Highly pathogenic avian influenza virus (HPAIV) has caused extensive mortalities in wild birds with a disproportionate impact on raptors since 2021. The population-level impact of HPAIV can be informed by telemetry studies that track large samples of initially healthy, wild birds. We leveraged movement data from 71 rough-legged hawks (Buteo lagopus) across all major North American migratory bird flyways concurrent with the 2022–2023 HPAIV outbreak and identified a total of 29 mortalities, of which 11 were confirmed, and an additional ~9 were estimated to have been caused by HPAIV. We estimated a 28% HPAIV cause-specific mortality rate among rough-legged hawks during a single year concurrent with the HPAIV outbreak in North America. Additionally, the overall mortality rate during the HPAIV outbreak (47%) was significantly higher than baseline annual mortality rates (3%–17%) suggesting that HPAIV-caused deaths were additive above baseline mortality levels. HPAIV mortalities were concentrated within the Central and Atlantic flyways during prebreeding migration and peaked in April 2022 when large-scale HPAIV mortalities were reported in other wild birds throughout North America. HPAIV exposure was most likely caused by scavenging or preying on infected waterfowl, as rough-legged hawks are known to opportunistically scavenge during the nonbreeding season. We utilized movement data to identify a continental-scale HPAIV cause-specific mortality event in rough-legged hawks that has the potential to exacerbate ongoing population declines. Our study highlights the usefulness of monitoring movement data to pinpoint sources of mortality that can help better understand the drivers of population change, even if studies are focused on other research questions.
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However, our recent investigations near Bethel, Alaska, revealed numerous near-surface ice wedges. Using 20 cm resolution aerial orthoimagery from 2018, we identified ~50 linear km of ice wedge troughs in a 60 km2 study area. Fieldwork in 2023 and 2024 confirmed ice wedges up to ~1.5 m wide and ~2.5 m in vertical extent, situated on average 0.9 m below the tundra surface (n = 29). Ground-penetrating radar (GPR) detected additional ice wedges beyond those visible in the remote sensing imagery, suggesting an underestimation of their true abundance. Coring of polygonal centers revealed late-Quaternary deposits, including thick early Holocene peat, late-Pleistocene ice-rich silts (reworked Yedoma), charcoal layers from tundra fires, and the Aniakchak CFE II tephra (~3600 cal yrs BP). Stable water isotopes from Bethel's wedge ice (mean δ18O = −15.7 ‰, δ2H = −113.1 ‰) indicate a relatively enriched signature compared to other Holocene ice wedges in Alaska, likely due to warmer temperatures and maritime influences. Expanding our mapping across the YKD using high-resolution satellite imagery from 2012 to 2024, we estimate that the Holocene ice wedge zone encompasses ~30% of the YKD tundra region. Our findings demonstrate that ice wedge networks are more widespread across the YKD than previously recognized, emphasizing both the resilience and vulnerability of the region's warm, ice-rich permafrost. These insights are crucial for understanding permafrost responses to climate change and assessing agricultural potential and development in the region.
","language":"English","publisher":"Wiley","doi":"10.1002/ppp.70004","usgsCitation":"Jones, B.M., Kanevskiy, M.Z., Ward Jones, M.K., Wilson, P.R., Ditmer, I., Gaglioti, B.V., Klein, E.S., Rangel, R.C., Wallace, K.L., Jones, M.C., Wooller, M.J., and Shur, Y., 2025, Cryptic ice wedge networks in Holocene peat, Yukon-Kuskokwim Delta, Alaska: Permafrost and Periglacial Processes, v. 36, no. 4, p. 678-701, https://doi.org/10.1002/ppp.70004.","productDescription":"24 p.","startPage":"678","endPage":"701","ipdsId":"IP-175795","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":499646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Kuskokwim Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n 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pulse responses","interactions":[],"lastModifiedDate":"2025-07-08T17:08:38.774687","indexId":"70268849","displayToPublicDate":"2025-07-05T10:05:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation pulse dynamics are not ubiquitous: A global meta-analysis of plant and ecosystem carbon- and water-related pulse responses","docAbstract":"Ecosystem responses to precipitation pulses (“pulse responses”) exert a large control over global carbon, water, and energy cycles. However, it is unclear how the timing and magnitude of pulse responses will vary across ecosystems as precipitation regimes shift under accelerating climate change. To address this issue, this study evaluates how plants and ecosystems respond to precipitation pulses and explores potential implications of altered precipitation regimes for the carbon and water cycles. In particular, we conducted a global meta-analysis to quantify the magnitude and timing of plant and ecosystem carbon-related (Anet, NPP, GPP, Reco, Rbg) and water-related (ET, T, Ψ, gs) responses to 587 precipitation pulses. By analyzing pulse-response metrics published in the primary literature, we evaluated the characteristics of those pulse responses. We assessed whether precipitation pulses lead to a classic pulse response (i.e., a hump-shaped response as described by the pulse-reserve framework), a linear pulse response, a combination of classic and linear, or a lack of a pulse response. If a pulse response occurred, we explored the factors that drove its timing, magnitude, and speed. Our meta-analyses revealed that the classic, hump-shaped response is not ubiquitous, as it only accounted for 52% of the pulse responses. However, when a pulse response did occur, carbon-related responses to precipitation pulses were larger in magnitude (e.g., larger peak) than water-related pulse responses at relatively arid sites. However, at relatively mesic sites, this relationship reversed (i.e., water-related responses to precipitation pulses were larger than carbon-related responses). Additionally, larger precipitation pulse amounts increased water-related response magnitudes more than carbon-related response magnitudes across both arid and mesic sites. Therefore, under future precipitation intensification, carbon-related responses to precipitation pulses may become more decoupled from water-related pulse responses in wetter biomes but more coupled to water-related pulse responses in drier biomes.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.70327","usgsCitation":"Reich, E., Guo, J., Peltier, D., Palmquist, E.C., Samuels-Crow, K., Boone, R., and Ogle, K., 2025, Precipitation pulse dynamics are not ubiquitous: A global meta-analysis of plant and ecosystem carbon- and water-related pulse responses: Global Change Biology, v. 31, no. 7, e70327, 15 p., https://doi.org/10.1111/gcb.70327.","productDescription":"e70327, 15 p.","ipdsId":"IP-172036","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":492071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.70327","text":"Publisher Index Page"},{"id":491832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-05","publicationStatus":"PW","contributors":{"authors":[{"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":942361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, Jessica","contributorId":356781,"corporation":false,"usgs":false,"family":"Guo","given":"Jessica","affiliations":[{"id":85232,"text":"CCT Data Science Group, University of Arizona, Tucson, USA","active":true,"usgs":false}],"preferred":false,"id":942362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peltier, Drew","contributorId":357727,"corporation":false,"usgs":false,"family":"Peltier","given":"Drew","affiliations":[{"id":85542,"text":"School of Life Sciences, University of Nevada, Las Vegas, Nevada, U.S.A","active":true,"usgs":false}],"preferred":false,"id":942363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":942365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, Rohan","contributorId":357728,"corporation":false,"usgs":false,"family":"Boone","given":"Rohan","affiliations":[{"id":85543,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, 86011, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":942366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":942367,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268843,"text":"70268843 - 2025 - Relating surface water dynamics in wetlands and lakes to spatial variability in hydrologic signatures","interactions":[],"lastModifiedDate":"2025-07-08T15:05:18.801102","indexId":"70268843","displayToPublicDate":"2025-07-05T08:01:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21989,"text":"Wetland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Relating surface water dynamics in wetlands and lakes to spatial variability in hydrologic signatures","docAbstract":"The retention of surface water in wetlands and lakes can modify the timing, duration, and magnitude of river discharge. However, efforts to characterize the influence of surface water on discharge regimes have been generally limited to small, wetland-dense watersheds. We developed random forest models to explain spatial variability in six hydrologic signatures, reflecting flashiness, high, and low flow conditions, at 72 gaged watersheds with variable water storage capacity across the conterminous United States. In addition to variables representing meteorology and landscape characteristics, we also tested the inclusion of surface water dynamics, derived from Sentinel-1 and Sentinel-2. Models for all six signatures improved with the addition of catchment characteristics, including surface water dynamics, relative to models with only climate variables. Percent improvement in model adjusted R2, mean square error, and Akaike information criterion ranged from 4.00 to 14.33%, 5.00 to 20.30%, and 2.75–8.14, respectively. Automated variable selection can be indicative of the relative importance of certain variables over others. Using a forward selection process, five of the six signature models selected remotely sensed inundation or wetland variables (p < 0.05). For example, the variable semi-permanent and permanent (SP + P) floodplain inundation (i.e., lakes along rivers) was associated with lower annual flashiness. Further, SP + P non-floodplain waters and geographically isolated wetlands significantly contributed to explaining variability in the low flow signatures. Our findings underscore the capacity of wetlands to stabilize and maintain flows during dry periods. Improved understanding of how surface water dynamics influence hydrologic signatures can inform wetland restoration efforts and facilitate improved resilience to extreme flow conditions.
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Agency","active":true,"usgs":false}],"preferred":false,"id":942337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":238115,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","middleInitial":"R.","affiliations":[],"preferred":false,"id":942338,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keenan, William 0009-0007-4686-1796","orcid":"https://orcid.org/0009-0007-4686-1796","contributorId":357723,"corporation":false,"usgs":true,"family":"Keenan","given":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":942339,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":354442,"corporation":false,"usgs":true,"family":"Dolan","given":"Wayana","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":942340,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268886,"text":"70268886 - 2025 - The systematics of stable hydrogen (δ2H) and oxygen (δ18O) isotopes and tritium (3H) in the hydrothermal system of the Yellowstone Plateau volcanic field, USA","interactions":[],"lastModifiedDate":"2025-07-09T14:54:14.511597","indexId":"70268886","displayToPublicDate":"2025-07-04T07:48:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"The systematics of stable hydrogen (δ2H) and oxygen (δ18O) isotopes and tritium (3H) in the hydrothermal system of the Yellowstone Plateau volcanic field, USA","docAbstract":"To improve our understanding of hydrothermal activity on the Yellowstone Plateau volcanic field, we collected and analyzed a large data set of δ2H, δ18O, and the 3H concentrations of circum-neutral and alkaline waters. We find that (a) hot springs are fed by recharge throughout the volcanic plateau, likely focused through fractured, permeable tuff units. Previous work had stressed the need for light δ2H water recharge restricted to the northern part of the plateau or recharge during past cold periods. However, new data from the Y-7 drill hole suggests that recharge is not restricted to a certain area or a cold period. (b) δ18O values of thermal waters in the geyser basins are shifted from the global meteoric water line by temperature-dependent water-rock reactions with higher subsurface temperatures resulting in a greater shift. (c) Large temporal variations in the isotopic composition of meteoric water recharge and small temporal variability in the isotopic composition of hot spring discharge implies that the volume of groundwater in, and around the Yellowstone caldera is substantially larger than the volume of annual water recharge. (d) Hot springs discharged through different rhyolitic units correlate with identifiable differences in δ2H and δ18O compositions, 3H concentrations, and water chemistry that imply equilibration at different temperatures and travel along different flow paths. (e) Based on measured 3H concentrations, we calculate that hot spring waters in the central part of the geyser basins mostly contain <2% post-1950 meteoric water, whereas waters discharged at the basin margins contain larger fractions of post-1950s meteoric water.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GC012230","usgsCitation":"Hurwitz, S., McCleskey, R., Jurgens, B., Lowenstern, J.B., Clor, L., and Hunt, A.G., 2025, The systematics of stable hydrogen (δ2H) and oxygen (δ18O) isotopes and tritium (3H) in the hydrothermal system of the Yellowstone Plateau volcanic field, USA: Geochemistry, Geophysics, Geosystems, v. 26, no. 7, e2025GC012230, 19 p., https://doi.org/10.1029/2025GC012230.","productDescription":"e2025GC012230, 19 p.","ipdsId":"IP-174864","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":492080,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gc012230","text":"Publisher Index Page"},{"id":491895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Plateau volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.05101027973069,\n 44.981940603343645\n ],\n [\n -111.05101027973069,\n 43.58270636700257\n ],\n [\n -109.52640476499235,\n 43.58270636700257\n ],\n [\n -109.52640476499235,\n 44.981940603343645\n ],\n [\n -111.05101027973069,\n 44.981940603343645\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":942478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. 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Basic groundwater chemistry, including major ions, total dissolved solids, and selected trace metal concentrations, are presented and analyzed to characterize the Coconino aquifer. The geochemical compositions of groundwater are associated with changes in geology and groundwater movement and are compared to drinking-water standards to determine suitable areas for potential groundwater resource development. Dissolved-solids concentrations in much of the Coconino aquifer water were higher than the U.S. Environmental Protection Agency’s secondary drinking-water standard of 500 milligrams per liter (mg/L) due to a buried halite body in the southeastern part of the study area. However, trace metal concentrations were generally low. Groundwater may need to be treated for high dissolved-solids concentrations before it is suitable for use as a resource for the Hopi Tribe and Navajo Nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255038","collaboration":"Prepared in cooperation with the Hopi Tribe","usgsCitation":"Jones, C.J.R., 2025, Assessment of water chemistry of the Coconino aquifer in northeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2025–5038, 30 p., https://doi.org/10.3133/sir20255038.","productDescription":"viii, 30 p.","onlineOnly":"Y","ipdsId":"IP-158121","costCenters":[],"links":[{"id":491712,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5038/images"},{"id":491711,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255038/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5038"},{"id":491709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5038/coverthb.jpg"},{"id":491710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5038/sir20255038.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5038"},{"id":491713,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5038/sir20255038.XML"}],"country":"United States","state":"Arizona","otherGeospatial":"Coconino aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.25,\n 35.5\n ],\n [\n -111.25,\n 34.5\n ],\n [\n -109.5,\n 34.5\n ],\n [\n -109.5,\n 35.5\n ],\n [\n -111.25,\n 35.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
520 N. Park Avenue, Suite 221
Tucson, AZ 85719
Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish (Danio rerio) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. More costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.4c14607","usgsCitation":"Behrens, J.R., Joyce, A., Ferguson, P., Kolpin, D., Jayasundara, N., Barbo, N., and Bernhardt, E., 2025, Integrating contaminant source indicators, water quality measures, and ecotoxicity to characterize contaminant mixtures and per- and polyfluoroalkyl substances (PFAS) variability in an urban watershed: Environmental Science & Technology, v. 59, no. 27, p. 13958-13969, https://doi.org/10.1021/acs.est.4c14607.","productDescription":"12 p.","startPage":"13958","endPage":"13969","ipdsId":"IP-168094","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501643,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12269787/","text":"External Repository"},{"id":492762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Ellerbe Creek, New Hope Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.85,\n 36.1667\n ],\n [\n -79.25,\n 36.1667\n ],\n [\n -79.25,\n 35.9\n ],\n [\n -78.85,\n 35.9\n ],\n [\n -78.85,\n 36.1667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"27","noUsgsAuthors":false,"publicationDate":"2025-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Behrens, J. 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This study implemented a novel approach to identify the relative contributions of various landscape and stream sources of sediment from the Back River watershed in eastern Baltimore, Maryland, and investigated the applicability of using trace PCBs found in an urban environment as discriminants between each source type. Trace PCBs were found to be poor discriminants when identifying the relative sediment contributions of watershed-scale land use categories. When excluding PCBs in the development of a sediment fingerprinting model and instead utilizing trace elements and carbon only, sediment fingerprint modeling successfully differentiated green spaces and eroding streambanks as the most significant contributors to stormwaters sediment (37.1 % and 44.0 %, respectively) of the total sediment contributions of all considered source categories. In all samples collected from various landscape sources, storms, and cores detectable concentrations of PCBs were measured. The results of this study indicate that sediment fingerprinting may not be an effective method in predicting where PCBs may be found within an impacted watershed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104657","usgsCitation":"Foss, E.P., Clifton, Z.J., Majcher, E.H., Needham, T.P., and Psoras, A.W., 2025, Contaminated stormwater sediment source tracking for polychlorinated biphenyls in an urban watershed of the Chesapeake Bay, United States: Journal of Contaminant Hydrology, v. 274, 104657, 16 p., https://doi.org/10.1016/j.jconhyd.2025.104657.","productDescription":"104657, 16 p.","ipdsId":"IP-177312","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","city":"Baltimore","otherGeospatial":"Back River watershed, Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.50954075138807,\n 39.32799166380633\n ],\n [\n -76.50954075138807,\n 39.256713104432606\n ],\n [\n -76.43110757990168,\n 39.256713104432606\n ],\n [\n -76.43110757990168,\n 39.32799166380633\n ],\n [\n -76.50954075138807,\n 39.32799166380633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"274","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foss, Ellie P. 0000-0001-9090-4617","orcid":"https://orcid.org/0000-0001-9090-4617","contributorId":290902,"corporation":false,"usgs":true,"family":"Foss","given":"Ellie","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Majcher, Emily H. 0000-0001-7144-6809","orcid":"https://orcid.org/0000-0001-7144-6809","contributorId":203335,"corporation":false,"usgs":true,"family":"Majcher","given":"Emily","middleInitial":"H.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Needham, Trevor P. 0000-0001-9356-4216","orcid":"https://orcid.org/0000-0001-9356-4216","contributorId":245024,"corporation":false,"usgs":true,"family":"Needham","given":"Trevor","email":"","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Psoras, Andrew W. 0000-0002-1779-5079","orcid":"https://orcid.org/0000-0002-1779-5079","contributorId":347166,"corporation":false,"usgs":true,"family":"Psoras","given":"Andrew","middleInitial":"W.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955725,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268792,"text":"sir20255049 - 2025 - Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2026-01-26T19:27:33.044408","indexId":"sir20255049","displayToPublicDate":"2025-07-03T07:22:30","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5049","displayTitle":"Completion Summary for Monitor Wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho","title":"Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho","docAbstract":"The U.S. Geological Survey (USGS)—in cooperation with the U.S. Department of Energy (DOE) for the Naval Reactors Laboratory Field Office that supports operations for the Naval Reactors Facility (NRF) located at the Idaho National Laboratory (INL)—drilled and constructed well NRF-17 (formerly borehole USGS 151) and well NRF-18 (formerly borehole USGS 152) for stratigraphic framework analyses and water-quality monitoring at the Idaho National Laboratory (INL) near the NRF, in southeastern Idaho. Borehole USGS 151 was continuously cored from about 48 to 1,070 feet (ft) below land surface (BLS); rotary drilled from approximately 1,070 to 1,720 ft BLS; and re-drilled to complete construction as a monitor well NRF-17, completed to 461 ft BLS. Borehole USGS 152 was continuously cored from approximately 19 to 1,259 ft BLS; rotary drilled from approximately 1,259 to 1,630 ft BLS; and re-drilled to complete construction as a monitor well NRF-18, completed to 450 ft BLS.
Geophysical data were examined with photographed core material to record lithologic descriptions and to suggest zones where groundwater flow was anticipated. Basalt flows varied from highly fractured to dense, with high-to-low vesiculation. Well NRF-17 generally was constructed in mostly dense basalt (greater than 75 percent), and well NRF-18 was constructed in primarily fractured and (or) vesicular basalt. In well NRF-17, the well capacity is directly affected by the limited amount of fractured basalt, which serves as the primary pathway for groundwater. This effect was observed during the pumping test conducted after the well's final construction.
Single-well aquifer tests were done at wells NRF-17 and NRF-18 to provide estimates of transmissivity and hydraulic conductivity after final well construction and initial well development. Estimated values of transmissivity and hydraulic conductivity for well NRF-17 were 8.81 feet squared per day (ft2/d) and 1.04×10-2 feet per day (ft/d), respectively. Estimated values of transmissivity and hydraulic conductivity for well NRF-18 were 4.77×103 ft2/d and 5.61 ft/d, respectively. The NRF-17 pump test resulted in 19.41 ft of measured drawdown at a sustained average pumping rate of 3.3 gallons per minute (gal/min). The NRF-18 pump test resulted in 0.55 ft of measured drawdown at a sustained average pumping rate of 31.0 gal/min.
Water-quality samples collected from the two wells were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for select inorganic constituents showed concentrations consistent with signatures from tributary valley groundwater with influences from ephemeral surface-water recharge from the Big Lost River. Water-quality samples analyzed for stable isotopes of oxygen and hydrogen are consistent with signatures from tributary valley groundwater and surface-water recharge inputs to the aquifer. No measured water-quality results were greater than their respective maximum contaminant levels for public drinking-water supplies. Inorganic and nutrient water-quality results for well NRF-17 and well NRF-18 suggest the groundwater in this area is potentially affected by industrial wastewater disposal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255049","collaboration":"Prepared in cooperation with the U.S. Department of Energy","programNote":"DOE/ID-22264","usgsCitation":"Twining, B.V., Treinen, K.C., and Zingre, J.A., 2025, Completion summary for monitor wells NRF-17 and NRF-18 at the Naval Reactors Facility, Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report\n2025–5049, 37 p., https://doi.org/10.3133/sir20255049.","productDescription":"Report: vii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-159224","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":491691,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5049/images"},{"id":491690,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13URUXF","text":"USGS data release","description":"USGS data release","linkHelpText":"Single-well aquifer test data from wells NRF-17 and NRF-18, Idaho National Laboratory, Idaho"},{"id":499046,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118682.htm","linkFileType":{"id":5,"text":"html"}},{"id":491692,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5049/sir20255049.XML"},{"id":491688,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5049/sir20255049.pdf","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5049"},{"id":491687,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5049/coverthb.jpg"},{"id":491689,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255049/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5049"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory, Naval Reactors Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.5,\n 44\n ],\n [\n -113.5,\n 44\n ],\n [\n -113.5,\n 43.25\n ],\n [\n -112.5,\n 43.25\n ],\n [\n -112.5,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m3) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL115911","usgsCitation":"Karasozen, E., West, M.E., Barnhart, K.R., Lyons, J.J., Nichols, T., Schaefer, L.N., Bahng, B., Ohlendorf, S., Staley, D.M., and Wolken, G.J., 2025, 2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska: Geophysical Research Letters, v. 52, no. 13, e2025GL115911, 11 p., https://doi.org/10.1029/2025GL115911.","productDescription":"e2025GL115911, 11 p.","ipdsId":"IP-176964","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":492061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl115911","text":"Publisher Index Page"},{"id":491813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.69339399398933,\n 61.18214394792622\n ],\n [\n -148.69339399398933,\n 59.91280847695441\n ],\n [\n -145.64673816140657,\n 59.91280847695441\n ],\n [\n -145.64673816140657,\n 61.18214394792622\n ],\n [\n -148.69339399398933,\n 61.18214394792622\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"13","noUsgsAuthors":false,"publicationDate":"2025-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Karasozen, Ezgi 0000-0003-1140-1427","orcid":"https://orcid.org/0000-0003-1140-1427","contributorId":244223,"corporation":false,"usgs":false,"family":"Karasozen","given":"Ezgi","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":942014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"West, Michael E.","contributorId":147407,"corporation":false,"usgs":false,"family":"West","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":942015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":942016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":942017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, Terry","contributorId":357616,"corporation":false,"usgs":false,"family":"Nichols","given":"Terry","affiliations":[{"id":85473,"text":"National Tsunami Warning Center, Palmer, Alaska, USA","active":true,"usgs":false}],"preferred":false,"id":942018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":942019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bahng, Bohyun","contributorId":357617,"corporation":false,"usgs":false,"family":"Bahng","given":"Bohyun","affiliations":[{"id":85473,"text":"National Tsunami Warning Center, Palmer, Alaska, USA","active":true,"usgs":false}],"preferred":false,"id":942020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ohlendorf, Summer","contributorId":357618,"corporation":false,"usgs":false,"family":"Ohlendorf","given":"Summer","affiliations":[{"id":85473,"text":"National Tsunami Warning Center, Palmer, Alaska, USA","active":true,"usgs":false}],"preferred":false,"id":942021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":942022,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wolken, Gabriel J.","contributorId":221149,"corporation":false,"usgs":false,"family":"Wolken","given":"Gabriel","email":"","middleInitial":"J.","affiliations":[{"id":40336,"text":"Alaska Department of Natural Resources: Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":942023,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70268143,"text":"sir20235101 - 2025 - Hydraulic conductivity and transmissivity estimates from slug tests in wells within the Mississippi Alluvial Plain, Arkansas and Mississippi, 2020","interactions":[],"lastModifiedDate":"2026-01-26T19:15:04.764709","indexId":"sir20235101","displayToPublicDate":"2025-07-02T07:37:05","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":"2023-5101","displayTitle":"Hydraulic Conductivity and Transmissivity Estimates from Slug Tests in Wells Within the Mississippi Alluvial Plain, Arkansas and Mississippi, 2020","title":"Hydraulic conductivity and transmissivity estimates from slug tests in wells within the Mississippi Alluvial Plain, Arkansas and Mississippi, 2020","docAbstract":"During the spring and summer of 2020, the U.S. Geological Survey conducted single-well slug tests on selected observation wells within the Mississippi Alluvial Plain in Arkansas and Mississippi to estimate hydraulic conductivity and transmissivity values for the Mississippi River Valley alluvial and middle Claiborne aquifers. Well and aquifer data were collected from field measurements, well-construction reports, and published aquifer-thickness information. A total of 324 slug-in and slug-out tests were conducted on 48 wells by using mechanical slugs to displace the water column and submersible pressure transducers to record changes in water levels in the wells. Hydraulic conductivity of the aquifers in which the wells are screened was estimated by curve fitting the water-level-change data using aquifer test analysis software. Estimates of aquifer transmissivity were made by multiplying the estimated hydraulic conductivity value by the aquifer thickness at well locations. Mean hydraulic conductivity estimates for 44 observation wells screened in the Mississippi River Valley alluvial aquifer range from 3 to 401 feet per day, and mean transmissivity estimates range from 285 to 80,559 feet squared per day. Mean hydraulic conductivity estimates for four observation wells screened in units of the middle Claiborne aquifer range from 0.14 to 183 feet per day, and mean transmissivity estimates range from 55 to 67,913 feet squared per day. The results from these tests can be used to improve the understanding of water availability and groundwater migration, to refine groundwater models, and to ultimately provide stakeholders and decisionmakers better information for management of the groundwater resources within the Mississippi Alluvial Plain.
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":"This report summarizes results from boat-based, high-resolution water-quality mapping surveys completed before, during, and after upgrades to the EchoWater Resource Recovery Facility (EchoWater Facility), the regional wastewater facility for the City of Sacramento and surrounding areas, near Elk Grove, California. Surveys were completed in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) in spring (May or June) 2018, 2020, 2021, and 2022. In each survey, a suite of in situ sensors were used to continuously (one measurement per second) measure water-quality conditions, nutrients, phytoplankton abundance, and species composition. In addition to in situ data collection, discrete water samples were collected about every 2 miles while underway for determination of phosphate, ammonium, and nitrate concentration. The boat stopped at about 30 locations to collect discrete samples for a suite of additional analytes, including phytoplankton enumeration. The four surveys represent snapshots in time across different phases of the EchoWater Facility Biological Nutrient Reduction (BNR) upgrade. The May 2018 survey represents conditions before the upgrade. The second survey (June 2020) represents conditions after implementation of the Nitrifying Sidestream Treatment. The third survey (May 2021) was completed immediately after the completion of the BNR upgrade and represents a transitional period, and the final survey (May 2022) represents post-upgrade conditions.
Relevant hydrologic and climatic context such as water-year type, X2 position (the distance from the Golden Gate Bridge to the point upstream where bottom salinity is 2 parts per thousand; Jassby and others, 1995), water export to import ratio, and management actions like the Delta Cross Channel gate operations are presented for each survey so they may be considered in comparisons among surveys. Differences in water-quality parameters, like turbidity, temperature, salinity, pH, and dissolved oxygen (DO) improve understanding of nutrient cycling and phytoplankton dynamics. Because the Delta is a complex system, we divided the study area into hydrologic zones to better examine general trends and obtain a broadscale view of differences among the 4 study years. Results are presented for each survey and parameter using box plots to compare the different hydrologic zones. We also present each parameter using contour maps by survey to display gradients across the system.
The most evident change to water quality in the Delta across surveys is related to the EchoWater Facility BNR upgrade, which included nitrification and denitrification processes. Through this upgrade, effluent ammonium (NH4+) concentrations were reduced by more than 95 percent (from about 2,000 micromolars [μM] to below the reporting limit of 35 μM), and nitrate (NO3−) concentrations increased from near zero to about 500 μM; therefore, the concentration of dissolved inorganic nitrogen (DIN; the sum of NH4+ and NO3−) in the effluent was reduced by about 75 percent between May 2018 and May 2022. The BNR upgrade resulted in a reduction in NH4+ concentrations in aquatic habitats immediately below the facility, designated as the “north Delta tidal transition zone” (Bergamaschi and others, 2024), from about 30 μM pre-upgrade to near zero during the 2022 spring survey, whereas effluent NO3− increased from median concentrations of about 7 μM to about 15 μM. Because of the reduced effluent nitrogen loads and variability in Sacramento River nitrogen loads from upstream sources, DIN concentrations in the north Delta tidal transition zone decreased from a median of 53.3 μM in 2018 to 35.3 μM in 2020, 20.7 μM in 2021, and 11.3 μM in 2022 during the spring surveys.
The changes in DIN concentration and form observed in the north Delta tidal transition zone after the EchoWater Facility upgrade extended downstream but were rapidly altered by hydrologic mixing, biogeochemical processes, and other nutrient source inputs. Most of the Delta indicated near-zero concentrations of NH4+ 1 year after the completion of the EchoWater Facility upgrades represented by the 2022 survey. Exceptions to this finding were observed in the San Joaquin River near Stockton and in Suisun Bay, indicating there are NH4+ inputs to these locations from other sources (for example, Stockton Regional Wastewater Control Facility and Central Contra Costs Sanitary District wastewater treatment plants or agricultural and urban runoff).
Although there was an increase in NO3− concentrations in the north Delta tidal transition zone after the upgrade, increases in NO3− in other zones were not apparent, presumably because nitrification of effluent derived ammonium was no longer a source of NO3−. Concentrations of DIN in many Delta zones were lower in 2022 compared to 2018 and 2020, with concentrations near or below what is considered potentially nitrogen limiting conditions for phytoplankton growth in the North Delta tidal transition zone and the Cache Slough complex channel system. Unrelated to the EchoWater Facility upgrade, NO3− and therefore DIN concentrations increased in the San Joaquin River near Stockton and in adjacent water bodies by survey date (likely associated with increasing drought conditions). The Mokelumne River had low DIN concentrations, except in 2018 when the Delta Cross Channel was open, which allowed nutrient-rich Sacramento River water to flow into this section of the river. Data from these surveys also support the hypothesis that nutrient drawdown during phytoplankton blooms may create localized nitrogen limiting conditions.
The BNR upgrade resulted in lower effluent phosphate (PO43−) concentrations, which lowered PO43− concentrations in some zones of the Delta during the four spring surveys; however, PO43− concentrations throughout the Delta remained above 0.3 μM, indicating that primary productivity was not limited by phosphorous availability. DIN and PO43− decreased after the upgrade in many areas of the Delta, and the DIN to dissolved inorganic phosphorus (DIN:DIP) ratio remained similar to pre-upgrade conditions and was often below the Redfield Ratio of 16, indicating nitrogen is more likely to limit phytoplankton growth than phosphorous. Inputs of dissolved organic carbon (DOC) from the EchoWater Facility are a minor source of this constituent to the Delta, so the upgrade had little to no effect on DOC concentrations across the Delta.
Because phytoplankton abundance and species composition in the Delta are shaped by multiple factors other than nutrients (for example, light availability, temperature, salinity, and predation), it is important to consider these factors (as well as long-term monitoring) in addition to the EchoWater Facility upgrade. Although phytoplankton populations were low across much of the Delta during the spring surveys, several localized phytoplankton blooms (defined here as greater than 15 micrograms per liter [μg/L] of chlorophyll) provide insight into conditions that may favor the growth of beneficial and harmful species.
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6000 J Street, Placer Hall
Sacramento, California 95819
Biosecurity practices are essential for maintaining pig health and productivity. Despite these measures, pathogen spread still occurs. Water is one of the largest daily inputs on swine farms by volume and is not routinely tested or disinfected before it is consumed by the animals [1-3], making it a poorly understood biosecurity risk. Groundwater from privately-owned wells is a common water source for swine farms. Pathogens in the landscape, such as bacteria, viruses, and protozoa, can reach groundwater more rapidly through soil macropores, maintaining viability and facilitating transmission of pathogens into aquifers [3-13].
","conferenceTitle":"2025 ISU James D. McKean Swine Disease Conference","conferenceDate":"June 24-25, 2025","conferenceLocation":"Ames, IA","language":"English","publisher":"Iowa State University Swine Disease Conference; American Association of Swine Veterinarians Library","usgsCitation":"Doughan, G., Walthart, B., Moncrief, M., Snezek, E., Skoland, K., Firnstahl, A.D., Gauger, P., Brown, J., Bonnema, J.L., Borchardt, M.A., Heffron, J., Stokdyk, J.P., Burch, T., and Karriker, L., 2025, Groundwater surveillance of swine pathogens from private wells supplying swine farms in Iowa, 2025 ISU James D. 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Kristin","contributorId":365000,"corporation":false,"usgs":false,"family":"Skoland","given":"Kristin","affiliations":[],"preferred":false,"id":953572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gauger, Phillip","contributorId":365004,"corporation":false,"usgs":false,"family":"Gauger","given":"Phillip","affiliations":[],"preferred":false,"id":953574,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Justin","contributorId":348806,"corporation":false,"usgs":false,"family":"Brown","given":"Justin","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":953575,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bonnema, J. L.","contributorId":365010,"corporation":false,"usgs":false,"family":"Bonnema","given":"J.","middleInitial":"L.","affiliations":[],"preferred":false,"id":953576,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":953577,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Heffron, Joe","contributorId":339799,"corporation":false,"usgs":false,"family":"Heffron","given":"Joe","email":"","affiliations":[],"preferred":false,"id":953578,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953579,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Burch, Tucker R.","contributorId":195801,"corporation":false,"usgs":false,"family":"Burch","given":"Tucker R.","affiliations":[],"preferred":false,"id":953580,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Karriker, Locke","contributorId":356382,"corporation":false,"usgs":false,"family":"Karriker","given":"Locke","affiliations":[{"id":84984,"text":"Iowa State University, Swine Medicine Education Center, Ames, IA, United States","active":true,"usgs":false}],"preferred":false,"id":953581,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70268753,"text":"70268753 - 2025 - Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions","interactions":[],"lastModifiedDate":"2025-07-08T16:36:55.393587","indexId":"70268753","displayToPublicDate":"2025-07-01T09:29:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions","docAbstract":"Study region: Headwaters of the upper Colorado River basin (UCOL), USA
Study focus: Surface-water and groundwater numerical models incorporating water-use information were used to investigate changes in climate, water use, and simulated hydrologic responses of snow processes, evapotranspiration, groundwater, and streamflow during recent wet (1982–1999) and drought (2000–2022) periods in the headwater subregions of the upper Colorado River basin.
New hydrologic insights for the region: Decreases in average streamflow between wet and drought periods ranged from 20 % in the Colorado River headwaters subregion to 23 % in the Gunnison River headwaters subregion. Like streamflow, average surface runoff was statistically less during the drought than the wet period, with decreases from 24–31 % in the headwaters. On a volume basis, runoff decreases were greater than streamflow decreases in both the Colorado River and Gunnison River headwaters. Although the amount of water-year groundwater discharge to streams remained nearly the same between the wet and drought periods, groundwater as a percentage of streamflow increased between the wet and drought periods, highlighting the importance of groundwater in sustaining streamflow during drought conditions. Multiple linear regression analyses revealed that snowmelt-only models were better than the best precipitation and temperature models at explaining streamflow variability from all headwater subregions for both the wet and drought periods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2025.102554","usgsCitation":"Tillman, F.D., Masbruch, M.D., Knight, J., Engott, J.A., Lopez, S.F., Jones, C.J., Dickinson, J.E., and Miller, M., 2025, Hydrologic response of groundwater and streamflow to natural and anthropogenic drivers of change in headwaters of the upper Colorado River basin during recent wet (1982–1999) and drought (2000–2022) conditions: Journal of Hydrology: Regional Studies, v. 60, 102554, 19 p., https://doi.org/10.1016/j.ejrh.2025.102554.","productDescription":"102554, 19 p.","ipdsId":"IP-176624","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":492063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2025.102554","text":"Publisher Index Page"},{"id":491819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"upper Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.83855791620346,\n 42.22226218528715\n ],\n [\n -110.83855791620346,\n 35.70206223466056\n ],\n [\n -106.7875698491801,\n 35.70206223466056\n ],\n [\n -106.7875698491801,\n 42.22226218528715\n ],\n [\n -110.83855791620346,\n 42.22226218528715\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Jacob E. 0000-0003-0271-9011","orcid":"https://orcid.org/0000-0003-0271-9011","contributorId":204140,"corporation":false,"usgs":true,"family":"Knight","given":"Jacob E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Samuel Francisco 0000-0002-3544-7465","orcid":"https://orcid.org/0000-0002-3544-7465","contributorId":344607,"corporation":false,"usgs":true,"family":"Lopez","given":"Samuel","email":"","middleInitial":"Francisco","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Casey J.R. 0000-0002-6991-8026","orcid":"https://orcid.org/0000-0002-6991-8026","contributorId":223364,"corporation":false,"usgs":true,"family":"Jones","given":"Casey","email":"","middleInitial":"J.R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941867,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269863,"text":"70269863 - 2025 - Angler dynamics in the St. Clair-Detroit River System after decades of change","interactions":[],"lastModifiedDate":"2025-12-15T16:29:47.588803","indexId":"70269863","displayToPublicDate":"2025-07-01T09:25:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Angler dynamics in the St. Clair-Detroit River System after decades of change","docAbstract":"Habitat and water quality were historically degraded within the St. Clair-Detroit River System (SCDRS). Beginning in 2004, extensive habitat restoration projects were implemented remediating losses of fish spawning beds and shoreline areas. Monitoring of post-restoration activities documented recovering fish populations; however, angler response remains unknown. Extensive creel surveys were conducted pre-restoration (2002–2004), but post-restoration (2012 and later) surveys were intermittent. The goal of this project was to examine both to create a comprehensive picture of the effects of restoration on angling. We calculated catch and harvest rates and inspected answers to supplemental questions collected by state and provincial agencies. We estimated economic impact of angling with a combination of lodging and gas expenses. Post-restoration, catch rates were higher, but harvest rates were variable for Lake St. Clair and the Detroit River. The 2017 open water boat fishery on Lake St. Clair was worth ∼$26 million. Increased fishing opportunities resulting from continued habitat and population recovery are leading to increased catch rates and likely attracting anglers to the area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102610","usgsCitation":"Castle, D., Galarowitz, T., Roseman, E., Claramunt, T., Chiotti, J., and Dvorak, R., 2025, Angler dynamics in the St. Clair-Detroit River System after decades of change: Journal of Great Lakes Research, v. 51, no. 6, 102610, 9 p., https://doi.org/10.1016/j.jglr.2025.102610.","productDescription":"102610, 9 p.","ipdsId":"IP-114671","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":493563,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Clair-Detroit River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.32107024202449,\n 43.006850820856755\n ],\n [\n -82.49276432463705,\n 43.05309054601082\n ],\n [\n -82.89037167384419,\n 42.65229703000273\n ],\n [\n -83.21116851240926,\n 42.29236828270675\n ],\n [\n -83.25635116572803,\n 42.22214183316797\n ],\n [\n -83.32864341103848,\n 41.87992998994085\n ],\n [\n -83.05754749112448,\n 42.02777689684618\n ],\n [\n -82.94007259249524,\n 42.29236828270675\n ],\n [\n -82.49276432463705,\n 42.23886950969248\n ],\n [\n -82.36625289534328,\n 42.32578195995458\n ],\n [\n -82.37528942600714,\n 42.54919596223701\n ],\n [\n -82.32107024202449,\n 43.006850820856755\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Castle, Dana","contributorId":334167,"corporation":false,"usgs":false,"family":"Castle","given":"Dana","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":944777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galarowitz, T.","contributorId":359009,"corporation":false,"usgs":false,"family":"Galarowitz","given":"T.","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":944778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":216805,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":944779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Claramunt, T.","contributorId":359011,"corporation":false,"usgs":false,"family":"Claramunt","given":"T.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":944780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiotti, J.","contributorId":207832,"corporation":false,"usgs":false,"family":"Chiotti","given":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":944781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dvorak, R.","contributorId":359014,"corporation":false,"usgs":false,"family":"Dvorak","given":"R.","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":944782,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70268991,"text":"70268991 - 2025 - Salmonid sensory system development is affected by climate change driven temperature increases","interactions":[],"lastModifiedDate":"2025-07-14T14:10:12.219343","indexId":"70268991","displayToPublicDate":"2025-07-01T09:08:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Salmonid sensory system development is affected by climate change driven temperature increases","docAbstract":"Increases in water temperature due to global climate change are known to alter the course and timing of fish development. The mechanosensory lateral line (LL) system mediates flow-sensing behaviors vital for survival in fishes, but the effects of increased water temperatures resulting from climate change on its development have not been examined. Here LL development was documented in a cold-water salmonid (brook trout, Salvelinus fontinalis) reared at the thermograph of a long-term study stream (ambient) and two higher temperatures (+ 2 and + 4 °C) that reflect projected increases within their native range. At these two higher temperatures, fish reach crucial early life history transitions earlier (e.g., hatch, “swim-up” from gravel nests into the water column) and are larger in size through the parr (juvenile) stage. Early forming canal neuromast receptor organs are larger, and the process of canal morphogenesis is also accelerated suggesting potential consequences for neuromast function and presumably for LL-mediated behaviors. A potential mismatch between the timing of transitions in early life history stages, the ability to carry out LL-mediated behaviors (e.g., prey detection), and the timing of the seasonal emergence of their preferred prey, could have serious implications for cold-water salmonid ecology and survival.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-99784-1","usgsCitation":"Jones, A., O'Donnell, M., Regish, A.M., and Webb, J., 2025, Salmonid sensory system development is affected by climate change driven temperature increases: Scientific Reports, v. 15, 20901, 13 p., https://doi.org/10.1038/s41598-025-99784-1.","productDescription":"20901, 13 p.","ipdsId":"IP-161230","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":492487,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-99784-1","text":"Publisher Index Page"},{"id":492198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2025-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Aubree","contributorId":357897,"corporation":false,"usgs":false,"family":"Jones","given":"Aubree","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":942838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":299019,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":942839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":942840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Jacqueline","contributorId":357899,"corporation":false,"usgs":false,"family":"Webb","given":"Jacqueline","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":942841,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270831,"text":"70270831 - 2025 - Lake Ontario spring prey fish bottom trawl survey and Alewife assessment, 2025","interactions":[],"lastModifiedDate":"2025-08-26T14:31:22.279024","indexId":"70270831","displayToPublicDate":"2025-07-01T09:00:14","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lake Ontario spring prey fish bottom trawl survey and Alewife assessment, 2025","docAbstract":"The multi-agency Lake Ontario spring prey fish survey quantifies changes in pelagic prey fish populations, in particular Alewife Alosa pseudoharengus, which are the primary prey supporting the lake’s sport fishes. The 2025 survey included 230 trawls in the main lake and embayments and sampled depths from 5.5 to 245 m (15 – 810 ft). The survey captured 504,541 fish from 33 species with a total weight of 7,301 kg (16,095 lbs). Alewife were 85% of the total catch numerically, while Yellow Perch Perca flavescens, Round Goby Neogobius melanostomus, Deepwater Sculpin Myoxocephalus thompsonii, and Rainbow Smelt Osmerus mordax, comprised 5%, 4%, 3%, and 1% of the catch, respectively.
The Alewife biomass index decreased from 2024 to 2025 (83 to 78 kg·ha-1) however due to an abundant 2024 Alewife year class the density index increased from 3,727 to 9,182 fish per ha-1. The Age-1 biomass (2024 year class) was 27.5 kg·ha-1, which was the greatest value estimated in the modern time series (since 1997). The abundance estimate for the 2024 Alewife year class (13.8 billion) was more than three times the number of all other Alewife combined (3.6 billion). Adult Alewife abundance decreased in 2025 which was consistent with predictions from 2024. Those predictive models suggested that adult Alewife biomass is likely to increase in 2026 and 2027, as the 2024 year class matures. Alewife condition declined in 2025, which was expected given the relatively high Alewife density. Acoustic-based prey fish densities were greater than previous years acoustic estimates especially at depths from 180 – 220 m (591 – 722 ft), however acoustic based densities continue to be substantially lower than trawl-based densities.
The 2025 biomass index was similar to 2024 for Emerald Shiner Notropis atherinoides and Threespine Stickleback Gasterosteus aculeatus, but was lower for Rainbow Smelt, and higher for Cisco Coregonus artedi. Three purported Bloater Coregonus hoyi were caught in the 2025 survey. Analysis of archived tissue identified five Bloater captured in previous surveys which increased the total number caught in Lake Ontario bottom trawl surveys to n = 24, since restoration stocking began in 2012. Whole lake density estimates of Lake Whitefish Coregonus clupeaformis increased in 2025 relative to 2024. Those density increases were due to increased catches in Canadian waters, as density in U.S. waters has remained low. The density index for wild or naturally reproduced juvenile Lake Trout Salvelinus namaycush increased in 2025 relative to 2024, with the most frequent catches occurring in waters around the Niagara River.
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Since 2014, multiple large-scale seabird mortality events have occurred in Alaska waters, with STXs detected in some carcasses. To investigate the sublethal behavioral and ecological effects of STX on seabirds, we conducted captive dosing trials with common murres (Uria aalge). We gavaged purified STX (dehydrated STX dihydrocholoride, STX-diHCl) or an Alexandrium catenella culture extract into murres, monitored behavioral responses and recovery times, and assessed tissue concentrations in individuals that died or were euthanized. Using a modified up-and-down dose-finding scheme, we estimated a median effective dose (ED50) of 89 µg STX-equivalents (eq) kg-1 for STX-diHCl and 366 µg STX-eq kg-1 for the A. catenella extract based on ecologically relevant behavior. Differences between the ED50 estimates could reflect uncertainties in toxin equivalency factors for PST congeners, which are based on studies using purified toxins in mice and may vary across taxa or toxin matrices. Post-dosing concentrations of STX varied by tissue type across individuals, with quantifiable levels ranging from 3 to 379 µg STX-eq 100g-1. Evidence of biotransformation of STX in A. catenella extract-dosed birds was observed. We also measured the chronic effects of dosing with sublethal levels of STX-diHCl over seven-days, which resulted in lower fish intake among treatment birds compared to controls (-187 g day-1). This investigation improves our understanding of the ecological effects of PSTs on seabird health.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2025.102919","usgsCitation":"Smith, M.M., Dusek, R.J., Hollmen, T.E., Schoen, S.K., Van Hemert, C.R., Steinmetzer, K., Lee, A., Schlenner, J., Patil, V.P., Hardison, D., Kulis, D., Anderson, D.M., Ridge, C.D., and Hall, S., 2025, Paralytic shellfish toxins and seabirds: Evaluating sublethal effects, behavioral responses, and ecological implications of saxitoxin ingestion by common murres (Uria aalge): Harmful Algae, v. 148, 102919, 13 p., https://doi.org/10.1016/j.hal.2025.102919.","productDescription":"102919, 13 p.","ipdsId":"IP-163602","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":494461,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2025.102919","text":"Publisher Index 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To deal with these effects, the use of stormwater control measures that aim to disconnect impervious surfaces and prevent stormwater from reaching the stream has surged. However, we lack widespread use of consistent metrics that describe how effective these stormwater control measures are for mitigating the effects of untreated stormwater. Using total impervious area neglects the effect of stormwater control measures whereas directly-connected impervious area assumes that stormwater control measures perform perfectly. Comparing the success of stormwater control measures across many watersheds and cities will require use of consistent metrics of effective imperviousness, describing actual performance of stormwater control measures in reducing impervious areas hydraulically connected to the stream. This work applies two published approaches to quantify effective imperviousness, one that measures the frequency of downstream flow disturbances and another that computes parameters from a paired rainfall-runoff regression analysis. We apply these approaches in two settings: 1) two watersheds with new low impact development in Clarksburg, Maryland, USA and 2) five watersheds with stormwater retrofits in Melbourne, Australia. These methods gave largely similar results, with differences in effective imperviousness ranging from 1%-9%. Using these approaches in Clarksburg, the effective imperviousness for the treatment watersheds was 6–12%, whereas the total imperviousness was 33–44% and the directly-connected imperviousness was 0%. In Clarksburg, effective imperviousness better described stream hydrologic and biotic outcomes compared to either total imperviousness or directly-connected imperviousness. In Melbourne, effective imperviousness was a better metric for hydrologic and water quality changes that are likely to provide ecological benefits. In both cases, new development and retrofits, we demonstrate the utility of effective imperviousness metrics for predicting stream outcomes and how these metrics may be used to understand the success of stormwater control measure using a consistent metric.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pwat.0000335","usgsCitation":"Bhaskar, A.S., Stillwell, C.C., Burns, M.J., Hopkins, K.G., and Walsh, C.J., 2025, Quantifying the success of stormwater control measure networks using effective imperviousness: PLOS Water, v. 4, no. 6, e0000335, 18 p., https://doi.org/10.1371/journal.pwat.0000335.","productDescription":"e0000335, 18 p.","ipdsId":"IP-171981","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":492076,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000335","text":"Publisher Index Page"},{"id":491849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhaskar, Aditi S.","contributorId":199824,"corporation":false,"usgs":false,"family":"Bhaskar","given":"Aditi","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":941752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stillwell, Charles C. 0000-0002-4571-4897","orcid":"https://orcid.org/0000-0002-4571-4897","contributorId":270394,"corporation":false,"usgs":true,"family":"Stillwell","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Matthew J.","contributorId":146251,"corporation":false,"usgs":false,"family":"Burns","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16645,"text":"Waterway Ecosystem Research Group, School of Ecosystem and Forest Sciences, The","active":true,"usgs":false}],"preferred":false,"id":941754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Christopher J.","contributorId":171683,"corporation":false,"usgs":false,"family":"Walsh","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":941756,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268830,"text":"70268830 - 2025 - Pyrethroid insecticides implicated in mass mortality of monarch butterflies at an overwintering site in California","interactions":[],"lastModifiedDate":"2025-11-18T16:52:10.629121","indexId":"70268830","displayToPublicDate":"2025-06-28T11:04:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Pyrethroid insecticides implicated in mass mortality of monarch butterflies at an overwintering site in California","docAbstract":"Since the 1980s, monarch butterfly (Danaus plexippus plexippus) populations across North America have declined by 80–95%. Although several studies have implicated pesticides as a contributing factor to their population declines, our understanding of monarch exposure levels in nature remains limited. In January 2024, a mass mortality event near an overwintering site in Pacific Grove, California, USA, provided an opportunity to analyze dead overwintering monarch butterflies for pesticide residues. Ten recently deceased butterflies were collected and analyzed using liquid and gas chromatography with tandem mass spectrometry (LC-MS/MS and GC-MS/MS). We identified a total of 15 pesticides and associated metabolites in the butterflies, including 8 insecticides (plus 1 associated metabolite), 2 herbicides (plus 2 associated metabolites), and 2 fungicides. On average, each monarch butterfly contained 7 pesticides, excluding transformation products if the parent compound was also detected. Notably, three pyrethroid insecticides—bifenthrin, cypermethrin, and permethrin—were consistently detected at or near each chemical’s lethal dose (LD50). Bifenthrin and cypermethrin were found in every sample, while permethrin was present in all but two samples. The average concentrations of these insecticides were 451.9 ng/g dry weight (dw) for bifenthrin, 646.9 ng/g dw for cypermethrin, and 337.1 ng/g dw for permethrin. These findings demonstrate pesticide contamination in monarch butterflies, including within urban areas, and highlight the risks pesticides, especially insecticides, pose to monarch populations. Additional measures may be required to safeguard this species from pesticide exposure, particularly near aggregation locations, such as overwintering sites in coastal California.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf163","usgsCitation":"Cibotti, S., Hladik, M.L., May, E., Pelton, E., Bargar, T., Johnston, N., and Code, A., 2025, Pyrethroid insecticides implicated in mass mortality of monarch butterflies at an overwintering site in California: Environmental Toxicology and Chemistry, v. 44, no. 10, p. 2716-2724, https://doi.org/10.1093/etojnl/vgaf163.","productDescription":"9 p.","startPage":"2716","endPage":"2724","ipdsId":"IP-171429","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":495174,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgaf163","text":"Publisher Index Page"},{"id":491811,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Pacific Grove","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.93166350087532,\n 36.627315376432804\n ],\n [\n -121.93166350087532,\n 36.625890169912864\n ],\n [\n -121.93022565277657,\n 36.625890169912864\n ],\n [\n -121.93022565277657,\n 36.627315376432804\n ],\n [\n -121.93166350087532,\n 36.627315376432804\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Cibotti, Staci","contributorId":357703,"corporation":false,"usgs":false,"family":"Cibotti","given":"Staci","affiliations":[{"id":34267,"text":"The Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":942258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":942259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Emily","contributorId":357704,"corporation":false,"usgs":false,"family":"May","given":"Emily","affiliations":[{"id":34267,"text":"The Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":942260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pelton, Emma","contributorId":357706,"corporation":false,"usgs":false,"family":"Pelton","given":"Emma","affiliations":[{"id":34267,"text":"The Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":942261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bargar, Timothy 0000-0001-8588-3436","orcid":"https://orcid.org/0000-0001-8588-3436","contributorId":211833,"corporation":false,"usgs":true,"family":"Bargar","given":"Timothy","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942262,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnston, Natalie","contributorId":357709,"corporation":false,"usgs":false,"family":"Johnston","given":"Natalie","affiliations":[{"id":85538,"text":"Pacific Grove Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":942263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Code, Aimee","contributorId":214378,"corporation":false,"usgs":false,"family":"Code","given":"Aimee","email":"","affiliations":[{"id":39027,"text":"Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":942264,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268695,"text":"70268695 - 2025 - Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization","interactions":[],"lastModifiedDate":"2025-07-08T15:40:36.038242","indexId":"70268695","displayToPublicDate":"2025-06-27T10:36:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization","docAbstract":"Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs - over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well-distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model-data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR038720","usgsCitation":"Helton, A., Dennedy-Frank, J., Emanuel, R., Neubauer, S.C., Adams, K., Ardon, M., Band, L., Befus, K.A., Borstlap, H., Duberstein, J., Gold, A., Kominoski John, Manda, A., Michael, H.A., Moysey, S., Myers-Pigg, A., Neville, J.A., Noe, G.E., Panthi, J., Pezeshki, E., Sirianni, M., and Ward.Nicolas, 2025, Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization: Water Resources Research, v. 61, no. 7, e2024WR038720, 8 p., https://doi.org/10.1029/2024WR038720.","productDescription":"e2024WR038720, 8 p.","ipdsId":"IP-167925","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":492056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr038720","text":"Publisher Index Page"},{"id":491805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":941662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennedy-Frank, James","contributorId":357528,"corporation":false,"usgs":false,"family":"Dennedy-Frank","given":"James","affiliations":[{"id":85449,"text":"Northeastern Universtiy","active":true,"usgs":false}],"preferred":false,"id":941663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Emanuel, Ryan","contributorId":333342,"corporation":false,"usgs":false,"family":"Emanuel","given":"Ryan","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":941664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neubauer, Scott C","contributorId":169723,"corporation":false,"usgs":false,"family":"Neubauer","given":"Scott","email":"","middleInitial":"C","affiliations":[{"id":25575,"text":"Dept. of Biology, Virginia Commonwealth University, Richmond, VA","active":true,"usgs":false}],"preferred":false,"id":941665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Kyra","contributorId":357529,"corporation":false,"usgs":false,"family":"Adams","given":"Kyra","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":941666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ardon, Marcelo","contributorId":298014,"corporation":false,"usgs":false,"family":"Ardon","given":"Marcelo","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":941667,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Band, Lawrence","contributorId":174085,"corporation":false,"usgs":false,"family":"Band","given":"Lawrence","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":941668,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Befus, Kevin A.","contributorId":299488,"corporation":false,"usgs":false,"family":"Befus","given":"Kevin","email":"","middleInitial":"A.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":941669,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Borstlap, Hanne","contributorId":357530,"corporation":false,"usgs":false,"family":"Borstlap","given":"Hanne","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":941670,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duberstein, Jamie 0000-0002-2787-5515","orcid":"https://orcid.org/0000-0002-2787-5515","contributorId":332972,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":941671,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gold, Adam","contributorId":357531,"corporation":false,"usgs":false,"family":"Gold","given":"Adam","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":941672,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kominoski John","contributorId":357532,"corporation":false,"usgs":false,"family":"Kominoski John","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":941673,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Manda, Alex","contributorId":333344,"corporation":false,"usgs":false,"family":"Manda","given":"Alex","email":"","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941674,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":941675,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moysey, Stephen","contributorId":357533,"corporation":false,"usgs":false,"family":"Moysey","given":"Stephen","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941676,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Myers-Pigg, Allison","contributorId":224762,"corporation":false,"usgs":false,"family":"Myers-Pigg","given":"Allison","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":941677,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Neville, Justine Annaliese 0000-0003-3160-5363","orcid":"https://orcid.org/0000-0003-3160-5363","contributorId":329739,"corporation":false,"usgs":true,"family":"Neville","given":"Justine","email":"","middleInitial":"Annaliese","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":941678,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":941679,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Panthi, Jeeban","contributorId":357534,"corporation":false,"usgs":false,"family":"Panthi","given":"Jeeban","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":941680,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Pezeshki, Elnaz","contributorId":357535,"corporation":false,"usgs":false,"family":"Pezeshki","given":"Elnaz","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941681,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sirianni, Matthew","contributorId":357536,"corporation":false,"usgs":false,"family":"Sirianni","given":"Matthew","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":941682,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ward.Nicolas","contributorId":357537,"corporation":false,"usgs":false,"family":"Ward.Nicolas","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":941683,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70268445,"text":"sir20245134 - 2025 - Assessment and validation of depressions in digital elevation models from multiple elevation data sources and delineation of depressions, sinking streams, and their watersheds in Tennessee and parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","interactions":[],"lastModifiedDate":"2025-08-14T19:40:56.797048","indexId":"sir20245134","displayToPublicDate":"2025-06-26T13:45:32","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":"2024-5134","displayTitle":"Assessment and Validation of Depressions in Digital Elevation Models From Multiple Elevation Data Sources and Delineation of Depressions, Sinking Streams, and Their Watersheds in Tennessee and Parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","title":"Assessment and validation of depressions in digital elevation models from multiple elevation data sources and delineation of depressions, sinking streams, and their watersheds in Tennessee and parts of Kentucky, Virginia, North Carolina, Georgia, Alabama, and Mississippi","docAbstract":"Closed depressions and sinking streams in karst landscapes pose difficulties for water-resources management, in the construction of roads and other public works, and in hydrologic and hydrogeomorphic analyses. Digital elevation models (DEMs) can be used to identify the location and determine the size and shape of closed depressions, but separating artificial depressions due to error from real depressions in DEMs can be difficult. Artificial depressions in the DEMs can result from errors that were inherited from limitations in the source data, the interpolation of the elevation data into a grid of values, or horizontal and vertical accuracy of the elevation data. Because the source dataset used to derive DEMs is only a model of the true landscape, field verification is necessary to separate artificial depressions from real ones in DEMs. DEM analysis alone can only be used to determine whether a depression is likely or unlikely to exist in the landscape.
The U.S. Geological Survey has applied methods to delineate depressions, sinking streams, and their watersheds by using DEMs derived from two sources of elevation data within karst areas of Tennessee and parts of surrounding States. Preliminary depressions, which include all depressions before separating the likely depressions from the unlikely depressions, were delineated from the DEMs with 30- by 30-foot cells derived from each elevation data source. The characteristics of these preliminary depressions were compared to occurrence probabilities for depressions derived from numerical error propagation tests in 10 test areas across the study area and to topographic-contour source data within a 17,739-square-mile test area in middle Tennessee and northern Alabama. The comparison was conducted to determine depression characteristics that, when combined with depression-proximity filters, could be used to separate unlikely from likely depressions. Preliminary depressions were examined in the field at 91 sites in Tennessee, and field observations were compared to digital determinations of unlikely and likely depressions.
The density and size of depressions derived from each elevation dataset were compared within eight karst regions in the study area. Depressions and their watersheds were compiled from each elevation dataset. Sinking streams derived from the National Hydrography Dataset and their watersheds also were compiled for the study area.
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":"Introduction: Rangeland ponds are vital to the livelihoods of pastoral and agropastoral communities in Africa, providing an important source of water for livestock. However, sparse instrumentation across much of Africa makes it extremely challenging to monitor surface water availability in these areas. Model estimates of surface water, for example, as used by the Famine Early Warning Systems Network (FEWS NET) Water Point Viewer, are one of the few operational tools available to monitor surface water stress across pastoral areas of the Sahel and East Africa.
Methods: Water availability data from these models are difficult to validate. New methods using satellite data to classify surface water provide an opportunity to assess the performance of these tools. This study compares water availability estimates derived from Landsat and Sentinel 1 satellite imagery to in situ observations and model simulations of water availability in 22 ephemeral ponds located in the Ferlo region of Senegal.
Results and discussion: The Active-Passive Water Classification (APWC) algorithm detected surface water at each location. Over 2022 and 2023, water was detected in pond locations annually at a frequency of 68.2% for all ponds and at a frequency of 43.8% for ponds with a surface area <10,000 square meters (m2). The APWC results outperform global and continental surface water datasets in the Ferlo region. Seasonal water availability was captured in 12 ponds over the 2022 and 2023 seasons. The 12 locations can function as sentinel ponds to monitor local water availability. Study results demonstrate the viability of satellite methods to assess water availability in the region, as well as the challenges to using satellite-based methods to estimate water availability in small ponds.
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Public participatory geographic information systems (PPGIS) are tools that have been used to help quantify and map the public’s diverse values for a landscape. This work describes the first known Office of Management and Budget–approved use of PPGIS by a Department of the Interior bureau. The U.S. Geological Survey developed an internet-based application to aid in gathering PPGIS data, called Values Mapping for Planning in Regional Ecosystems (VaMPIRE). Further, this work describes the first pilot of the VaMPIRE application in coordination with the Bureau of Land Management to collect spatial data and other survey data regarding the public’s uses of and values for locations within Mojave Trails National Monument. We emailed the link to the VaMPIRE application to an interested party email list in 2024 with 207 valid emails and received 74 responses; we also received 47 responses from members of an off-roading social media group. Of the list of 16 value options, recreation was the most popular value for the monument, followed by wilderness and inspirational. Over 1,000 points were placed throughout the monument, indicating locations people use or value, with the locations spread throughout the entire monument. Additionally, most survey respondents stated their ability to receive benefits in locations they mapped would not change in response to a hypothetical scenario related to recreational facility development. This report describes exploratory results from the first use of the VaMPIRE tool in Mojave Trails National Monument and includes reflections on how the process went and considerations for future use of VaMPIRE.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255037","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Land Management Research Program","usgsCitation":"Wilkins, E.J., Lindley, S.M., Rogers, K., Schuster, R., Hannon, M.T., Rowland, P.T., and Runnels, M.J., 2025, Using public participatory geographic information systems (PPGIS) to explore uses and values for Mojave Trails National Monument, California: U.S. Geological Survey Scientific Investigations Report 2025–5037, 27 p., https://doi.org/10.3133/sir20255037.","productDescription":"Report: vi, 27 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-168071","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":491391,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5037/sir20255037.xml"},{"id":491390,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5037/images"},{"id":491394,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255037/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5037"},{"id":491306,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1423FLS","text":"USGS data release","linkHelpText":"Values Mapping for Planning in Regional Ecosystems: Mojave Trails National Monument, California, 2024"},{"id":491303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5037/coverthb.jpg"},{"id":491304,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5037/sir20255037.pdf","text":"Report","size":"5.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5037"}],"country":"United States","state":"California","otherGeospatial":"Mojave Trails National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.37203217608662,\n 35.235920982774275\n ],\n [\n -116.63385757611397,\n 35.235920982774275\n ],\n [\n -116.63385757611397,\n 34.05652997012804\n ],\n [\n -114.37203217608662,\n 34.05652997012804\n ],\n [\n -114.37203217608662,\n 35.235920982774275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118