groundwater age across the Mississippi River Valley alluvial aquifer (MRVA). Groundwater samples from 69 MRVA wells and 19 wells in Tertiary units of the Mississippi embayment aquifer system (MEAS) were analyzed for sulfur hexafluoride (SF6), tritium (3H), helium (He), and (or) carbon-14 of dissolved inorganic carbon (14C). The age distributions of 89 samples were estimated by fitting lumped parameter models to processed tracer concentrations with the U.S. Geological Survey software TracerLPM. Mean ages of MRVA groundwater samples ranged from 12 to 22,000 years, with a median of 140 years. Mean ages of MEAS groundwater samples ranged from 230 to 52,000 or more years, with a median of 13,500 years. The spatial distribution of MRVA groundwater ages was found to be influenced by depth, inflow of groundwater from deeper units, and soil saturated hydraulic conductivity. In parts of the MRVA, the spatial distribution of MRVA groundwater ages was found to be influenced by annual recharge and (or) annual groundwater pumpage.
Director, Lower Mississippi-Gulf Water Science Center, U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"In the arid Grand Canyon region, water resources are limited to primarily the Colorado River and associated tributaries and to groundwater in the form of seeps and springs. Groundwater resources in the region supply water for human use and support diverse and rich ecosystems in the locations immediately surrounding the seeps and springs. Throughout the region, uranium resources occur and may interact with water resources in both mined and unmined uranium deposits. There is a need to better understand groundwater in the region and the effects from uranium mining in order to better manage the limited water resources in the area. This Fact Sheet summarizes results from U.S. Geological Survey studies that were conducted on this topic from 2012 to 2023.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243055","issn":"2327-6916, 2327-6932","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Environmental Health Program","usgsCitation":"Beisner, K.R., Siebers, B.J., Tillman, F.D., and Walton-Day, K., 2025, Water resources related to breccia pipe uranium mining in the Grand Canyon region: U.S. Geological Survey Fact Sheet 2024–3055, 4 p., https://doi.org/10.3133/fs20243055.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-160657","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":481937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3055/coverthb.jpg"},{"id":481947,"rank":12,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225037","text":"USGS SIR 2022–5037","linkHelpText":"- Conceptual models of groundwater flow in the Grand Canyon region, Arizona"},{"id":481948,"rank":13,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1007/s10040-020-02193-z","text":"Journal Article","linkHelpText":"- Rethinking groundwater flow on the South Rim of the Grand Canyon, USA—Characterizing recharge sources and flow paths with environmental tracers"},{"id":481938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3055/fs20243055.pdf","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3055"},{"id":481939,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3055/fs20243055_printer-friendly.pdf","text":"Printer Friendly Supplemental File","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Printer Friendly FS 2024-3055"},{"id":481940,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3055/images"},{"id":481941,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3055/fs20243055.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2024-3055 XML"},{"id":483257,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243055/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3055 HTML"},{"id":481951,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243003","text":"USGS FS 2024–3003","linkHelpText":"- Balancing natural resource use and extraction of uranium and other elements in the Grand Canyon region"},{"id":481943,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2010/5025/","text":"USGS SIR 2010–5025","linkHelpText":"- Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona"},{"id":481944,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1144/geochem2023-007","text":"Journal Article","linkHelpText":"- Anthropogenic influence on groundwater geochemistry in Horn Creek watershed near the Orphan Mine in Grand Canyon National Park, Arizona, USA"},{"id":481945,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1016/j.ejrh.2023.101461","text":"Journal Article","linkHelpText":"- Utilizing anthropogenic compounds and geochemical tracers to identify preferential structurally controlled groundwater pathways influencing springs in Grand Canyon National Park, Arizona, USA"},{"id":481946,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1007/s10040-016-1494-8","text":"Journal Article","linkHelpText":"- Geochemistry and hydrology of perched groundwater springs—Assessing elevated uranium concentrations at Pigeon Spring relative to nearby Pigeon Mine, Arizona (USA)"},{"id":481949,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1371/journal.pone.0241502","text":"Journal Article","linkHelpText":"- Assessing uranium and select trace elements associated with breccia pipe uranium deposits in the Colorado River and main tributaries in Grand Canyon, USA"},{"id":481950,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.1038/s41598-021-01621-8","text":"Journal Article","linkHelpText":"- An assessment of uranium in groundwater in the Grand Canyon region"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.31257554612749,\n 36.98617449546404\n ],\n [\n -114.0381223568529,\n 36.98617449546404\n ],\n [\n -114.0381223568529,\n 35.5450981868304\n ],\n [\n -111.31257554612749,\n 35.5450981868304\n ],\n [\n -111.31257554612749,\n 36.98617449546404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Contact Us- USGS Publications Warehouse
","tableOfContents":"Rain gardens installed as green infrastructure to divert storm runoff from entering combined sewers also collect dissolved constituents and particulates. An urban rain garden in northwestern Indiana, USA, was continuously monitored from November 2019 to May 2021 to evaluate the fate of dissolved constituents entering the rain garden in runoff. Physical and chemical properties of soils in the rain garden were also monitored, along with underlying groundwater. Linear regression models relating specific conductance to chloride concentration indicated that the 0.0371-ha (3998 square feet) rain garden collected approximately 1490 kg (3285 pounds) of road salt from the surrounding 0.2228 ha (24,500 square feet) of impervious surfaces. Soils and groundwater were seasonally affected by road salt application but carryover from year to year was not indicated. Rain garden soil permeability (5.20 × 10−5 to 9.72 × 10−5 m/s) remained unchanged during the study period and soil organic carbon generally increased under native vegetation. The results suggest that a rain garden built on sandy soil can divert substantial quantities of runoff and dissolved constituents from combined sewers; however, chloride is transported to sub-infrastructure groundwater that eventually discharges to adjacent waterways with concentrations lower than those observed in runoff.
","language":"English","publisher":"MDPI","doi":"10.3390/w17040510","usgsCitation":"Bayless, E.R., Naylor, S., Lampe, D.C., Story, A., and Artz, C., 2025, Road salt collection and redistribution at an urban rain garden on sandy soil, Gary, Indiana: Water, v. 17, no. 4, 510, 25 p., https://doi.org/10.3390/w17040510.","productDescription":"510, 25 p.","ipdsId":"IP-126325","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":489968,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17040510","text":"Publisher Index Page"},{"id":482638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","city":"Gary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.33710281880745,\n 41.603842124498556\n ],\n [\n -87.33710281880745,\n 41.60260759598816\n ],\n [\n -87.33586794894438,\n 41.60260759598816\n ],\n [\n -87.33586794894438,\n 41.603842124498556\n ],\n [\n -87.33710281880745,\n 41.603842124498556\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bayless, E. Randall 0000-0002-0357-3635","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":42586,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"","middleInitial":"Randall","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naylor, Shawn 0000-0003-0710-1560","orcid":"https://orcid.org/0000-0003-0710-1560","contributorId":333771,"corporation":false,"usgs":true,"family":"Naylor","given":"Shawn","email":"","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lampe, David C. 0000-0002-8904-0337 dclampe@usgs.gov","orcid":"https://orcid.org/0000-0002-8904-0337","contributorId":2441,"corporation":false,"usgs":true,"family":"Lampe","given":"David","email":"dclampe@usgs.gov","middleInitial":"C.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Story, Amy A 0000-0003-1926-9811","orcid":"https://orcid.org/0000-0003-1926-9811","contributorId":350865,"corporation":false,"usgs":true,"family":"Story","given":"Amy A","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Artz, Caleb Colyer 0009-0002-3049-6062","orcid":"https://orcid.org/0009-0002-3049-6062","contributorId":350866,"corporation":false,"usgs":true,"family":"Artz","given":"Caleb Colyer","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929090,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263598,"text":"70263598 - 2025 - A fire deficit persists across diverse North American forests despite recent increases in area burned","interactions":[],"lastModifiedDate":"2025-02-18T15:08:19.333441","indexId":"70263598","displayToPublicDate":"2025-02-10T09:01:20","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 fire deficit persists across diverse North American forests despite recent increases in area burned","docAbstract":"Rapid increases in wildfire area burned across North American forests pose novel challenges for managers and society. Increasing area burned raises questions about whether, and to what degree, contemporary fire regimes (1984–2022) are still departed from historical fire regimes (pre-1880). We use the North American tree-ring fire-scar network (NAFSN), a multi-century record comprising >1800 fire-scar sites spanning diverse forest types, and contemporary fire perimeters to ask whether there is a contemporary fire surplus or fire deficit, and whether recent fire years are unprecedented relative to historical fire regimes. Our results indicate, despite increasing area burned in recent decades, that a widespread fire deficit persists across a range of forest types and recent years with exceptionally high area burned are not unprecedented when considering the multi-century perspective offered by fire-scarred trees. For example, ‘record’ contemporary fire years such as 2020 burned 6% of NAFSN sites—the historical average—well below the historical maximum of 29% sites that burned in 1748. Although contemporary fire extent is not unprecedented across many North American forests, there is abundant evidence that unprecedented contemporary fire severity is driving forest loss in many ecosystems and adversely impacting human lives, infrastructure, and water supplies.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-025-56333-8","usgsCitation":"Parks, S., Guiterman, C., Margolis, E.Q., Lonergan, M., Whitman, E., Abatzoglou, J.T., Falk, D.A., Johnston , J., Daniels, L., Lafon, C.W., Loehman, R.A., Kipfmueller, K.F., Naficy, C.E., Parisien, M., Portier, J., Stambaugh, M.C., Williams, A.P., Wion, A.P., and Yocom, L., 2025, A fire deficit persists across diverse North American forests despite recent increases in area burned: Nature Communications, v. 16, 1493, 13 p., https://doi.org/10.1038/s41467-025-56333-8.","productDescription":"1493, 13 p.","ipdsId":"IP-171157","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":487647,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-025-56333-8","text":"Publisher Index 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Park","contributorId":200207,"corporation":false,"usgs":false,"family":"Williams","given":"A.","email":"","middleInitial":"Park","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":927494,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wion, Andreas Paul 0000-0002-0701-2843","orcid":"https://orcid.org/0000-0002-0701-2843","contributorId":335166,"corporation":false,"usgs":true,"family":"Wion","given":"Andreas","email":"","middleInitial":"Paul","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":927495,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Yocom, Larissa","contributorId":224404,"corporation":false,"usgs":false,"family":"Yocom","given":"Larissa","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":927496,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70267221,"text":"70267221 - 2025 - Filling the gaps: A Bayesian mixture model for imputing missing soil water content data","interactions":[],"lastModifiedDate":"2025-05-16T15:31:40.63399","indexId":"70267221","displayToPublicDate":"2025-02-10T08:27:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Filling the gaps: A Bayesian mixture model for imputing missing soil water content data","docAbstract":"Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water-limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well (R2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap-fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.70004","usgsCitation":"Ogle, K., Reich, E., Samuels-Crow, K., Litvak, M., Bradford, J., Schlaepfer, D.R., and Devan, M., 2025, Filling the gaps: A Bayesian mixture model for imputing missing soil water content data: Ecohydrology, v. 18, no. 1, e70004, 17 p., https://doi.org/10.1002/eco.70004.","productDescription":"e70004, 17 p.","ipdsId":"IP-163652","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490127,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eco.70004","text":"External Repository"},{"id":486071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.07993996238093,\n 37.04473109056555\n ],\n [\n -109.07993996238093,\n 31.382778545525298\n ],\n [\n -103.04352625964134,\n 31.382778545525298\n ],\n [\n -103.04352625964134,\n 37.04473109056555\n ],\n [\n -109.07993996238093,\n 37.04473109056555\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":937346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Emma","contributorId":355440,"corporation":false,"usgs":false,"family":"Reich","given":"Emma","affiliations":[{"id":84751,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":937347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuels-Crow, Kimberly","contributorId":289104,"corporation":false,"usgs":false,"family":"Samuels-Crow","given":"Kimberly","email":"","affiliations":[{"id":62051,"text":"School of Informatics, Computing, and Cyber Systems; Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":937348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Litvak, Marcy","contributorId":216915,"corporation":false,"usgs":false,"family":"Litvak","given":"Marcy","affiliations":[{"id":39549,"text":"University of New Mexico: Albuquerque, NM","active":true,"usgs":false}],"preferred":false,"id":937349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Devan, Megan","contributorId":355441,"corporation":false,"usgs":false,"family":"Devan","given":"Megan","affiliations":[{"id":84752,"text":"Department of Biology, University of New Mexico, Albuquerque, New Mexico, 87131, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":937352,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263843,"text":"70263843 - 2025 - Possible influence of water level management on nutrient flux in nearshore sediments of Kabetogama Lake, Minnesota, USA","interactions":[],"lastModifiedDate":"2025-02-26T20:43:03.031044","indexId":"70263843","displayToPublicDate":"2025-02-06T13:36:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Possible influence of water level management on nutrient flux in nearshore sediments of Kabetogama Lake, Minnesota, USA","docAbstract":"Lake water level fluctuations are an important factor driving variation in many ecosystem processes. The nearshore sediments that are periodically exposed and re-inundated can develop distinct physical and chemical characteristics, especially in relationship to the organic matter content of the sediments and the particle size distribution. These sediment characteristics in turn can alter the flux of nitrogen (N) and phosphorus (P) from sediments into the water column when sediments are inundated. Here, we used intact sediment core experiments across a range of sediment inundation frequencies to estimate the effect of inundation frequency on sediment nutrient flux in Kabetogama Lake, Minnesota, USA. We observed associations between elevation or inundation frequency and some sediment characteristics, but in a structural equation model, inundation frequency and the sediment properties we measured were poorly related to inorganic nutrient flux. On the other hand, inundation frequency did have a moderate association with organic N and P flux from sediments, which could be due to decay of terrestrial organic matter that accumulates on exposed sediments. We used our parameterized structural equation model to estimate how three different water level management regimes employed over the past 50 years could influence organic N and P flux from sediments. The models suggested more recent water level management regimes reduced organic N and P flux by 9%–13% and 5.9%–9.8%, respectively. Nearshore sediment flux could sustain and influence harmful algal blooms that occur in this lake, and these fluxes could be influenced by water level management.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70176","usgsCitation":"Larson, J.H., Bailey, S., Maki, R., Christensen, V., Stelzer, E., Smith, J., LeDuc, J.F., and McWhorter, S., 2025, Possible influence of water level management on nutrient flux in nearshore sediments of Kabetogama Lake, Minnesota, USA: Ecosphere, v. 16, no. 2, e70176, 22 p., https://doi.org/10.1002/ecs2.70176.","productDescription":"e70176, 22 p.","ipdsId":"IP-160471","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":487688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70176","text":"Publisher Index Page"},{"id":482500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1323728221501,\n 48.530999864005054\n ],\n [\n -93.1323728221501,\n 48.39653345056249\n ],\n [\n -92.70028521395359,\n 48.39653345056249\n ],\n [\n -92.70028521395359,\n 48.530999864005054\n ],\n [\n -93.1323728221501,\n 48.530999864005054\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":928641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Sean 0000-0003-0361-7914 sbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-0361-7914","contributorId":198515,"corporation":false,"usgs":true,"family":"Bailey","given":"Sean","email":"sbailey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":928642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maki, Ryan P.","contributorId":190131,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":928643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, James C.","contributorId":351486,"corporation":false,"usgs":false,"family":"Smith","given":"James C.","affiliations":[{"id":82351,"text":"U.S. National Park Service (NPS)","active":true,"usgs":false}],"preferred":false,"id":928646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeDuc, Jamie F.","contributorId":178241,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jamie","email":"","middleInitial":"F.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":928647,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McWhorter, Seth","contributorId":351487,"corporation":false,"usgs":false,"family":"McWhorter","given":"Seth","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":928648,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70267513,"text":"70267513 - 2025 - Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms","interactions":[],"lastModifiedDate":"2025-05-28T14:23:50.819907","indexId":"70267513","displayToPublicDate":"2025-02-06T09:19:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms","docAbstract":"Louisiana's coastal wetlands are complex systems that require a continuous input of organic and inorganic material to keep pace with relative sea-level rise. Coastal restoration projects such as sediment diversions are being implemented to mitigate land loss and increase availability of inorganic sediment to coastal wetlands, and marshes specifically rely on organic material to build soil volume and maintain surface elevation. Interannual-to-decadal sea-level anomalies such as hurricanes can affect marsh accretion, mineral deposition, and plant productivity. In this light, complex ecogeomorphic feedback controls whether a marsh surface is sustainable or eroded/drowns. This study performs some of the first differential vertical accretion rates (VARs) and organic and inorganic mass accumulation rates (MARs) over time in SE Louisiana marshes determined from the 210Pb Constant Rate of Supply model, coupled with standard 137Cs VARs. These accumulation rates over the past ∼100 years were measured from a total of six brackish and salt marsh locations in Barataria Basin near the proposed Mid-Barataria Sediment Diversion. They were then related to interannual sea-surface elevations at Grand Isle, Louisiana, over the last ∼60 years and recorded hurricane activity in the delta. Results show VARs range from 0.63 cm/y to 1.69 cm/y and total MARs range from 0.11 to 0.43 g/cm2/y. Temporally, VARs and MARs (total, inorganic, and organic) are characterized by gradual increases in rates with decreasing age along with episodic peaks in VARs and MARs. The findings of this study indicate that no relationship occurs between sea-level anomalies and VARs or organic and inorganic MARs; however, a strong relationship appears to occur between major hurricanes to VAR and MAR contributions. Furthermore, high water content (81 ± 8%) and organic-rich soils in the sediment cores highlight the significance of belowground biomass and associated pore volume in maintaining marsh elevation in the study area.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-24-00032.1","usgsCitation":"Vincent, S., Wilson, C., Snedden, G., and Quirk, T., 2025, Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms: Journal of Coastal Research, v. 41, no. 3, p. 452-467, https://doi.org/10.2112/JCOASTRES-D-24-00032.1.","productDescription":"16 p.","startPage":"452","endPage":"467","ipdsId":"IP-167886","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":486639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.48248147473386,\n 29.674646712251956\n ],\n [\n -90.48248147473386,\n 29.118938193358844\n ],\n [\n -89.69005114637018,\n 29.118938193358844\n ],\n [\n -89.69005114637018,\n 29.674646712251956\n ],\n [\n -90.48248147473386,\n 29.674646712251956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Vincent, Sophie","contributorId":355962,"corporation":false,"usgs":false,"family":"Vincent","given":"Sophie","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":938460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Carol","contributorId":302654,"corporation":false,"usgs":false,"family":"Wilson","given":"Carol","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":938461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snedden, Gregg A. 0000-0001-7821-3709","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":212275,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quirk, Tracy","contributorId":208063,"corporation":false,"usgs":false,"family":"Quirk","given":"Tracy","email":"","affiliations":[{"id":37701,"text":"Academy of Natural Sciences of Drexel University, Philadelphia, Pa","active":true,"usgs":false}],"preferred":false,"id":938463,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266054,"text":"70266054 - 2025 - Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS","interactions":[],"lastModifiedDate":"2025-06-12T15:39:19.215206","indexId":"70266054","displayToPublicDate":"2025-02-06T08:46:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS","docAbstract":"Hydrologic connectivity is a crucial determinant of aquatic ecosystem services, governing the exchange of nutrients, sediments, chemicals, and biota. Various indices and metrics exist for quantifying hydrologic connectivity across diverse environments and scales. However, existing methodologies often fail to adequately capture lateral connectivity between floodplain lakes and streams across vast, low-relief, multi-lake floodplain systems. This study introduces a novel approach for quantifying lateral hydrologic connectivity specifically tailored for floodplain lakes connecting to streams within the expansive floodplain of the Lower Mississippi River. This approach centers on the spatial and temporal intersection of lakes and streams, leveraging remote sensing and GIS data to estimate nine distinct metrics of hydrologic connectivity. To assess the reliability of the method, the study estimated connectivity metrics for 92 randomly selected floodplain lakes, comprising 53 lakes connected to large streams (Strahler order >7), 13 lakes connected to medium (order 4-6) streams, and 26 lakes connected to small (order 1-3) streams. As expected, there was significant variability in hydrologic connectivity across different stream size classes. The outlined approach contributes valuable insights into the hydrologic connectivity of floodplain lakes and offers a generalizable framework applicable to other floodplains. Its versatility makes it a practical tool for understanding connectivity requirements for biota and facilitating applications in conservation and water resources management. Thus, this work represents a meaningful step toward advancing our understanding of lateral hydrologic connectivity dynamics in complex aquatic ecosystems.\n ","language":"English","publisher":"Wiley","doi":"10.1002/rra.4426","usgsCitation":"Ahmad, H., Miranda, L.E., Dunn, C.G., Boudreau, M., Colvin, M., and Dash, P., 2025, Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS: River Research and Applications, v. 41, no. 5, p. 1014-1029, https://doi.org/10.1002/rra.4426.","productDescription":"16 p.","startPage":"1014","endPage":"1029","ipdsId":"IP-166779","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":484990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Lower Mississippi River floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.70569886340942,\n 35.378193533513624\n ],\n [\n -91.48523796505039,\n 33.22134089549405\n ],\n [\n -91.97295509476544,\n 30.945728873306038\n ],\n [\n -91.04203402054121,\n 30.941053928057386\n ],\n [\n -90.92591403794623,\n 31.351716726235846\n ],\n [\n -90.60384187137875,\n 33.59410666110667\n ],\n [\n -89.14760247281004,\n 36.80807080526803\n ],\n [\n -90.70569886340942,\n 35.378193533513624\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahmad, Hafez","contributorId":353774,"corporation":false,"usgs":false,"family":"Ahmad","given":"Hafez","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":934467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boudreau, Melanie R.","contributorId":353778,"corporation":false,"usgs":false,"family":"Boudreau","given":"Melanie R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":934470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E.","contributorId":264842,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":934471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dash, Padmanava 0000-0003-3851-6830","orcid":"https://orcid.org/0000-0003-3851-6830","contributorId":297903,"corporation":false,"usgs":false,"family":"Dash","given":"Padmanava","email":"","affiliations":[{"id":64445,"text":"Department of Geosciences, Mississippi State University, Mississippi State, MS, US","active":true,"usgs":false}],"preferred":false,"id":934472,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264040,"text":"70264040 - 2025 - Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA","interactions":[],"lastModifiedDate":"2025-05-28T14:49:29.252868","indexId":"70264040","displayToPublicDate":"2025-02-06T08:00:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA","docAbstract":"Double-crested Cormorants (Nannopterum auritum) have historically exhibited low levels of infection and antibodies to avian influenza virus (AIV). The recent global expansion of clade 2.3.4.4b A/goose/Guangdong/1/1996 highly pathogenic (HP) avian influenza virus H5N1 (HPAI H5N1) has resulted in large-scale mortalities across diverse waterbird taxa including cormorants. We sampled 32 and 29 Double-crested Cormorants breeding in the Chesapeake Bay, US, during the summers of 2023 and 2024, respectively, to assess HPAI H5N1 infection and AIV antibodies. Although no mortality was observed in the area, one bird sampled in 2023 was infected with HPAI H5N1. Additionally, 21/31 individuals in 2023 and 10/25 individuals in 2024 for which sera were collected had AIV antibodies. Based on additional testing using hemagglutination inhibition, virus neutralization, and an enzyme-linked lectin assay, 94 and 100% (2023 and 2024, respectively) of the seropositive birds tested positive for antibodies to both H5 and N1, suggesting previous infection with HPAI H5N1. These results are consistent with survival and limited clinical effects related to HPAI H5N1 infections. Furthermore, these results suggest that population immunity to HPAI H5N1 within the Chesapeake Bay might reduce future infections and potential population impacts should HP H5N1 remain on the landscape, though immunity may be waning across time. Because results are based on a single population, additional testing for both infection and antibodies as well as continued monitoring could enhance understanding of antibody persistence.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/jwd-d-24-00111","usgsCitation":"Harvey, J., Sullivan, J., Poulson, R., Carter, D.L., Driscoll, C.P., McGowan, P.C., Callahan, C.R., O'Donnell, A., Mullinax, J.M., Stallknecht, D., and Prosser, D.J., 2025, Highly pathogenic avian influenza virus H5N1 in double-crested cormorants (Nannopterum auritum) of the Chesapeake Bay, USA: Journal of Wildlife Diseases, v. 61, no. 2, p. 348-356, https://doi.org/10.7589/jwd-d-24-00111.","productDescription":"9 p.","startPage":"348","endPage":"356","ipdsId":"IP-166564","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":482915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.8702033385699,\n 39.65270512692044\n ],\n [\n -76.71510396799904,\n 39.65270512692044\n ],\n [\n -76.71510396799904,\n 36.82223050001578\n ],\n [\n -75.8702033385699,\n 36.82223050001578\n ],\n [\n -75.5415430693737,\n 37.907513139633274\n ],\n [\n -75.8702033385699,\n 39.65270512692044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Johanna Alexandra 0000-0003-4504-6777","orcid":"https://orcid.org/0000-0003-4504-6777","contributorId":351781,"corporation":false,"usgs":true,"family":"Harvey","given":"Johanna Alexandra","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":929570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery Dale 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Georgia","active":true,"usgs":false}],"preferred":false,"id":929573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Cindy P.","contributorId":190850,"corporation":false,"usgs":false,"family":"Driscoll","given":"Cindy","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":929574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":929575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis 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Georgia","active":true,"usgs":false}],"preferred":false,"id":929579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":929580,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263259,"text":"fs20253004 - 2025 - The 3D Elevation Program—Supporting Utah’s economy","interactions":[],"lastModifiedDate":"2025-05-15T00:35:47.104765","indexId":"fs20253004","displayToPublicDate":"2025-02-05T12:40:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact 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Light detection and ranging (lidar) data are used to support infrastructure planning and management, assess natural resources, and improve resiliency to hazards. The expanding availability of current and more accurate lidar data helps to better support natural resource conservation, wildfire risk management, geologic hazard investigation and mitigation, flood risk management, water supply planning, and urban planning and development. Critical applications that meet the State’s management needs depend on lidar data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program is managed by the U.S. Geological Survey in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Utah. The status of available and in-progress 3DEP baseline lidar data in Utah is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $8.70 million in new benefits annually to the State. The top 10 Utah business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253004","usgsCitation":"Ritmiller, C., 2025, The 3D Elevation Program—Supporting Utah’s economy: U.S. Geological Survey Fact Sheet 2025–3004, 2 p., https://doi.org/10.3133/fs20253004.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146493","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":481624,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3004/fs20253004.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3004 XML"},{"id":481621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3004/coverthb.jpg"},{"id":481625,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3004/images/"},{"id":481623,"rank":3,"type":{"id":39,"text":"HTML 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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Sea star wasting syndrome (SSWS) has affected numerous species of sea star, with populations of Pycnopodia helianthoides (Brandt, 1835) left most at risk. As their populations are struggling to recover, it is important to gain a better understanding of the impacts that the multiple stressors in their habitats can have on their populations. Contaminant stressors in particular are of increasing importance, as aquatic organisms can be exposed to a dynamic range of contaminants from nearby anthropogenic activity that may affect their future recovery efforts. This study is the first to quantify the effects of contaminant stressors on the larvae of P. helianthoides. We exposed P. helianthoides larvae to the neonicotinoid insecticide imidacloprid and polyester microfibers, both individually and in combination, at environmentally relevant concentrations (10 ng/L and 25 fibers/L, respectively) to measure the effects of these contaminants on their early life stages. Imidacloprid exposure resulted in stomach malformation in 10% of larvae and increased mortality during early development (p < 0.001), and all treatments resulted in increased larval lengths relative to controls (p < 0.001). During settlement, imidacloprid resulted in more rapid settlement responses than in the controls (p < 0.01). These findings highlight the need for further research investigating the effects of contaminant stressors to endangered organisms during reintroduction, as well as a more comprehensive understanding of the effects of pesticides to non-target organisms.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf039","usgsCitation":"Tissot, A.G., Granek, E.F., Curliss, F., Kalytiak-Davis, A., Hodin, J., and Hladik, M.L., 2025, The effects of imidacloprid and polyester microfibers on the larval development of the endangered sunflower star: Environmental Toxicology and Chemistry, v. 44, no. 4, p. 1107-1119, https://doi.org/10.1093/etojnl/vgaf039.","productDescription":"13 p.","startPage":"1107","endPage":"1119","ipdsId":"IP-171431","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":482110,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Tissot, Alexandra G.","contributorId":269833,"corporation":false,"usgs":false,"family":"Tissot","given":"Alexandra","email":"","middleInitial":"G.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":927436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granek, Elise F.","contributorId":176630,"corporation":false,"usgs":false,"family":"Granek","given":"Elise","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":927437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Curliss, Fiona","contributorId":350948,"corporation":false,"usgs":false,"family":"Curliss","given":"Fiona","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":927438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalytiak-Davis, Augustin","contributorId":350949,"corporation":false,"usgs":false,"family":"Kalytiak-Davis","given":"Augustin","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":927439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodin, Jason","contributorId":295360,"corporation":false,"usgs":false,"family":"Hodin","given":"Jason","email":"","affiliations":[{"id":63853,"text":"Friday Harbor Labs","active":true,"usgs":false}],"preferred":false,"id":927440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":927441,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267521,"text":"70267521 - 2025 - Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","interactions":[{"subject":{"id":70267521,"text":"70267521 - 2025 - Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","indexId":"70267521","publicationYear":"2025","noYear":false,"title":"Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020"},"predicate":"SUPERSEDED_BY","object":{"id":70274705,"text":"sir20265001 - 2026 - Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","indexId":"sir20265001","publicationYear":"2026","noYear":false,"title":"Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020"},"id":1}],"supersededBy":{"id":70274705,"text":"sir20265001 - 2026 - Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","indexId":"sir20265001","publicationYear":"2026","noYear":false,"title":"Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020"},"lastModifiedDate":"2026-04-08T14:00:49.054189","indexId":"70267521","displayToPublicDate":"2025-02-05T08:48:40","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19891,"text":"ESS Open Archive","active":true,"publicationSubtype":{"id":32}},"title":"Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","docAbstract":"The U.S. Geological Survey (USGS) and the Washington State Department of Ecology (Ecology) have developed watershed models of seasonal load estimates of total nitrogen (TN) and total phosphorus (TP) discharging into the Washington waters of the Salish Sea from 2005 through 2020. The modeling approach used was dynamic SPARROW (SPAtially Referenced Regressions On Watershed attributes), a statistical-physical watershed modeling technique, initially applied at large spatial scales to represent long-term average stream loads throughout a stream network, refined here to estimate seasonal TN and TP loads across watersheds to clarify upstream contributions from discernable point and nonpoint sources delivered to marine waters at surface water confluences along the shoreline and quantify when, where, and why they were high or low. Upstream contributing sources included permitted treated wastewater facilities, crop fertilizer, animal feeding operations, septic systems, urban land and stormwater, atmospheric deposition (TN only), nitrogen fixation by Red Alder Alnus rubra trees (TN only), and background geologic material (TP only). Instream load magnitudes and their source compositions varied widely across watersheds, and even within each watershed, yet the largest loads typically occurred in the large rivers during winter and fall when streamflow was highest. Likewise, instream loads were typically lowest in summer during low streamflow, yet the relative instream aquatic decay was highest. The seasonal storage lag component of those nonpoint sources was estimated to contribute a quarter of the seasonal instream load during winter and fall high streamflow and sometimes half of the instream load during summer low streamflow. A key aspect of Ecology’s current Puget Sound Nutrient Source Reduction Project is consideration of upstream watershed contributions of nutrients to their marine-water discharge points. Simulated seasonal loads carried by streams to 63 river mouth marine discharge points 9 ranged by several orders-of-magnitude for both TN and TP due to the spatial and seasonal differences in hydrologic flows, magnitude and timing of contributing sources, and in-stream decay. The Snohomish and Skagit Rivers discharged the largest TN and TP loads, yet the Samish River was shown to have some of the highest TN and TP yields and concentrations. Additionally, a reference scenario was developed to provide an estimate of the pre-industrial local and regional loads.
","language":"English","publisher":"ESS Open Archive","doi":"10.22541/essoar.173878059.92247480/v1","usgsCitation":"Schmadel, N., Figueroa-Kaminsky, C., Wise, D., Wasielewski, J., Johnson, Z., and Black, R.W., 2025, Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020: ESS Open Archive, preprint posted February 05, 2025, https://doi.org/10.22541/essoar.173878059.92247480/v1.","productDescription":"110 p.","ipdsId":"IP-174989","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":486634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":938477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Figueroa-Kaminsky, Cristiana","contributorId":350514,"corporation":false,"usgs":false,"family":"Figueroa-Kaminsky","given":"Cristiana","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":938478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Daniel 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","email":"","affiliations":[],"preferred":true,"id":938479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wasielewski, Jamie K. 0009-0005-7497-3344","orcid":"https://orcid.org/0009-0005-7497-3344","contributorId":344993,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Jamie K.","affiliations":[{"id":82458,"text":"Washington Dept. of Ecology","active":true,"usgs":false}],"preferred":false,"id":938480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":938481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938482,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263262,"text":"ofr20241076 - 2025 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2022","interactions":[],"lastModifiedDate":"2025-07-21T18:11:15.378927","indexId":"ofr20241076","displayToPublicDate":"2025-02-04T14:11:40","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1076","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2022","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2022","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, deepened the St. Johns River channel in Jacksonville, Florida, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection sites in the St. Johns River and its tributaries.
This report contains information collected during the 2022 water year, from October 2021 to September 2022. Data at each site were compared for the length of the project and on a yearly basis to show the annual variability of discharge and salinity.
The countywide annual rainfall for the 2022 water year was above the average yearly rainfall in four of the five counties. Annual mean discharge at 8 of the 10 tributary monitoring sites was lower for the 2022 water year than for the 2021 water year, and the annual mean flow at Broward River below Biscayne Boulevard near Jacksonville, Florida (USGS site number 02246751), was the lowest recorded at that site over the 7 years of data collection. The annual mean discharge for each of the main-stem sites was lower for the 2022 water year than for the 2021 water year.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek above Buckhorn Bluff near Jacksonville, Fla. (USGS site number 302657081312400), the site closest to the Atlantic Ocean, and was lowest at Durbin Creek near Fruit Cove, Fla. (USGS site number 022462002), the site farthest from the ocean, for all years. Annual mean salinity data from the main-stem sites indicate that salinity decreased with distance upstream from the ocean, which was expected. Annual mean salinity at all monitoring locations was higher for the 2022 water year than the 2021 water year, except at St. Johns River at Buffalo Bluff near Satsuma, Fla. (USGS site number 02244040) and St. Johns River at Dancy Point near Spuds, Fla. (USGS site number 294213081345300), which remained the same. St. Johns River Shands Bridge near Green Cove Springs, Fla. (USGS site number 295856081372301) and Durbin Creek near Fruit Cove, Fla. (USGS site number 022462002) had the highest annual mean salinities at their respective sites since data collection began.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241076","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Carson, J.N., and Benacquisto, M.T., 2025, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2022: U.S. Geological Survey Open-File Report 2024–1076, 51 p., https://doi.org/10.3133/ofr20241076.","productDescription":"Report: x, 51 p.; Data Release","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-159934","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":492684,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118424.htm","linkFileType":{"id":5,"text":"html"}},{"id":481631,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS NWIS Data Release","linkHelpText":"- USGS water data for the Nation"},{"id":481630,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241076/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1076 HTML"},{"id":481628,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1076/ofr20241076.pdf","size":"6.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1076"},{"id":481626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1076/coverthb.jpg"},{"id":481629,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1076/ofr20241076.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1076 XML"},{"id":481627,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1076/images"}],"country":"United States","state":"Florida","otherGeospatial":"Lower St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.07550333942321,\n 30.37984516308761\n ],\n [\n -82.07550333942321,\n 29.26001508937391\n ],\n [\n -81.32685861157174,\n 29.26001508937391\n ],\n [\n -81.32685861157174,\n 30.37984516308761\n ],\n [\n -82.07550333942321,\n 30.37984516308761\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Contact Us- USGS Publications Warehouse
","tableOfContents":"Illustration of U.S. Geological Survey science at breccia pipe mines in the Grand Canyon region. The upper left portion shows a cross section of a breccia pipe and rock layers (far upper left) in a panoramic view of the Grand Canyon with upper right depicting rock pinnacles the Havasupai Tribe call Wi’i Gileeva. The right portion depicts a spring. The Colorado River bisects the illustration. A typical breccia pipe uranium mine site is shown in the lower left. Local plant and animal species studied are also included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip249","usgsCitation":"Siebers, B.J., 2025, Uranium mining, the Grand Canyon region, and the science of an ecosystem: U.S. Geological Survey General Information Product 249, https://doi.org/10.3133/gip249.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171589","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":481651,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243003","text":"USGS Fact Sheet 2024–3003","linkHelpText":"- Balancing natural resource use and extraction of uranium and other elements in the Grand Canyon region"},{"id":481618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/249/coverthb.jpg"},{"id":492682,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118423.htm","linkFileType":{"id":5,"text":"html"}},{"id":481619,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/249/gip249.pdf","text":"Report","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 249"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.32256082421961,\n 36.96787079826102\n ],\n [\n -114.04321695572075,\n 36.96787079826102\n ],\n [\n -114.04321695572075,\n 35.68382789858792\n ],\n [\n -111.32256082421961,\n 35.68382789858792\n ],\n [\n -111.32256082421961,\n 36.96787079826102\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192
As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2022 (October 1, 2021, through September 30, 2022). Water-quality samples were collected by Providence Water at 37 sampling stations on tributaries to the Scituate Reservoir during water year 2022. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2022.
Annual mean streamflows for monitoring stations in this study ranged from about 0.31 to 28.0 cubic feet per second during water year 2022. At the 16 continuous-record streamgages, tributaries transported about 2,600 metric tons of chloride and 1,600 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 15 to 100 metric tons per square mile, and annual sodium yields ranged from 10 to 59 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 55,000 million colony forming units per day for coliform bacteria, 1,300 million colony forming units per day for Escherichia coli, 230 kilograms per day for chloride, 11 grams per day as nitrogen for nitrite, 620 grams per day as nitrogen for nitrate, and 440 grams per day as orthophosphate for phosphate, The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 810 million colony forming units per day per square mile for Escherichia coli, 110 kilograms per day per square mile for chloride, 5.1 grams per day per square mile as nitrogen for nitrite, less than 300 grams per day per square mile as nitrogen for nitrate, and 230 grams per day per square mile as orthophosphate for phosphate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1205","collaboration":"Prepared in cooperation with Providence Water","usgsCitation":"Smith, K.P., and Spaetzel, A.B., 2025, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2022: U.S. Geological Survey Data Report 1205, 33 p., https://doi.org/10.3133/dr1205.","productDescription":"Report: vi, 33 p.; Data Release","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168044","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":492680,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118425.htm","linkFileType":{"id":5,"text":"html"}},{"id":481543,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 3.0, November 2023)"},{"id":481542,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1205/images/"},{"id":481539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1205/dr1205.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1205 PDF"},{"id":481461,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1205/coverthb.jpg"},{"id":481541,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1205/dr1205.XML","linkFileType":{"id":8,"text":"xml"},"description":"DR 1205 XML"},{"id":481540,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1205/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1205 HTML"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.74828321234178,\n 41.88241813157933\n ],\n [\n -71.74828321234178,\n 41.72949318006701\n ],\n [\n -71.53726504656385,\n 41.72949318006701\n ],\n [\n -71.53726504656385,\n 41.88241813157933\n ],\n [\n -71.74828321234178,\n 41.88241813157933\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The U.S. Geological Survey, in cooperation with Providence Water (formerly Providence Water Supply Board), conducted a long-term program to monitor water quality in the Scituate Reservoir drainage area in Rhode Island to collect streamflow and water-quality data from 16 tributaries to the reservoir during the water year 2022. These data were used to estimate loads of chloride and sodium. Additionally, water-quality samples were collected at 37 sampling stations on the tributaries, and the data were summarized using central tendency values.
Aechmophorus occidentalis (Western Grebe) are colonial nesting waterbirds that have experienced population declines. We located and monitored 709 grebe nests using a drone within Lake Cascade, the largest grebe breeding colony in Idaho. We conducted 6 flights between June 20, 2018 and July 11, 2018 and used the photographs from each flight to create an orthomosaic image that we then digitized and georeferenced. The resolution of the images allowed for visualization of each nest, nest contents, and adult grebes on each flight. Using the georeferenced images, we created nest histories and estimated nest fate for the 709 grebe nests. We also collected data on the following covariates to assess whether any of them affected nest survival: distance of the nest to the center of the colony; distance of the nest to the edge of the colony; distance of the nest to deep water habitat; water depth at the nest; nearest neighbor distance, and an aggregation index (mean distance to the 5 nearest nests). The orthomosaics from repeated drone flights allowed us to estimate nesting success without disturbing the colony; 51.2% of nests survived until hatching. The daily survival probability of grebe nests was positively correlated with the aggregation index and water depth at the nest (albeit only slightly). Daily survival probabilities were negatively correlated with distance between the nest and the colony center and distance to deep water (i.e., foraging habitat). The results of this study can be used to inform conservation efforts by identifying areas of the Lake Cascade grebe colony that are most vulnerable to nest failures and formulating explicit management actions that could be implemented to increase nest survival such as changes in timing of water drawdowns and habitat management to ensure habitat suitable for grebe nesting is in close proximity to deep water foraging areas. Moreover, grebes are not the only waterbird that makes use of managed reservoirs; other waterbirds may benefit from the findings of this study to implement more informed management practices.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf011","usgsCitation":"Lachman, D.A., Conway, C.J., Vierling, K.T., and Matthews, T., 2025, Water depth, position within the nesting colony, and nearest neighbor density affect nest survival in Aechmophorus occidentalis (Western Grebe): Ornithological Applications, v. 127, no. 3, duaf011, https://doi.org/10.1093/ornithapp/duaf011.","productDescription":"duaf011","ipdsId":"IP-167752","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":496906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Cascade","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.22230762170753,\n 44.76352823654196\n ],\n [\n -116.22230762170753,\n 44.46219778864179\n ],\n [\n -115.98703112617977,\n 44.46219778864179\n ],\n [\n -115.98703112617977,\n 44.76352823654196\n ],\n [\n -116.22230762170753,\n 44.76352823654196\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lachman, Deo A.","contributorId":338149,"corporation":false,"usgs":false,"family":"Lachman","given":"Deo","email":"","middleInitial":"A.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":943610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":943611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Kerri T.","contributorId":338150,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":943612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, Ty","contributorId":280032,"corporation":false,"usgs":false,"family":"Matthews","given":"Ty","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":943613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263512,"text":"70263512 - 2025 - Video evidence of a Red-eared Slider (Trachemys scripta elegans) preying upon a live Mallard (Anas platyrhynchos) duckling in Louisiana","interactions":[],"lastModifiedDate":"2025-02-13T15:44:54.229252","indexId":"70263512","displayToPublicDate":"2025-02-03T09:32:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Video evidence of a Red-eared Slider (Trachemys scripta elegans) preying upon a live Mallard (Anas platyrhynchos) duckling in Louisiana","title":"Video evidence of a Red-eared Slider (Trachemys scripta elegans) preying upon a live Mallard (Anas platyrhynchos) duckling in Louisiana","docAbstract":"Most animal matter in the diet of the omnivorous Trachemys scripta (Pond Slider) consists of invertebrate prey items such as insects, crustaceans, and mollusks, but often also includes fish and amphibians. Reptiles, birds, and mammals are less commonly reported, and even when found, it is usually unknown if they were captured alive, as Pond Sliders will certainly scavenge dead animals. Though it is well known that Chelydra serpentina (Snapping Turtle) will prey upon waterfowl from the water surface, reports of such encounters are seemingly rare in Pond Sliders. Here, we document with video evidence an adult female T. s. elegans (Red-eared Slider) emerging from the water to successfully take and drown an Anas platyrhynchos (Mallard) duckling.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.023.0417","usgsCitation":"Glorioso, B., Landry, A., and Mandill, G., 2025, Video evidence of a Red-eared Slider (Trachemys scripta elegans) preying upon a live Mallard (Anas platyrhynchos) duckling in Louisiana: Southeastern Naturalist, v. 23, no. 4, p. N90-N93, https://doi.org/10.1656/058.023.0417.","productDescription":"4 p.","startPage":"N90","endPage":"N93","ipdsId":"IP-169171","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":482029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Mandeville","volume":"23","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":204397,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":927242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landry, Alex","contributorId":350905,"corporation":false,"usgs":false,"family":"Landry","given":"Alex","affiliations":[{"id":83872,"text":"Canoe and Trail Adventures","active":true,"usgs":false}],"preferred":false,"id":927243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mandill, Gabrielle","contributorId":350906,"corporation":false,"usgs":false,"family":"Mandill","given":"Gabrielle","affiliations":[],"preferred":false,"id":927244,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263302,"text":"70263302 - 2025 - Bait trapping of waterfowl increases the environmental contamination of avian influenza virus (AIV)","interactions":[],"lastModifiedDate":"2025-03-25T15:54:44.911751","indexId":"70263302","displayToPublicDate":"2025-02-03T08:58:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Bait trapping of waterfowl increases the environmental contamination of avian influenza virus (AIV)","docAbstract":"Highly pathogenic avian influenza virus (HPAIV) H5Nx clade 2.3.4.4b has circulated in North America since late 2021, resulting in higher rates of morbidity and mortality in wild birds than observed in this region before. The objective of this study was to determine whether baiting, which is widely conducted in Canada and the United States as part of waterfowl management practices (e.g., duck banding), influences the occurrence of avian influenza virus (AIV) in wetlands. We used a quasi-experimental design, collecting superficial sediment samples (n = 336) and fecal samples (n = 242) from paired baited (treatment) and non-baited (control) sites at 2 wetlands in Saskatchewan, Canada, between August and September 2022. We visited sampling sites 3 times during the sampling period: prior to the commencement of baiting activities (t0), approximately 14 days after t0 (t1), and 24 days after t0 (t2). We screened samples for AIV using real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) targeting the matrix gene and subjected the PCR-positive samples to next-generation sequencing. We used a mixed-effects logistic regression model to estimate the effect of baiting on the odds of AIV positivity in sediment samples, while controlling for clustering by wetland. At control sites, we did not detect evidence for a difference in the odds of AIV detection in sediment at t1 or t2 versus t0; however, at baited sites, the odds of AIV detection at t1 were 5.43 (95% CI = 1.99, 14.79) times the odds at t0 and at t2 the odds of AIV detection were 8.73 (95% CI = 3.29, 23.18) times the odds at t0. We detected HPAIV clade 2.3.4.4b H5N1 in sediment at 1 treatment site following baiting. There was also a trend towards increased fecal AIV positivity and increased fecal and sediment AIV diversity in baited versus non-baited sites; however, there was insufficient power to determine if these findings were statistically significant. Overall, our results indicate that baiting is associated with localized increases in AIV environmental contamination, with baiting potentially creating concentrated areas of AIV accumulation. As such, wetland baiting activities may pose a risk to wildlife population health through the propagation of AIV in wetlands and the waterfowl using those environments and efforts to replace, refine, or reduce this activity may be warranted depending on local ecosystem contexts and cost-benefit analyses.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22720","usgsCitation":"Andrew, C., McPhee, L., Kuchinski, K., Wight, J., Rahman, I., Mansour, S., Angelo Cortez, G., Kalhor, M., Kenmuir, E., Prystajecky, N., Hargan, K., Lang, A., Leafloor, J., Soos, C., Ramey, A.M., and Himsworth, C., 2025, Bait trapping of waterfowl increases the environmental contamination of avian influenza virus (AIV): Journal of Wildlife Management, v. 89, no. 3, e22720, 15 p., https://doi.org/10.1002/jwmg.22720.","productDescription":"e22720, 15 p.","ipdsId":"IP-165980","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":487623,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22720","text":"Publisher Index 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Disease Control Public Health Laboratory","active":true,"usgs":false}],"preferred":false,"id":926234,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prystajecky, Natalie","contributorId":350531,"corporation":false,"usgs":false,"family":"Prystajecky","given":"Natalie","affiliations":[{"id":83760,"text":"British Columbia Center for Disease Control Public Health Laboratory","active":true,"usgs":false}],"preferred":false,"id":926235,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hargan, Kathryn","contributorId":205716,"corporation":false,"usgs":false,"family":"Hargan","given":"Kathryn","email":"","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":926236,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lang, Andrew","contributorId":331075,"corporation":false,"usgs":false,"family":"Lang","given":"Andrew","affiliations":[],"preferred":false,"id":926237,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Leafloor, James","contributorId":350532,"corporation":false,"usgs":false,"family":"Leafloor","given":"James","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":926238,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Soos, Catherine","contributorId":177909,"corporation":false,"usgs":false,"family":"Soos","given":"Catherine","email":"","affiliations":[],"preferred":false,"id":926240,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":926241,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Himsworth, Chelsea","contributorId":350534,"corporation":false,"usgs":false,"family":"Himsworth","given":"Chelsea","affiliations":[{"id":83761,"text":"British Columbia Ministry of Agriculture","active":true,"usgs":false}],"preferred":false,"id":926242,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70263305,"text":"70263305 - 2025 - Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","interactions":[],"lastModifiedDate":"2025-02-11T15:50:56.369579","indexId":"70263305","displayToPublicDate":"2025-02-03T07:53:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","docAbstract":"Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104513","usgsCitation":"Newman, C.P., Navarre-Sitchler, A., Runkel, R.L., and Cowie, R.M., 2025, Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed: Journal of Contaminant Hydrology, v. 269, 104513, 19 p., https://doi.org/10.1016/j.jconhyd.2025.104513.","productDescription":"104513, 19 p.","ipdsId":"IP-159009","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":489934,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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\"}}]}","volume":"269","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":926260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cowie, Rory M.","contributorId":270098,"corporation":false,"usgs":false,"family":"Cowie","given":"Rory","email":"","middleInitial":"M.","affiliations":[{"id":56077,"text":"Alpine Water Resources","active":true,"usgs":false}],"preferred":false,"id":926262,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263586,"text":"70263586 - 2025 - Waterfront property owners' shoreline preferences amid salt marsh to mangrove transitions","interactions":[],"lastModifiedDate":"2025-03-11T15:18:25.574964","indexId":"70263586","displayToPublicDate":"2025-02-03T07:44:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5936,"text":"People and Nature","active":true,"publicationSubtype":{"id":10}},"title":"Waterfront property owners' shoreline preferences amid salt marsh to mangrove transitions","docAbstract":"1. We examined the influence of mangrove encroachment into salt marsh areas along the northern Gulf of Mexico (USA) on waterfront property owners' perceptions of coastal health and preferences for shoreline management.
2. Using mail-in and online surveys, we targeted over 3000 waterfront property owners across four jurisdictions experiencing or anticipating mangrove encroachment.
3. Our findings revealed a nuanced perception of coastal health, with many respondents recognizing the potentially environmental impacts of mangrove encroachment but favouring low-cost management strategies, such as maintaining current shoreline or passive monitoring. This reluctance to engage in active management highlights a perception-behaviour gap, likely influenced by the gradual nature of mangrove transitions, which diminishes urgency for active intervention.
4. Socio-demographic factors such as age, gender, income, residency and reliance on coastal resources significantly shaped preferences for shoreline management and regional responses. These preferences varied across jurisdictions, reflecting the importance of incorporating localized community values into management decisions.
5. Our findings highlight the need for a balanced approach to shoreline management that integrates ecological insights with the socio-cultural priorities of local communities. By aligning adaptation strategies with regional perceptions and values, it is possible to protect individual properties while enhancing the long-term resilience of coastal ecosystems under climate change pressures.
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In the desert southwestern USA, managers are considering significant changes to reservoir operation strategies and water management in response to consumptive use and ongoing drought. To inform reservoir management decision-making, we reviewed current peer-reviewed literature to identify the effects of decreasing or increasing water level on phytoplankton, cyanobacteria, Escherichia coli, and Naegleria spp. We identified 34 studies containing 42 individual waterbodies that investigated the effects of water level increases or decreases on phytoplankton or cyanobacteria. We found that water level decreases resulted in a higher likelihood of increased cyanobacteria, and that phytoplankton were more likely to decrease in response to water level increases. Most of the waterbodies included in the literature review were eutrophic or hypereutrophic, underscoring the need to explore the effects of water level fluctuations on oligotrophic systems. We only identified five studies on E. coli through our review, and no studies on Naegleria spp. We supplemented our review with regional white papers and case studies within the Colorado River Basin and the Rio Grande River Basin to highlight relevant research. Prior and ongoing research highlights the need to explore impacts of water level fluctuations on phytoplankton and cyanobacteria to guide future management decision-making.
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