Lake Superior is typically assumed to have excellent water quality, but its tributaries have been understudied for contaminants relative to other Great Lakes. This study monitored polycyclic aromatic hydrocarbons (PAHs), alkylphenols (AP) and alkylphenol ethoxylates (APEs), bisphenols, and neonicotinoid pesticides in 18 sites on 17 United States tributaries to Lake Superior in 2022. Contaminants were analyzed from 54 surface water and 17 stream bed sediment samples. PAHs were the most prevalent contaminant class. Among 17 PAHs in 17 samples (289 instances), 71 % were positive detections. Surface water samples were not analyzed for PAHs. Next, among 4 APs and APEs analyzed, 35 % of sediment sample instances and 21 % of instances in 54 water samples were positive detections. Bisphenol analogues were detected in 2 % of sediment sample instances and 4 % of water sample instances. Bisphenol A (BPA) was not quantified due to field blank contamination, but bisphenol AF (BPAF), bisphenol E (BPE), bisphenol F (BPF), and bisphenol S (BPS) were detected in environmental samples. Neonicotinoids were detected in 0.5 % of sediment sample instances and 0.4% of water samples instances. Low detection frequencies for contaminants precluded analyses with watershed land use characteristics, but four sites (Tischer Creek, Miller Creek, Carp River and Iron River) emerged as locations with relatively elevated contaminant concentrations. Comparison of concentrations with ToxCast and other water quality guidelines suggested potential for biological effects from some samples. This study provides a baseline of low contaminant prevalence in Lake Superior tributaries while identifying a few locations that may warrant further monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102608","usgsCitation":"LaFond-Hudson, S., Pronschinske, M.A., Elliott, S.M., and Corsi, S., 2025, Prevalence and potential for biological effects of several chemicals of interest in Lake Superior tributaries: Journal of Great Lakes Research, v. 51, no. 4, 102608, 12 p., https://doi.org/10.1016/j.jglr.2025.102608.","productDescription":"102608, 12 p.","ipdsId":"IP-177038","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":502985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2025.102608","text":"Publisher Index Page"},{"id":502944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","otherGeospatial":"Lake Superior tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.75227036599577,\n 48.92833262463154\n ],\n [\n -85.81152503458061,\n 48.92833262463154\n ],\n [\n -85.81152503458061,\n 45.34493920539285\n ],\n [\n -95.75227036599577,\n 45.34493920539285\n ],\n [\n -95.75227036599577,\n 48.92833262463154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"LaFond-Hudson, Sophia 0000-0002-0860-2546","orcid":"https://orcid.org/0000-0002-0860-2546","contributorId":356735,"corporation":false,"usgs":true,"family":"LaFond-Hudson","given":"Sophia","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pronschinske, Matthew A. 0000-0001-9787-4545 mpronschinske@usgs.gov","orcid":"https://orcid.org/0000-0001-9787-4545","contributorId":295961,"corporation":false,"usgs":true,"family":"Pronschinske","given":"Matthew","email":"mpronschinske@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959608,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269400,"text":"ofr20251039 - 2025 - Evaluating deterrent locations and sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to minimize invasive carp occupancy and abundance","interactions":[],"lastModifiedDate":"2026-02-03T14:30:33.772241","indexId":"ofr20251039","displayToPublicDate":"2025-07-22T09:48:30","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1039","displayTitle":"Evaluating Deterrent Locations and Sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to Minimize Invasive Carp Occupancy and Abundance","title":"Evaluating deterrent locations and sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to minimize invasive carp occupancy and abundance","docAbstract":"Invasive carps, specifically silver carp (Hypophthalmichthys molitrix), bighead carp (H. nobilis), grass carp (Ctenopharyngodon idella), and black carp (Mylopharyngodon piceus), have proliferated in the Mississippi River Basin owing to escapes from aquaculture facilities and intentional releases. In the Water Resources and Development Act (WRDA) of 2020 Sec. 509, Congress directed the U.S. Army Corps of Engineers to work with the Tennessee Valley Authority and other relevant agencies with deterrent projects to implement as many as 10 deterrent projects intended to manage and prevent the spread of invasive carp in the Tennessee and Cumberland River subbasins. The WRDA was amended in 2022 to include that at least one location must be situated on the Tennessee–Tombigbee Waterway. This report documents a structured decision-making process that engaged State and Federal agencies to evaluate alternative deterrent site sequences at specified lock and dam complexes on the Tennessee River, Cumberland River, and the Tennessee–Tombigbee Waterway. State and Federal agencies participated in a series of virtual and face-to-face meetings to structure the problem, expand the models used in previous decision analyses for the Tennessee River, and define management objectives. Potential deterrent sites were restricted to the downstream locations on the Tennessee River (n=3), Cumberland River (n=2), and the Tennessee–Tombigbee Waterway (n=10). Only considering 15 sites allowed all feasible deterrent site combinations and sequences to be evaluated. Invasive carp relative abundance was projected for the Tennessee River, Cumberland River, and Tennessee–Tombigbee Waterway management units for 20 years using a simulation model. The deterrent site sequences were ranked based on the system-level invasive carp relative abundance and distribution in year 20. The unique downstream expansion of invasive carp through the Tennessee–Tombigbee Waterway was important to the interest group, but downstream movement rates were unknown; therefore, several downstream movement rates were evaluated, and the outcomes were used to rank deterrent site sequences. Additionally, the analysis incorporated two scenarios involving the retention and removal of an experimental deterrent at Barkley Lock on the Cumberland River. The results of the deterrent site sequences varied among downstream movement rates, with Tennessee–Tombigbee Waterway deterrent locations installed earlier in highly ranked sequences with increasing downstream movement rates. This analysis was time-limited owing to agency needs and represents Phase 1 of this project. Phase 2 expands Phase 1 to address additional uncertainties and more holistic management objectives and strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251039","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Colvin, M.E., Aldridge, C.A., Jackson, N., and Post van der Burg, M., 2025, Evaluating deterrent locations and sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to minimize invasive carp occupancy and abundance: U.S. Geological Survey Open-File Report 2025–1039, 27 p., https://doi.org/10.3133/ofr20251039.","productDescription":"vii, 27 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171324","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":492704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251039/full"},{"id":492703,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1039/images/"},{"id":492702,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1039/ofr20251039.XML"},{"id":492701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1039/ofr20251039.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2-25–1039"},{"id":492700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1039/coverthb.jpg"}],"country":"United States","state":"Alabama, Georgia, Kentucky, Mississippi, Tennessee, Virginia","otherGeospatial":"Cumberland River, Tennessee River, Tennessee-Tombigbee Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.25835232816404,\n 30.40221322680152\n ],\n [\n -87.74112738454285,\n 30.53409733966683\n ],\n [\n -86.28197353514268,\n 33.17664867905761\n ],\n [\n -84.58539276715948,\n 35.11174136013369\n ],\n [\n -84.00529754650283,\n 34.7785832881593\n ],\n [\n -83.35182994181118,\n 34.28883621944685\n ],\n [\n -83.19236665540257,\n 35.041055997522406\n ],\n [\n -80.2096850872316,\n 36.78640735388454\n ],\n [\n -80.86738805566942,\n 37.257953522126016\n ],\n [\n -82.13281736640333,\n 37.06950836241309\n ],\n [\n -83.02442148961904,\n 37.262219027957244\n ],\n [\n -83.54138832596139,\n 37.46692711167633\n ],\n [\n -84.33015340933808,\n 37.60749767579556\n ],\n [\n -85.06533697843895,\n 37.036511430167636\n ],\n [\n -85.5677502361562,\n 36.45362253430034\n ],\n [\n -85.87920757818353,\n 36.383379347391596\n ],\n [\n -86.6325463621631,\n 37.379506944709526\n ],\n [\n -87.72434869310914,\n 37.50907115621132\n ],\n [\n -88.41107734207077,\n 37.2244083095801\n ],\n [\n -88.42057356609506,\n 37.02794489656113\n ],\n [\n -89.00288659023786,\n 37.183779269350126\n ],\n [\n -88.75606773049479,\n 35.10788131292719\n ],\n [\n -89.05545157713219,\n 34.33758222980704\n ],\n [\n -88.86237269918561,\n 33.56728314668689\n ],\n [\n -88.61821473605681,\n 32.488997215417314\n ],\n [\n -88.31062051861113,\n 31.90405945387107\n ],\n [\n -88.25835232816404,\n 30.40221322680152\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Invasive silver carp are spreading upstream in the Tennessee and Cumberland Rivers. This report details a collaborative effort among State and Federal agencies to evaluate potential sites for invasive carp deterrent projects along the Tennessee River, Cumberland River, and the Tennessee–Tombigbee Waterway. The findings highlight that project implementation timing could significantly impact their success, especially with increasing downstream movement rates of invasive carp.
","publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":943664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Caleb A.","contributorId":358407,"corporation":false,"usgs":false,"family":"Aldridge","given":"Caleb A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":943665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Neal","contributorId":203382,"corporation":false,"usgs":false,"family":"Jackson","given":"Neal","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":943666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219400,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":943667,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269509,"text":"70269509 - 2025 - Genetic structure of an expanding population of Humpback Chub in Grand Canyon","interactions":[],"lastModifiedDate":"2025-11-20T16:40:29.42034","indexId":"70269509","displayToPublicDate":"2025-07-22T09:45:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure of an expanding population of Humpback Chub in Grand Canyon","docAbstract":"Humpback Chub (HBC) Gila cypha in Grand Canyon declined in abundance and distribution over the latter part of the 20th century but have substantially increased in abundance and distribution over the past two decades. Although previous genetic work suggested that HBC in Grand Canyon belong to one genetic group, here we evaluate the genetic structure of HBC in Grand Canyon to determine whether relic populations in western Grand Canyon may have contributed unique variation to the recent population expansion or whether differences in behavior linked to migration in eastern Grand Canyon may promote assortative mating and heretofore unrecognized population structure.
Using fin clips collected from 167 individual HBC representing four sampling sites within Grand Canyon, we extracted DNA and developed data sets consisting of approximately 20,000 anonymous genomic loci. We quantified patterns of genetic diversity, and we accounted for outlier single-nucleotide polymorphisms to ensure that our interpretations of genetic patterns were not misled by adaptive processes and did not mask adaptively important genetic variation.
Despite behavioral variation and the possibility that individuals with unique genetic variation survived in isolated warmwater sites within western Grand Canyon, HBC were not differentiated by sampling site or by differences in migratory behavior. Heterozygosity and nucleotide diversity were consistently high among sampling sites, and inbreeding coefficients were close to zero.
The HBC in Grand Canyon constitute a single genetic population. Our results do not preclude a genetic basis to migratory behavior, but our data suggest that this trait does not lead to assortative mating. Furthermore, while HBC may have survived in discontiguous warmwater refugia in western Grand Canyon during decades when the main stem was too cold for spawning, our data did not reveal any noticeable spatial variability in HBC genetics in the main stem after the recent HBC population expansion.
The three North American Rosy-Finch species (Brown-capped [Leucosticte australis], Black [L. atrata], and Gray-crowned [L. tephrocotis]) are among the most climate-threatened species in the United States. New Mexico is an important location for investigating the effects of climate change because it is the southernmost location in which Brown-capped Rosy-Finches breed and the southernmost location where all three Rosy-Finch species co-occur during winter. In the context of climate change, this range boundary is important to study because it is the first part of the range anticipated to cross a threshold of unsuitability for these species with increasing temperatures. Rosy-Finches are difficult to study during the breeding season due to the high elevation and remoteness of their breeding grounds; therefore, winter studies may lend insight into population trends and provide direction for conservation actions based on knowledge of the breeding origins of wintering birds. The goals of our study were to investigate long-term survival and migration trends from wintering Brown-capped Rosy-Finches in New Mexico and evaluate the efficacy of radio frequency identification (RFID)-equipped artificial feeders to monitor population trends. As of May 2025, we have conducted a robust design survival analysis on 22 years of mark-recapture data from a particular wintering site in New Mexico, assessed patterns in the breeding origins of individuals captured at this site using stable isotope analysis, and examined patterns in data collected via RFID. Our main findings from this study are that annual survival probability of Rosy-Finches wintering in New Mexico is low compared to that of other migratory passerines, that Brown-capped Rosy-Finches wintering in New Mexico likely originate from a variety of locations across their breeding range, and that RFID monitoring is useful in improving survival estimates in Rosy-Finches, particularly in short-term studies.
","language":"English","publisher":"New Mexico Department of Game and Fish Share with Wildlife Program","usgsCitation":"Watson, W.A., Borgman, C.C., Cox, S., and Lawson, A.J., 2025, Inferring Brown-Capped Rosy-Finch demography and breeding distribution trends from long-term wintering data in New Mexico: Final Report, 31 p.","productDescription":"31 p.","ipdsId":"IP-179262","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":495001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":494873,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.dgf.nm.gov/download/new-mexico-state-university-las-cruces-inferring-brown-capped-rosy-finch-demography-and-breeding-distribution-trends-from-long-term-wintering-data-in-new-mexico-final-report/"}],"country":"United States","state":"New 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Inc.","active":true,"usgs":false}],"preferred":false,"id":947206,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":947207,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269469,"text":"70269469 - 2025 - Beach nourishment response and recent morphological evolution of Minnesota Point, Lake Superior","interactions":[],"lastModifiedDate":"2025-07-24T14:43:36.320989","indexId":"70269469","displayToPublicDate":"2025-07-22T09:36:52","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":"Beach nourishment response and recent morphological evolution of Minnesota Point, Lake Superior","docAbstract":"Beach nourishments are a popular nature-based alternative to armoring for shoreline erosion mitigation, but nourishments have been criticized due to their environmental impacts and uncertain sustainability. Monitoring is often nonexistent or insufficient to constrain nourishment longevity and inform the renourishment interval required to maintain shoreline protection. This study uses a combination of topobathymetric surveys, high-resolution satellite-derived shorelines, and coastal engineering analyses to investigate the recent evolution of Minnesota Point and the fate of three beach nourishments constructed adjacent to littoral barriers. We use semi-empirical formulations for sediment compatibility, wave runup, and longshore sediment transport to inform the observed nourishment behavior. Minnesota Point experienced widespread foredune retreat averaging 7±2.8 m from 2009–2019 and 130,000 (70,000–140,000) m3 of sediment was eroded during this interval. The 2019 nourishment at the Superior Entry was rapidly eroded by strong storms, losing >80% of the added beach width by the following spring. The 2020 and 2021 nourishments at the Duluth Entry retained >80% of the nourishment material at the time of the last topobathymetric survey in the fall of 2022, and satellite-derived shorelines indicate that the beach remained 10 m wider than pre-nourishment conditions at the end of 2023. Modeled longshore transport rates over the period 2009–2022 averaged 11,400 m3 yr−1 northwestward at the Superior Entry, nearly 3x greater than the 4000 m3 yr−1 southeastward transport modeled at the Duluth Entry. These observations show that differences in shoreline orientation, littoral sediment supply, and grain size compatibility can lead to contrasting beach nourishment longevities, and this study provides additional measurements of Minnesota Point’s long-term morphological change which can help inform coastal resiliency efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102459","usgsCitation":"Roland, C., Groten, J.T., Lund, J., and Hanson, J.L., 2025, Beach nourishment response and recent morphological evolution of Minnesota Point, Lake Superior: Journal of Great Lakes Research, v. 51, no. 4, 102459, 21 p., https://doi.org/10.1016/j.jglr.2024.102459.","productDescription":"102459, 21 p.","ipdsId":"IP-167678","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":492884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2024.102459","text":"Publisher Index Page"},{"id":492830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","city":"Duluth, Superior","otherGeospatial":"Minnesota Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.11687484166973,\n 46.79169814336808\n ],\n [\n -92.11687484166973,\n 46.69589459379978\n ],\n [\n -92.00223407990056,\n 46.69589459379978\n ],\n [\n -92.00223407990056,\n 46.79169814336808\n ],\n [\n -92.11687484166973,\n 46.79169814336808\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Collin 0000-0003-1004-0746","orcid":"https://orcid.org/0000-0003-1004-0746","contributorId":343660,"corporation":false,"usgs":true,"family":"Roland","given":"Collin","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groten, Joel T. 0000-0002-0441-8442 jgroten@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-8442","contributorId":173464,"corporation":false,"usgs":true,"family":"Groten","given":"Joel","email":"jgroten@usgs.gov","middleInitial":"T.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lund, J. William 0000-0002-8830-4468","orcid":"https://orcid.org/0000-0002-8830-4468","contributorId":289132,"corporation":false,"usgs":true,"family":"Lund","given":"J. William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Jenny L. 0000-0001-8353-6908 jhanson@usgs.gov","orcid":"https://orcid.org/0000-0001-8353-6908","contributorId":461,"corporation":false,"usgs":true,"family":"Hanson","given":"Jenny","email":"jhanson@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943842,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269959,"text":"70269959 - 2025 - Evaluating large wood additions as a scalable method of urban stream restoration","interactions":[],"lastModifiedDate":"2025-11-20T16:47:10.943884","indexId":"70269959","displayToPublicDate":"2025-07-22T09:35:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating large wood additions as a scalable method of urban stream restoration","docAbstract":"Urbanization is associated with increased erosion and habitat homogenization in stream ecosystems. This habitat degradation often has biological consequences, such as decreased species richness. Conventional stream restoration practices are costly, and projects are limited to small areas with easy access. A scalable, low-cost method of stream restoration is needed to address the widespread degradation occurring in urban streams. Large wood (LW) is an important element in stream ecosystems that is typically abundant in forested watersheds but scarce in urban streams. LW can reduce water velocities, generate pool habitat, decrease erosion, and provide cover for aquatic organisms. In this study, we performed experimental LW installations to assess the capacity of LW restoration to improve habitat and reduce sediment transport in an urban headwater stream in Cincinnati, Ohio. We tracked the geomorphic effects of these installations using a before-after-control-impact study design in four 60-m reaches, two treatment and two control, over a 1.5-year period to investigate the following questions: (1) Will unanchored LW additions remain stable in a flashy urban stream? (2) Will LW additions increase the availability of pool habitat? (3) Will wood additions increase bed stability and modify sediment size distributions? We found that LW installations rapidly increased pool habitat availability (size) around stable jams, but a majority of the LW jams were frequently mobilized and reconfigured by high-flow events. LW additions had no significant impact on the probability of stream bed mobilization, likely due to the instability of LW; however, the distance particles traveled once mobilized significantly decreased. While LW additions can increase the availability of pool habitat in urban headwater streams, further investigation is needed to understand the stability of such structures and the environmental context where these additions will be most beneficial.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.70007","usgsCitation":"Grap, P., Matter, S., Lehmann, A., Ward, D., and Booth, M., 2025, Evaluating large wood additions as a scalable method of urban stream restoration: River Research and Applications, v. 41, no. 9, p. 2032-2051, https://doi.org/10.1002/rra.70007.","productDescription":"20 p.","startPage":"2032","endPage":"2051","ipdsId":"IP-175806","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","county":"Hamilton County","otherGeospatial":"Cooper Creek, Mill Creek","volume":"41","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Grap, Peter","contributorId":357014,"corporation":false,"usgs":false,"family":"Grap","given":"Peter","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":945054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matter, Stephen F.","contributorId":359214,"corporation":false,"usgs":false,"family":"Matter","given":"Stephen F.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":945055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehmann, Adam","contributorId":357020,"corporation":false,"usgs":false,"family":"Lehmann","given":"Adam","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":945056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, Dylan","contributorId":265490,"corporation":false,"usgs":false,"family":"Ward","given":"Dylan","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":945057,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Booth, Michael Thomas 0000-0002-9842-085X","orcid":"https://orcid.org/0000-0002-9842-085X","contributorId":357011,"corporation":false,"usgs":true,"family":"Booth","given":"Michael Thomas","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":945058,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269761,"text":"70269761 - 2025 - Blowing in the wind: Anemochory in blackbrush habitat of South Texas","interactions":[],"lastModifiedDate":"2025-11-20T16:43:14.129544","indexId":"70269761","displayToPublicDate":"2025-07-22T09:30:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Blowing in the wind: Anemochory in blackbrush habitat of South Texas","docAbstract":"Wind dispersal has the potential to carry seeds long-distances and could inform the management and restoration of natural vegetation along the U.S.-Mexico Border. Plant species with the potential to disperse seeds in arid landscapes fragmented by border barrier infrastructure include foundational native, invasive, and federally endangered plant species. Wind dispersal traps constructed of cloth were set facing into the prevailing wind direction (SE) to characterize the role of wind in transporting soil particles, pebbles, plant debris, and seeds in blackbrush habitat during maximum events of wind speed (km per hour), and precipitation (cm). Shrubs, native grasses, the invasive Pennisetum ciliare (buffelgrass), soil particles, and pebbles dispersed in the wind, especially during maximum wind and/or precipitation events. Natural blackbrush areas supported the wind dispersal of twelve native species including grasses and woody shrubs. Sites disturbed by border infrastructure (barrier, roads, waterways) had higher seed numbers of invasive species such as P. ciliare captured in the wind traps. While modifications in passages through waterways and other structures have been proposed to improve the movement of organisms influenced by the barrier, the restoration of native plant species in damaged areas might further aid in the maintenance of blackbrush ecosystems by reducing invasive plant species dispersal into natural habitats.
","language":"English","publisher":"Springer","doi":"10.1007/s11258-025-01527-9","usgsCitation":"Middleton, B., and Lain, E., 2025, Blowing in the wind: Anemochory in blackbrush habitat of South Texas: Plant Ecology, v. 226, p. 1057-1064, https://doi.org/10.1007/s11258-025-01527-9.","productDescription":"8 p.","startPage":"1057","endPage":"1064","ipdsId":"IP-167847","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":493240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Arroyo Morteros, Arroyo Ramirez, Cuellar tract, Lower Rio Grande Valley National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.86537923681847,\n 27.90301608157847\n ],\n [\n -99.19865426109092,\n 26.168012208444026\n ],\n [\n -97.2958075042999,\n 25.753100816726878\n ],\n [\n -97.08690291521907,\n 25.9785258529746\n ],\n [\n -98.88941956966367,\n 26.540145638316744\n ],\n [\n -99.47996857108726,\n 27.671219788235106\n ],\n [\n -99.86537923681847,\n 27.90301608157847\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"226","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206684,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":944575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lain, Emily J.","contributorId":358948,"corporation":false,"usgs":false,"family":"Lain","given":"Emily J.","affiliations":[{"id":83764,"text":"Cherokee Nation System Solutions, contracted to the U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":944576,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70269581,"text":"70269581 - 2025 - Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area","interactions":[],"lastModifiedDate":"2025-09-09T14:45:30.640888","indexId":"70269581","displayToPublicDate":"2025-07-22T08:59:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area","docAbstract":"Strategies animals use to navigate human-dominated landscapes frequently mimic anti-predator responses employed by prey species. Understanding how large carnivores respond to outdoor recreation is important for conservation, particularly in protected areas with preservation mandates. Visitation to Yellowstone National Park doubled from 1980 to 2015, increasing the need to examine potential changes in behavior of grizzly bears (Ursus arctos) in relation to human recreation sites (trails, backcountry campsites). We developed integrated step-selection functions to explore how recreation sites influenced the movement rate and selection by male and female grizzly bears. Further, we tested whether time of day (diurnal, crepuscular, nocturnal) and restrictions to human access (i.e., restricted, unrestricted) modified bear responses and then compared behaviors based on proximity to recreation sites. Male grizzly bears used trails to travel during crepuscular and nocturnal hours and exhibited more pronounced behavior in restricted areas compared with unrestricted areas, suggesting recreation in unrestricted areas influenced the behavior of male bears. In contrast, female bears varied their movement rate and selection of trails in restricted areas much more than in unrestricted areas, suggesting females may make security tradeoffs between male bears and people. Both sexes used trails, likely as energetically efficient travel corridors; however, our analyses did not indicate that bears spent time near backcountry campsites. The sex-based differences in selection and movement patterns associated with trails and campsites suggest a single management approach for recreation may not equally benefit all bears. Recreation impacts on wildlife are complex to characterize and predict, but simultaneously modeling movement and selection provides a more comprehensive assessment of strategies animals use to navigate perceived risk.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.70068","usgsCitation":"Loggers, E., Litt, A.R., Haroldson, M., Gunther, K.A., and van Manen, F.T., 2025, Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area: Journal of Wildlife Management, v. 89, no. 7, e70068, 24 p., https://doi.org/10.1002/jwmg.70068.","productDescription":"e70068, 24 p.","ipdsId":"IP-174424","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":493317,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70068","text":"Publisher Index Page"},{"id":492993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.05465697234523,\n 45.04848474160275\n ],\n [\n -111.05465697234523,\n 44.132997929608706\n ],\n [\n -110.00606720612153,\n 44.132997929608706\n ],\n [\n -110.00606720612153,\n 45.04848474160275\n ],\n [\n -111.05465697234523,\n 45.04848474160275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Loggers, Elise","contributorId":331713,"corporation":false,"usgs":false,"family":"Loggers","given":"Elise","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":944101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litt, Andrea R.","contributorId":208358,"corporation":false,"usgs":false,"family":"Litt","given":"Andrea","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":944102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haroldson, Mark 0000-0002-7457-7676","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":316737,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":944103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":944104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":944105,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270836,"text":"70270836 - 2025 - Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development","interactions":[],"lastModifiedDate":"2025-11-20T16:58:09.990917","indexId":"70270836","displayToPublicDate":"2025-07-22T07:58:36","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":"Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development","docAbstract":"Proper development and inflation of the swim bladder is essential for swimming and foraging behavior in fish. To characterize the effects of the Brazilian oil spill that occurred between 2019 and 2020 to early life stage fish, the expression of genes involved in swim bladder development were targeted, with biochemical assays, morphology, and behavior assessed. The swim bladder was focused on due to recent findings of being a target of polycyclic aromatic hydrocarbons (PAHs) present in oil. Zebrafish (Danio rerio) were exposed to oil water accommodated fractions at concentrations measured following the spill, 1.12–71.8 total PAHs (μg-ΣPAHt L−1). Larvae exposed to 4.49 and 17.9 μg-ΣPAHt L−1 had a downregulation in swim bladder development genes hb9, sox2, has2, and elovl1a at 48 hr postfertilization (hpf). Downregulation in these genes was associated with a high frequency of uninflated swim bladders at 96 and 168 hpf, with uninflated swim bladders detected in 100% of 96 to 168 hpf larvae exposed to 35.9 and 71.8 μg-ΣPAHt L−1. Superoxide dismutase and catalase levels were inhibited in larvae exposed to 1.12 and 2.24 μg-ΣPAHt L−1, respectively. There was an increase in glutathione-S-transferase and glutathione levels in exposed larvae. Average swimming speed and distance were reduced in larvae exposed to 1.12 μg-ΣPAHt L−1. This suggests that complex mixtures of PAHs from crude oil can inhibit the transcription of genes involved in swim bladder tissue development and proper swim-up behavior, which may have implications for the viability and success of developing larvae, affecting recruitment.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf184","usgsCitation":"Mariz, C.F., de Melo Alves, M.K., Magnuson, J.T., Braga de Castro, I., Silva de Andrade, F.A., Zanardi-Lamardo, E., Dias Medeiros, I., and Carvalho, P.S., 2025, Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development: Environmental Toxicology and Chemistry, v. 44, no. 11, p. 3363-3374, https://doi.org/10.1093/etojnl/vgaf184.","productDescription":"12 p.","startPage":"3363","endPage":"3374","ipdsId":"IP-172025","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":494897,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Mariz, Célio F.","contributorId":360535,"corporation":false,"usgs":false,"family":"Mariz","given":"Célio","middleInitial":"F.","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Melo Alves, Maria Karolaine","contributorId":360536,"corporation":false,"usgs":false,"family":"de Melo Alves","given":"Maria","middleInitial":"Karolaine","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":947191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braga de Castro, Italo","contributorId":360537,"corporation":false,"usgs":false,"family":"Braga de Castro","given":"Italo","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silva de Andrade, Felix Augusto","contributorId":360538,"corporation":false,"usgs":false,"family":"Silva de Andrade","given":"Felix","middleInitial":"Augusto","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zanardi-Lamardo, Eliete","contributorId":360539,"corporation":false,"usgs":false,"family":"Zanardi-Lamardo","given":"Eliete","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dias Medeiros, Igor","contributorId":360540,"corporation":false,"usgs":false,"family":"Dias Medeiros","given":"Igor","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947195,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carvalho, Paulo S.","contributorId":360541,"corporation":false,"usgs":false,"family":"Carvalho","given":"Paulo","middleInitial":"S.","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947196,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269660,"text":"70269660 - 2025 - The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics","interactions":[],"lastModifiedDate":"2025-08-18T15:22:57.469229","indexId":"70269660","displayToPublicDate":"2025-07-22T07:45:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics","docAbstract":"Forest harvesting can lead to mercury (Hg) mobilization from soils to aquatic habitats and promote the transformation of inorganic Hg to highly neurotoxic and bioaccumulative methyl-Hg (MeHg). Multiple past studies reveal broad variation of stream water MeHg and total Hg (THg) concentrations responses to forest harvesting, which has confounded messaging to forest and resource managers. To advance beyond divergent and sometimes contradictory findings, we synthesize information for 23 previously studied catchments in North America and Fennoscandia, and compiled a uniform set of soil, landscape, and harvesting properties to identify forest management, riparian, and hillslope factors that influence responses of stream water MeHg and THg concentrations. From this synthesis, we found catchments with high soil moisture and organic soil layers > 100 cm to be at highest risk for disturbance-induced increases in MeHg formation after harvest, but not necessarily affecting concentrations of MeHg in stream waters. Instead, the combination of MeHg formation in soils along with factors that affect mobilization with runoff to streams most influenced how forest harvest affects MeHg concentrations in stream waters.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5c02787","usgsCitation":"Eklof, K., de Wit, H.A., Eckley, C.S., Eagles-Smith, C., Eggert, S.L., Mackereth, R., Skyllberg, U., Ukonmaanaho, L., Verta, M., Allan, C.J., Emilson, E., Kidd, K.A., Mitchell, C., Munthe, J., Sallantaus, T., Segersten, J., Bravo, A., Kolka, R., McCarter, C., Porvari, P., Ring, E., Sebestyen, S., Sikstrom, U., and Zetterberg, T., 2025, The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics: Environmental Science and Technology, v. 59, no. 30, p. 15944-15955, https://doi.org/10.1021/acs.est.5c02787.","productDescription":"12 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0000-0001-5646-5390","orcid":"https://orcid.org/0000-0001-5646-5390","contributorId":332803,"corporation":false,"usgs":false,"family":"de Wit","given":"Heleen","email":"","middleInitial":"A.","affiliations":[{"id":13695,"text":"Norwegian Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":944307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eckley, Chris S. 0000-0002-6986-4451","orcid":"https://orcid.org/0000-0002-6986-4451","contributorId":246031,"corporation":false,"usgs":false,"family":"Eckley","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":944308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eggert, Susan L.","contributorId":191489,"corporation":false,"usgs":false,"family":"Eggert","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":944310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mackereth, Robert W.","contributorId":358852,"corporation":false,"usgs":false,"family":"Mackereth","given":"Robert W.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":944311,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skyllberg, Ulf","contributorId":358855,"corporation":false,"usgs":false,"family":"Skyllberg","given":"Ulf","affiliations":[{"id":12666,"text":"Swedish University of Agricultural 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While West Virginia’s alluvial aquifers have been studied extensively, bedrock aquifers have only been characterized for studies completed in a few areas in Jefferson, McDowell, and Monroe Counties. Bedrock aquifers are water supplies for public supply, agriculture, industry, and residential homeowner use. In this study, the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management, provides a statewide assessment of the occurrence and distribution of fractures within bedrock aquifers of the State and the various topographic, physiographic, and lithologic influences controlling the occurrence and distribution of bedrock fractures. The results of this study provide an increased understanding of the distribution of fractures in bedrock aquifers in West Virginia and help to verify trends that have been suspected for many years but were never well documented or verified by data.
The results confirmed that the density of fractures and those that were determined to be water bearing decrease significantly with depth. A statistically significant difference in the density of fractures was observed at a depth of 215 feet for wells in the Appalachian Plateaus Physiographic Province’s and in the Valley and Ridge Physiographic Province’s aquifers; a higher density of fractures and water-bearing fractures were above a depth of 215 feet than below that depth. This is an important consideration when drilling wells for residential, commercial, industrial, or agricultural water supply.
Abandoned underground coal mines are commonly believed to form large pools of water in the interconnected mine entries in abandoned room and pillar coal mines. Such pools of water can and do exist in abandoned underground coal mines, but many mines lack open entries and are held up by overburden strata and pillars that can collapse and form aquifers comprised of vast interconnected rubble zones (gob), especially in older mines.
Data assessed for this study showed that shale-corrected values of effective porosity for limestone aquifers in West Virginia had a median value of 2 percent and an average value of 4 percent and generally are mineralized with low effective porosity. Argillaceous or sandy limestone has a median shale-corrected porosity of 4 percent and an average shale-corrected porosity of 5 percent. The median and average shale-corrected porosity of sandstone aquifers was estimated to be 14 percent, but the median shale-corrected porosity for argillaceous or calcareous sandstone was 5 percent and the average shale-corrected porosity for argillaceous or calcareous sandstone was 6 percent. Even though shale has a relatively high total sonic porosity compared to other lithologies, shale and siltstone had relatively low shale-corrected porosity, ranging from 0 to 2 percent.
Well yields were previously documented to be highest in valley settings, lowest on hilltops, and intermediate on hillsides. Transmissivity data provided by this study confirm this general pattern within the Appalachian Plateaus Province; however, the Valley and Ridge Province does not follow this pattern. While still lowest on hilltop settings, the highest well yields were in hillside settings. The trend for the Valley and Ridge Province was likely skewed because of 9 high-yield wells specifically targeting deeper thin limestone units, such as the Tonoloway and Helderberg Limestones, at depths with transmissivity in excess of 2,000 feet squared per day in Mineral County, West Virginia, or targeting karst aquifers in Berkeley, Jefferson, or Greenbrier Counties, West Virginia.
Finally, water-bearing fractures have been hypothesized to comprise a small number of all fractures within a typical bedrock well in West Virginia. Data collected for this study support this theory. A total of 3,403 fractures were identified during this study; 3,151 (92.6 percent) of those fractures are low-transmissive, and only 252 (7.4 percent) fractures are water-bearing. Even though a well may contain many fractures, less than 8 percent are considered water-bearing fractures.
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Virginia\",\"nation\":\"USA \"}}]}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Healthy stream networks rely on diverse fish assemblages and the mobility of fish between habitats to maintain ecosystem structure and function. Anthropogenic structures that impede fish movement (e.g., roads, dams) disrupt life cycles of migratory fishes and isolate fish populations making them more sensitive to environmental stressors. Growing interest in barrier removal is driven by the recognition that restoring fish passage improves ecosystem health and resilience at multiple trophic levels, but identifying which streams should be reconnected and which barriers to remove remains an unresolved issue. Using the state of Missouri (USA) stream network, we developed an interactive decision support tool designed to help natural resource managers identify a shortlist of stream reaches to prioritize for reconnection, barrier removal, and habitat restoration. Our aquatic connectivity decision support tool, which we call AquaConn, is aimed at managers seeking to improve connectivity within and between existing conservation areas, particularly in wadeable streams. AquaConn provides a flexible platform that allows managers to consider entire assemblages of fish or individual species across local or more regional spatial scales. While AquaConn (https://bit.ly/4kQgXK8) was built for the state of Missouri, our approach and framework can be replicated in any geographical region that has adequate fish assemblage data.
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\"}}]}","volume":"50","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Winikoff, Sarah G.","contributorId":360333,"corporation":false,"usgs":false,"family":"Winikoff","given":"Sarah","middleInitial":"G.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":946979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":268045,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sievert, Nicholas","contributorId":272500,"corporation":false,"usgs":false,"family":"Sievert","given":"Nicholas","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":946981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274005,"text":"70274005 - 2025 - Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","interactions":[],"lastModifiedDate":"2026-02-20T16:11:51.850785","indexId":"70274005","displayToPublicDate":"2025-07-21T10:05:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","docAbstract":"Knowledge of animal-movement patterns is a crucial component in identifying areas with high potential for human–wildlife conflict and in prioritizing associated management actions. Electrical energy infrastructure is a major source of mortality for animals worldwide, with millions of birds colliding with or being electrocuted by power lines and power-pole infrastructure each year. Movement, habitat use, and the spatial distribution of electrocution risk can vary with age, but studies of younger age classes are often hampered because these groups are difficult to observe and lack well-defined home ranges. To identify movement patterns and high-use areas of bald eagles in Arizona, USA, we analyzed global positioning system (GPS) telemetry data collected from 13 immature bald eagles (Haliaeetus leucocephalus) across Arizona between 2017 and 2023. We built multi-scale, integrated step-selection functions that evaluated eagle responses to a suite of environmental covariates. We then used these models to simulate eagle movement and predict habitat use within and surrounding Maricopa County, which contains both the Phoenix Metropolitan Area and the plurality of bald eagle breeding areas in Arizona. We provide a use case for how these simulated movements could be used by resource managers to identify high-risk areas for electrocution. Eagles avoided urban areas and selected steeper slopes, more pronounced ridges, and areas with greater water and wetland land cover. Predicted habitat use by bald eagles was greatest near waterbodies and along ridges and steep slopes, and indicated where power infrastructure may pose greater electrocution risk. We show how integrated step-selection analyses and movement path simulation may be used for subadult animals lacking stable home ranges to predict high-use areas and identify locations with greater potential for negative human–wildlife interactions.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70061","usgsCitation":"Cappello, C. ., Jacobson, K.V., Driscoll, J.T., McCarty, K.M., Bauder, J.M., 2025, Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species: Journal of Wildlife Management, v. 89, no. 7, e70061, 19 p., https://doi.org/10.1002/jwmg.70061.","productDescription":"e70061, 19 p.","ipdsId":"IP-178672","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.5,\n 34.1\n ],\n [\n -113.5,\n 32.5\n ],\n [\n -111,\n 32.5\n ],\n [\n -111,\n 34.1\n ],\n [\n -113.5,\n 34.1\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Cappello, Caroline D.","contributorId":366625,"corporation":false,"usgs":false,"family":"Cappello","given":"Caroline","middleInitial":" D.","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":956103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Kenneth V.","contributorId":366626,"corporation":false,"usgs":false,"family":"Jacobson","given":"Kenneth","middleInitial":"V.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, James T.","contributorId":366627,"corporation":false,"usgs":false,"family":"Driscoll","given":"James","middleInitial":"T.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Kyle M.","contributorId":366629,"corporation":false,"usgs":false,"family":"McCarty","given":"Kyle","middleInitial":"M.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273993,"text":"70273993 - 2025 - Shared leadership can promote success in collaborative research networks in ecology","interactions":[],"lastModifiedDate":"2026-02-24T14:55:18.949074","indexId":"70273993","displayToPublicDate":"2025-07-21T09:03:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Shared leadership can promote success in collaborative research networks in ecology","docAbstract":"1. While collaborative science is becoming the norm in ecology, many ecologists participating in collaborations are less aware of the body of research that studies the processes by which collaborative teams organize and communicate.
2. Here, we discuss how we successfully used a shared leadership model in the Dry Rivers Research Coordination Network. We discuss how this model promote dour success in different stages of the project, using the Tuckman model of team development: forming, storming, norming, performing and adjourning.
3. Shared leadership in the forming phase helped us recruit a diverse membership from different scientific disciplines. In the storming and norming phases, shared leadership was especially useful in ensuring that all voices were heard in establishing group norms that promoted adhesion among and investment by RCN members. Shared leadership in the performing phase was crucial in providing opportunities for early career members to lead projects, and in the adjourning phase we reflected upon our entire collaboration to identify that shared leadership was crucial to our success, generating the thesis for this commentary.
4. It is our hope that others may find this discussion of our experience in implementing a shared leadership model useful in developing their own fruitful collaborations.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.70109","usgsCitation":"Allen, D.C., Burgin, A.J., Seybold, E.C., Dodds, W.K., Busch, M.H., Bergstrom, A., Krabbenhoft, C.A., Boersma, K.S., Stegen, J.C., Olden, J.D., Atkinson, C.L., Jones, C.N., Datry, T., Godsey, S.E., Shogren, A.J., Walters, A.W., Plont, S., Walker, R.H., Shanafield, M., Mims, M.C., Price, A.N., Smith, C.R., You, Y., Bogan, M.T., Burrows, R.M., Messager, M.L., Stubbington, R., Zimmer, M.A., 2025, Shared leadership can promote success in collaborative research networks in ecology: Functional Ecology, 9 p., https://doi.org/10.1111/1365-2435.70109.","productDescription":"9 p.","ipdsId":"IP-176946","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500600,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.70109","text":"Publisher Index Page"},{"id":500414,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Daniel C. 0000-0002-0451-0564","orcid":"https://orcid.org/0000-0002-0451-0564","contributorId":225169,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","middleInitial":"C.","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":956032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgin, Amy J.","contributorId":366528,"corporation":false,"usgs":false,"family":"Burgin","given":"Amy","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":956033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seybold, Erin C.","contributorId":366529,"corporation":false,"usgs":false,"family":"Seybold","given":"Erin","middleInitial":"C.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":956034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dodds, Walter K.","contributorId":366531,"corporation":false,"usgs":false,"family":"Dodds","given":"Walter","middleInitial":"K.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":956035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Busch, Michelle H.","contributorId":366533,"corporation":false,"usgs":false,"family":"Busch","given":"Michelle","middleInitial":"H.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":956036,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergstrom, Anna 0000-0002-9684-4018","orcid":"https://orcid.org/0000-0002-9684-4018","contributorId":289664,"corporation":false,"usgs":false,"family":"Bergstrom","given":"Anna","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":956037,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krabbenhoft, Corey A.","contributorId":366536,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Corey","middleInitial":"A.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":956038,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boersma, Kate S.","contributorId":366537,"corporation":false,"usgs":false,"family":"Boersma","given":"Kate","middleInitial":"S.","affiliations":[{"id":34010,"text":"University of San Diego","active":true,"usgs":false}],"preferred":false,"id":956039,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stegen, James C.","contributorId":366539,"corporation":false,"usgs":false,"family":"Stegen","given":"James","middleInitial":"C.","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":956040,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Olden, Julian D.","contributorId":366541,"corporation":false,"usgs":false,"family":"Olden","given":"Julian","middleInitial":"D.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":956041,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Atkinson, Carla L.","contributorId":366543,"corporation":false,"usgs":false,"family":"Atkinson","given":"Carla","middleInitial":"L.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":956042,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jones, C. 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USA","interactions":[],"lastModifiedDate":"2025-07-23T14:32:38.22027","indexId":"70269443","displayToPublicDate":"2025-07-20T09:28:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA","docAbstract":"Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with known bioaccumulative and toxic effects in aquatic ecosystems. This study assessed site-specific differences in PFAS contamination in fish from Ashumet Pond, Sudbury River, and Great Herring Pond (reference site) in Massachusetts. Fish from Ashumet Pond exhibited the highest PFAS concentrations, particularly perfluorooctane sulfonate (PFOS), which exceeded levels in plasma almost 650 times those at the reference site. Principal component analysis identified distinct PFAS profiles at each site, reflecting localized contamination sources. Temporal analysis at Ashumet Pond revealed a substantial increase in plasma PFOS and perfluorodecanoic acid (PFDA) from 2020 to 2022. Tissue distribution analyses showed the highest PFAS concentrations in plasma, followed by liver and muscle, consistent with PFAS binding affinity for blood proteins. Species-specific differences in PFAS bioaccumulation were observed, with largemouth bass (Micropterus nigricans) exhibiting higher body burdens than banded killifish (Diaphanus fundulus), likely due to trophic position and dietary exposure. Histopathological assessments and gene transcript analyses revealed associations between PFAS exposure and inflammatory responses, oxidative stress, endocrine disruption, and immune-related pathways, with the most pronounced molecular effects observed at the downstream site of the Sudbury River. This study underscores the importance of understanding site-specific contamination sources, exposure pathways, and biological effects of PFAS in fish. These findings would benefit from additional research on sediment contamination, temporal analyses at each site, trophic transfer, and transcriptomic analyses across multiple organs to further elucidate PFAS toxicity mechanisms and guide remediation efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquatox.2025.107499","usgsCitation":"Walsh, H.L., Blazer, V., Lord, E., Hurley, S.T., and LeBlanc, D.R., 2025, Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA: Aquatic Toxicology, v. 287, 107499, 17 p., https://doi.org/10.1016/j.aquatox.2025.107499.","productDescription":"107499, 17 p.","ipdsId":"IP-179883","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquatox.2025.107499","text":"Publisher Index Page"},{"id":492766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"287","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":943755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":349694,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":943756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lord, Emma","contributorId":358438,"corporation":false,"usgs":false,"family":"Lord","given":"Emma","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":943757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurley, Stephen T.","contributorId":138980,"corporation":false,"usgs":false,"family":"Hurley","given":"Stephen","email":"","middleInitial":"T.","affiliations":[{"id":12605,"text":"Mass Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":943758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943759,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269620,"text":"70269620 - 2025 - Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA","interactions":[],"lastModifiedDate":"2025-07-28T14:17:21.049353","indexId":"70269620","displayToPublicDate":"2025-07-20T09:10:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA","docAbstract":"The ecological importance of springs in semiarid regions is far greater than their small size and sparse distribution, yet little is known about the hydrologic functioning of these systems. During 2016–22, 261 springs were visited in the volcanic terrane of eastern Oregon and northern Nevada. When conditions were suitable, measurements of discharge, water temperature, and specific conductance were made, and samples for the analysis of carbon-14, tritium, and water stable isotopes (WSI) were collected. A subset of 60 springs was revisited during different seasons in the same year and during the dry season in multiple years to evaluate variability in discharge, chemistry, and groundwater age. Specific conductance and WSI varied considerably among springs across the study area but were unexpectedly stable across seasons and years at individual springs. Seasonal and interannual variability in spring discharge was related to the residence time of the discharging groundwater. Springs discharging older groundwater (103–104 years) had significantly less variability in their discharge compared to springs discharging younger groundwater (100–101 years). Variability among springs discharging younger groundwater included cessation of late-summer discharge at 18 % of the repeat-visit springs. A logistic regression model predicted the age of discharging spring water with 89 % accuracy using only the spring latitude, longitude, elevation, and δ2H value. This study framework provides a simple, inexpensive, and robust method to provisionally assess the hydrologic behavior of springs having little or no prior information in understudied, semiarid regions across the globe.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133922","usgsCitation":"Johnson, H.M., 2025, Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA: Journal of Hydrology, v. 662, no. Part A, 133922, 13 p., https://doi.org/10.1016/j.jhydrol.2025.133922.","productDescription":"133922, 13 p.","ipdsId":"IP-123085","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":493312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133922","text":"Publisher Index Page"},{"id":492994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.31311680484953,\n 41.99539074875983\n ],\n [\n -120.0068581722988,\n 41.99391273807197\n ],\n [\n -119.90145747408332,\n 41.992434693061426\n ],\n [\n -119.84179670150823,\n 41.66048803137227\n ],\n [\n -118.9246520186846,\n 41.65959449142923\n ],\n [\n -118.93301194332504,\n 41.98445357532694\n ],\n [\n -117.02491929749873,\n 42.016929659002585\n ],\n [\n -117.01355889504242,\n 43.86708893750037\n ],\n [\n -116.91131527293696,\n 44.17343283492443\n ],\n [\n -117.20668573679785,\n 44.30365776197061\n ],\n [\n -117.26349474591721,\n 44.58751884415352\n ],\n [\n -117.18671855238352,\n 44.79442609102742\n ],\n [\n -117.77146876695777,\n 44.926186190521406\n ],\n [\n -117.91090405154984,\n 44.91839177439985\n ],\n [\n -117.97144831985975,\n 44.63186629043838\n ],\n [\n -118.6664325411721,\n 44.37656025661704\n ],\n [\n -119.868869617017,\n 44.396170474914186\n ],\n [\n -121.12677954373844,\n 44.318586844969104\n ],\n [\n -121.51042244069035,\n 42.944368334976076\n ],\n [\n -121.28368996303429,\n 42.40400912273424\n ],\n [\n -120.73802661060382,\n 42.42707264631977\n ],\n [\n -120.26821317970226,\n 41.99741467441126\n ],\n [\n -120.31311680484953,\n 41.99539074875983\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"662","issue":"Part A","noUsgsAuthors":false,"publicationDate":"2025-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Henry M. 0000-0002-7571-4994 hjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":869,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"hjohnson@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944189,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70269455,"text":"70269455 - 2025 - A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","interactions":[],"lastModifiedDate":"2025-07-23T14:18:18.596644","indexId":"70269455","displayToPublicDate":"2025-07-19T09:12:39","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":"A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","docAbstract":"Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub-watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5-m stream sub-reach across 426 sub-watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub-watersheds that contained training data and decreased to 0.67 for sub-watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040478","usgsCitation":"Burnett, J., Jaeger, K.L., Johnson, S.L., Wondzell, S., Dunham, J., Barker, M., Heaston, E.D., Chelgren, N., Wing, M., Staab, B., and Brown, M., 2025, A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation: Water Resources Research, v. 61, no. 7, e2025WR040478, 29 p., https://doi.org/10.1029/2025WR040478.","productDescription":"e2025WR040478, 29 p.","ipdsId":"IP-166720","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040478","text":"Publisher Index Page"},{"id":492763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Coast Range, Cascades, Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.57426256802401,\n 42.38410052088969\n ],\n [\n -121.21373758117394,\n 45.28963738462886\n ],\n [\n -121.54860532807825,\n 45.699012143249206\n ],\n [\n -122.42689354437806,\n 45.47540902005011\n ],\n [\n -123.13281971409793,\n 44.19046431828406\n ],\n [\n -122.79064395589202,\n 45.678368936712275\n ],\n [\n -123.17575442941168,\n 46.11430287596801\n ],\n [\n -123.98200543500289,\n 46.12677363777644\n ],\n [\n -124.52205720467518,\n 42.84974529742891\n ],\n [\n -124.19614743434411,\n 41.9512539365376\n ],\n [\n -121.59312670246439,\n 42.062457611874805\n ],\n [\n -121.47701396768437,\n 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0000-0002-4223-3465","orcid":"https://orcid.org/0000-0002-4223-3465","contributorId":192210,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":943797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wondzell, Steven M. 0000-0002-5182-5796","orcid":"https://orcid.org/0000-0002-5182-5796","contributorId":337143,"corporation":false,"usgs":false,"family":"Wondzell","given":"Steven M.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":943798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barker, Matthew Irwin 0000-0002-5286-4930","orcid":"https://orcid.org/0000-0002-5286-4930","contributorId":358465,"corporation":false,"usgs":true,"family":"Barker","given":"Matthew Irwin","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaston, Emily Dawn 0000-0002-3949-391X","orcid":"https://orcid.org/0000-0002-3949-391X","contributorId":290618,"corporation":false,"usgs":true,"family":"Heaston","given":"Emily","email":"","middleInitial":"Dawn","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":943802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wing, Michael G.","contributorId":358467,"corporation":false,"usgs":false,"family":"Wing","given":"Michael G.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943803,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Staab, Brian","contributorId":358469,"corporation":false,"usgs":false,"family":"Staab","given":"Brian","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943804,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brown, Michael E.","contributorId":358471,"corporation":false,"usgs":false,"family":"Brown","given":"Michael E.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":943805,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70268790,"text":"sir20255054 - 2025 - Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2026-02-03T14:29:12.653472","indexId":"sir20255054","displayToPublicDate":"2025-07-18T13:39:29","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":"2025-5054","displayTitle":"Hydrogeologic Framework and Conceptual Model of the Red River Alluvial Aquifer East of Lake Texoma, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","docAbstract":"The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. At present (2025), the Oklahoma Water Resources Board has not established a maximum annual yield for the Red River alluvial aquifer east of Lake Texoma. To support the evaluation and determination of a maximum annual yield, a hydrogeologic framework and conceptual groundwater-flow model were developed to assess groundwater availability in the Red River alluvial aquifer east of Lake Texoma.
The scope of this hydrologic investigation is the alluvium and terrace containing the Red River alluvial aquifer in Oklahoma between Lake Texoma, the Texas State line, and the Arkansas State line, an extent referred to in this report as “the eastern part of the Red River alluvial aquifer.” Parts of the alluvium and terrace extent in Arkansas and Texas are included in some analyses to address hydrologic influences from outside the aquifer’s boundaries in Oklahoma.
The eastern part of the Red River alluvial aquifer in southeastern Oklahoma consists of approximately 401,280 acres of Quaternary alluvium and terrace deposits associated with the Red River and its major tributaries. Mean annual recharge to the aquifer for the 1980–2022 study period was estimated to be 8.62 inches per year, or 17.98 percent of the mean annual precipitation over the same period (47.94 inches). This mean annual recharge rate is equivalent to an inflow of approximately 288,250 acre-feet per year for the eastern part of the Red River alluvial aquifer. Recharge estimated using the Soil-Water-Balance code accounts for 98.7 percent of the conceptual-model inflows to the eastern part of the Red River alluvial aquifer. Saturated-zone evapotranspiration accounts for 11.9 percent and net streambed seepage accounts for 87.4 percent of the outflows in the conceptual model.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adv6484","usgsCitation":"Florez, M., Li, B.Q., Shelly, D.R., Angulo, M., and Sanabria-Gomez, J., 2025, Long-term dynamics of earthquake swarms in the Yellowstone caldera: Science Advances, v. 11, no. 29, eadv6484, 10 p., https://doi.org/10.1126/sciadv.adv6484.","productDescription":"eadv6484, 10 p.","ipdsId":"IP-175431","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":495178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adv6484","text":"Publisher Index Page"},{"id":495121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.2,\n 44.85\n ],\n [\n -111.2,\n 44.1\n ],\n [\n -110.2,\n 44.1\n ],\n [\n -110.2,\n 44.85\n ],\n [\n -111.2,\n 44.85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"29","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Florez, Manuel","contributorId":360774,"corporation":false,"usgs":false,"family":"Florez","given":"Manuel","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Bing Q.","contributorId":360823,"corporation":false,"usgs":false,"family":"Li","given":"Bing","middleInitial":"Q.","affiliations":[],"preferred":false,"id":947633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":947634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angulo, Mia","contributorId":360775,"corporation":false,"usgs":false,"family":"Angulo","given":"Mia","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanabria-Gomez, Jose","contributorId":360776,"corporation":false,"usgs":false,"family":"Sanabria-Gomez","given":"Jose","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269434,"text":"70269434 - 2025 - Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","interactions":[],"lastModifiedDate":"2025-08-18T15:15:37.43118","indexId":"70269434","displayToPublicDate":"2025-07-18T09:35:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","docAbstract":"The management of invasive Silver Carp Hypophthalmichthys molitrix in the Tennessee River basin focuses on removal, and there is interest in extending removal efforts to the tailwater environments of high-head locks and dams along the Tennessee River, such as Kentucky Dam. We used acoustic telemetry data from Silver Carp to understand important ecological associations underlying their residence in the Kentucky Dam tailwater, measured by daily fish counts and mean residence time.
We used time-series-informed regression models, variance partitioning, and cross-correlation function analysis to associate six predictors, including lock and dam operations (total, spill gate, and turbine discharge and number of lockages), hydrology (tailwater elevation), and water temperature, with two measures of Silver Carp residency (daily counts and mean residence time).
We found that spill-induced hydrology (total discharge + spill discharge + tailwater elevation) was negatively associated with daily counts but not with residence time, whereas temperature was positively associated with counts and negatively associated with residence times. Variance partitioning indicated that nearly all the variance in counts and residence times was jointly explained by temporal effects, lock and dam operations (discharge, tailwater elevation, and lockages), and temperature. The cross-correlations indicated that the counts were lagged by all predictors, sometimes up to 5 d, whereas residence times were lagged by both total and spill discharge and number of lockages.
We found that discharge and water temperature were principally associated with residency of Silver Carp in the Kentucky Dam tailwater. However, these associations were entirely temporally constrained, which can affect how strongly and how quickly Silver Carp respond to changing environmental conditions across different time scales. Managers can leverage these associations to plan removal periods where daily tailwater conditions/dam operations are favorable to invasive carp residence (e.g., >10°C and <2,500 m3/s) and adjust fishing effort to optimize removal rates in response to changing conditions.
Perfluorodecanesulfonate (PFDS), a long-chain polyfluoroalkyl substance (PFAS), is widely detected in aquatic environments and increasingly recognized for its environmental persistence and bioaccumulative potential; however, its immunotoxicity remains poorly understood in aquatic biota. In this study, early life stage zebrafish (Danio rerio) were exposed to environmentally relevant concentrations of PFDS and PFOS for 120 h to better characterize the adverse effects of PFDS on aquatic organisms. Additionally, the toxicological differences between PFDS and PFOS at the same exposure concentrations were compared, as PFDS is a known substitute for PFOS. PFDS bioaccumulated in zebrafish larvae at environmentally relevant concentrations, which disrupted immune function by altering the number of macrophages and neutrophils, inducing oxidative stress, and dysregulating immune markers such as interleukins and immunoglobulins. Mechanistically, PFDS activated the nuclear factor kappa B (NF-κB) signaling pathway, driving pro-inflammatory cytokine expression and immune dysfunction. Furthermore, the use of a NF-κB morpholino knockdown confirmed the role of the NF-κB pathway in mediating PFDS-induced immunotoxicity. These findings provide the first comprehensive evidence of PFDS-induced immunotoxicity being mediated through NF-κB activation, offering novel insights into the ecological risks of long-chain perfluorosulfonic acids. Notably, PFDS exhibited a stronger immunotoxic response relative to PFOS, indicating that its adverse effects may be more severe. Overall, these findings provide valuable insights for the ecological risk assessment of PFDS and the toxic potential that unregulated PFAS can have to aquatic systems.
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The connection between inland fish, fisheries, and their ecosystems means that addressing the needs of fish directly offers opportunities to meet multiple global commitments and provide indicators of progress towards many global goals. In this perspective, we highlight opportunities to better integrate inland fish and fisheries into MEAs, specifically the Convention on Biological Diversity (CBD), Convention on Wetlands (commonly known as the Ramsar Convention), Convention on Conservation of Migratory Species (CMS), Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), and World Heritage Convention (WHC). Greater attention on inland fish and fisheries through MEAs could help ensure more holistic planning, investment, and conservation of these important fish and fisheries, their biodiversity, the essential resources they provision, and the environments they inhabit.
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niche of brown bears: Constraints on adaptive capacity in human-modified landscapes","docAbstract":"DDiel activity rhythms, representing the behavioral pattern of the sleep–wake cycle, may be adjusted by wildlife in response to changes in environmental conditions. An increase in nocturnality is typically recognized as an adaptive strategy to segregate from humans and mitigate heat stress. Numerous studies have investigated spatial patterns and habitat use of large carnivores in human-modified landscapes, but little research has examined their activity rhythms. We compiled Global Positioning System data (2004–2022) for 139 brown bears Ursus arctos from six populations across Europe, representing a human-modified landscape, and the Greater Yellowstone Ecosystem, U.S.A., representing a landscape with limited human impact, which we used to calculate hourly movement rates as an activity proxy. Using a Bayesian approach to model the temporal autocorrelation of activity data, we tested if the extent of nocturnality in brown bears is modulated by intensity of human encroachment, accounting for primary productivity and maximum ambient temperature. All bear populations exhibited a predominantly bimodal, crepuscular pattern of activity, although Yellowstone bears were proportionally more crepuscular and diurnal. Whereas the effect of primary productivity was variable, all European populations became more nocturnal in response to higher human encroachment and reduced diurnal and crepuscular activity at higher summer temperatures, decreasing overall diel activity levels. Yellowstone bears displayed the greatest shift towards nocturnality among all populations in response to increasing human encroachment, and increased nocturnal activity to compensate for lower diurnal and crepuscular activity at higher summer temperatures. Our research indicates that European bears in human-modified landscapes may be reaching a limit in the behavioral plasticity they can manifest in their activity patterns, being already constrained into increased nocturnality. Our findings enhance the understanding of brown bear adaptive capacity to accommodate future changes, such as urbanization and increasing temperatures, to the ecosystems they inhabit.
","language":"English","publisher":"Wiley","doi":"10.1002/ecog.07979","usgsCitation":"Donatelli, A., Ćirović, D., Haroldson, M.A., Huber, Đ., Kindberg, J., Kojola, I., Kusak, J., Mastrantonio, G., Ordiz, A., Reljić, S., Santini, L., van Manen, F.T., and Ciucci, P., 2025, The diel niche of brown bears: Constraints on adaptive capacity in human-modified landscapes: Ecography, v. 2025, no. 10, e07979, 15 p., https://doi.org/10.1002/ecog.07979.","productDescription":"e07979, 15 p.","ipdsId":"IP-174846","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":493787,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecog.07979","text":"Publisher Index Page"},{"id":492607,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Croatia, Finland, Italy, Russia, Serbia, Sweden, United States","geographicExtents":"{\n \"type\": 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Sapienza","active":true,"usgs":false}],"preferred":false,"id":943657,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":943658,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ciucci, P.","contributorId":358405,"corporation":false,"usgs":false,"family":"Ciucci","given":"P.","affiliations":[{"id":81866,"text":"University of Rome La Sapienza","active":true,"usgs":false}],"preferred":false,"id":943659,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70269707,"text":"70269707 - 2025 - Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","interactions":[],"lastModifiedDate":"2025-07-30T15:06:19.598148","indexId":"70269707","displayToPublicDate":"2025-07-18T07:58:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22155,"text":"Smart Agricultural Technology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","docAbstract":"Cover crops play a critical role in providing agroecological services such as improving soil health, reducing erosion and nitrogen loss, and suppressing weeds, which are closely tied to their performance such as accumulated biomass. This study evaluated the Active Canopy Sensor (ACS) -214, an active proximal sensing device equipped with its own light-emitting red and near-infrared spectral reflectance sensors, a time-of-flight laser, and an ultrasonic sensor, for estimating winter cover crop biomass across 13 U.S. states from 2020 to 2024. We assessed 11 species from three functional groups – grasses (n = 797), legumes (n = 264), and brassicas (n = 181) – using Random Forest (RF) models and four cross-validation strategies. The ACS-214 showed moderate to strong prediction accuracy for grasses (R2 = 0.51 – 0.64) and legumes (R2 = 0.44 – 0.76), though performance declined in leave-one-region-out analyses (R2 = 0.06 – 0.46), indicating limited spatial generalizability. Brassica models had low prediction accuracy for all models (R2 < 0.30), likely due to flowering and patchy growth. Biomass prediction breakpoints were observed at ∼3000 kg ha−1 for legumes and ∼4000 kg ha−1 for grasses. We also evaluated the effectiveness of using ACS-214 data to train Sentinel-2 satellite imagery for estimating grass cover crop biomass using withheld, out of bag data from 2023 to 2024. Sentinel-2 RF models trained with ACS-214 data showed good agreement with field-sampled (R2 = 0.58 – 0.61) and ACS-214-estimated biomass (R2 = 0.70). While Sentinel-2 offers scalability, the ACS-214 enables finer-resolution biomass mapping and better accounts for within-field variability, making it an effective tool for localized management and monitoring. These findings support the integration of proximal and satellite sensing approaches to enhance cover crop biomass estimation and agroecological assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atech.2025.101201","usgsCitation":"Jennewein, J., Davis, B., Seehaver-Eagan, S., Nicolette, J., Pittman, J., Hively, W.D., Goldsmith, A., Hidalgo, C., Reberg-Horton, C., and Mirsky, S., 2025, Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions: Smart Agricultural Technology, v. 12, 101201, 22 p., https://doi.org/10.1016/j.atech.2025.101201.","productDescription":"101201, 22 p.","ipdsId":"IP-179201","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":493304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atech.2025.101201","text":"Publisher Index Page"},{"id":493188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Indiana, Iowa, Kansas, Maryland, Missouri, North Carolina, Ohio, New Hampshire, Vermont, Virginia, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.92714553560637,\n 43.58854319693313\n ],\n [\n -95.89232587289348,\n 37.62183341552925\n ],\n [\n -89.95992461869106,\n 37.07043638610585\n ],\n [\n -88.56407871751861,\n 30.53924077937387\n ],\n [\n -87.95786849494071,\n 30.079081766107564\n ],\n [\n -79.28622937957765,\n 30.005749406912585\n ],\n [\n -71.27060896702632,\n 45.07860396784778\n ],\n [\n -86.55806437204849,\n 45.188229262227445\n ],\n [\n -91.6664764308591,\n 46.72848518852835\n ],\n [\n -96.92714553560637,\n 43.58854319693313\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":944485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Brian W. 0000-0003-0714-5133","orcid":"https://orcid.org/0000-0003-0714-5133","contributorId":358921,"corporation":false,"usgs":false,"family":"Davis","given":"Brian W.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seehaver-Eagan, S. 0009-0002-1048-9623","orcid":"https://orcid.org/0009-0002-1048-9623","contributorId":358924,"corporation":false,"usgs":false,"family":"Seehaver-Eagan","given":"S.","affiliations":[{"id":85715,"text":"North Carolina State University (NCSU)","active":true,"usgs":false}],"preferred":false,"id":944487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicolette, J. 0000-0002-8904-2391","orcid":"https://orcid.org/0000-0002-8904-2391","contributorId":358925,"corporation":false,"usgs":false,"family":"Nicolette","given":"J.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pittman, J.","contributorId":358926,"corporation":false,"usgs":false,"family":"Pittman","given":"J.","affiliations":[{"id":85718,"text":"BAER","active":true,"usgs":false}],"preferred":false,"id":944489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hively, W. 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Special conditions identified from U.S. Geological Survey gaging records and basin characteristics included regulation and diversion, urbanization, indeterminate drainage areas, drainage areas less than the minimum used in regional analyses, glacial lake outburst floods, other outburst floods, and snowmelt floods. For peak flows that occurred during calendar years 1980–2019, an atmospheric river dataset was used to identify atmospheric river presence or absence on the dates peak flows occurred. Extreme floods (defined as peak flows exceeding the 1-percent annual exceedance probability flood magnitude or an empirical measure of relative magnitude using Creager’s coefficient C) were identified and associated with flood-generating mechanisms using the other inventoried special conditions and other information.
The gaging record contained glacial lake outburst floods at 15 streamgages and other types of outburst floods at 10 streamgages. Non-outburst peak flows in Alaska resulted from a mixture of rainfall and melt-based flood-generating mechanisms in all but the most rain-dominated seasonal flow regime. Melt-based flood-generating mechanisms included snowmelt, high-elevation snow and ice melt, or rain-on-snow events. Atmospheric rivers were common in Alaska and conterminous basins in Canada, occurring in that region on 67 percent of the days in the calendar year 1980–2019 period. Atmospheric rivers were more common on the days of peak flows and even more common on the days of non-outburst extreme floods. The percentage of days when an atmospheric river was present increased to 78 percent for the days of peak flows in that period and to 83 percent for the days of non-outburst extreme floods in that period. Of 149 extreme floods in the gaging record, 38 were generated by outburst floods. Of the non-outburst extreme floods, 72 percent were generated by rainfall and 26 percent were generated by melt-based processes or a combination of rainfall and melt-based processes. Flood-generating mechanisms could not be determined for the final 2 percent of the non-outburst extreme floods because the month and day of the peak flows were unknown and no other information was available. Secondary factors strongly associated with extreme floods included antecedent rain and streamflow conditions and warm storm conditions that produced rain instead of snow or generated snowmelt.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska, 99508