Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 1.0 billion barrels of oil and 53.4 trillion cubic feet of gas in India and Sri Lanka.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253043","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Mercier, T.J., Le, P.A., Cicero, A.D., Drake, R.M., II, Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., and Timm, K.K., 2025, Assessment of undiscovered conventional oil and gas resources of India and Sri Lanka, 2024: U.S. Geological Survey Fact Sheet 2025–3043, 4 p., https://doi.org/10.3133/fs20253043.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169389","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":495323,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253043/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3043"},{"id":495284,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3043/fs20253043.xml"},{"id":495283,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3043/images"},{"id":495163,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13KMTXF","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—India and Sri Lanka Provinces—Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":495161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3043/coverthb.jpg"},{"id":495162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3043/fs20253043.pdf","text":"Report","size":"5.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3043"}],"country":"India, Sri Lanka","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[80.47672,29.72987],[80.08842,28.79447],[81.0572,28.4161],[81.99999,27.92548],[83.30425,27.36451],[84.67502,27.2349],[85.25178,26.7262],[86.02439,26.63098],[87.22747,26.3979],[88.06024,26.41462],[88.1748,26.81041],[88.04313,27.44582],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[88.83564,27.09897],[89.74453,26.7194],[90.37327,26.87572],[91.21751,26.80865],[92.03348,26.83831],[92.10371,27.45261],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.14603,23.6275],[91.86993,23.62435],[91.70648,22.98526],[91.15896,23.50353],[91.46773,24.07264],[91.91509,24.13041],[92.3762,24.97669],[91.7996,25.14743],[90.87221,25.1326],[89.92069,25.26975],[89.83248,25.96508],[89.35509,26.01441],[88.56305,26.44653],[88.20979,25.76807],[88.93155,25.23869],[88.30637,24.86608],[88.08442,24.50166],[88.69994,24.23371],[88.52977,23.63114],[88.87631,22.87915],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[68.8426,24.35913],[71.04324,24.35652],[70.8447,25.2151],[70.28287,25.72223],[70.16893,26.49187],[69.51439,26.94097],[70.6165,27.9892],[71.77767,27.91318],[72.82375,28.96159],[73.45064,29.97641],[74.42138,30.97981],[74.40593,31.69264],[75.25864,32.27111],[74.45156,32.7649],[74.10429,33.44147],[73.74995,34.3177],[74.2402,34.74889],[75.75706,34.50492],[76.87172,34.65354],[77.83745,35.49401]]],[[[81.78796,7.52306],[81.63732,6.48178],[81.21802,6.19714],[80.34836,5.96837],[79.87247,6.76346],[79.69517,8.20084],[80.1478,9.82408],[80.83882,9.26843],[81.30432,8.56421],[81.78796,7.52306]]]]},\"properties\":{\"name\":\"India\"}}]}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Omori’s law states that the rate of aftershocks decays as a function of inverse time. There are multiple physical explanations that we reduce into a nonlinear mixed effects relation of three terms: (1) a Rate/State expression that can account for static/dynamic and viscoelastic triggering caused directly by the mainshock, (2) a fluid diffusion triggering term, and (3) a randomized secondary triggering (cascade) term. We fit free physical-model parameters to an observed aftershock sequence through two nonlinear regression methods to find the relative contributions of physics-based models in an observed aftershock sequence. Results from both methods show that Rate/State models overpredict aftershock rates by ∼0–30%. Secondary aftershocks cause a net negative contribution (seismicity rate reduction that corrects overprediction by other terms) ranging between ∼0 and 30%. All regression solutions yield negative secondary triggering contributions without being guided to do so. A physical explanation for this is that aftershock occurrence relieves stress from the crust, ultimately causing the sequence to extinguish itself. Fluid diffusion triggering contributions range from ∼0 to 20%. Diffusion processes are observed to be shorter in time than the full duration of an aftershock sequence and they are also spatially limited, diminishing their influence. Our results apply to an aftershock decay curve from the 2016 Central Apennines earthquake sequence, meaning that our specific results may not be general. Our primary conclusion is that any one physical model cannot alone fit the observed sequence as well as the combination of three we investigated.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2025.1619887","usgsCitation":"Parsons, T.E., Geist, E.L., and Malagnini, L., 2025, An exploration of the relative influence of physical models for Omori’s law: Frontiers in Earth Science, v. 13, 1619887, 20 p., https://doi.org/10.3389/feart.2025.1619887.","productDescription":"1619887, 20 p.","ipdsId":"IP-173870","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2025.1619887","text":"Publisher Index Page"},{"id":496017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2025-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malagnini, L.","contributorId":358032,"corporation":false,"usgs":false,"family":"Malagnini","given":"L.","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":949365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271992,"text":"70271992 - 2025 - Detection and genetic characterization of red-spotted grouper nervous necrosis virus and a novel genotype of nervous necrosis virus in black sea bass from the U.S. Atlantic coast","interactions":[],"lastModifiedDate":"2026-02-10T13:37:55.887296","indexId":"70271992","displayToPublicDate":"2025-09-10T10:17:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Detection and genetic characterization of red-spotted grouper nervous necrosis virus and a novel genotype of nervous necrosis virus in black sea bass from the U.S. Atlantic coast","docAbstract":"Nervous necrosis virus (NNV) causes a neurologic disease in a wide range of marine fish and poses serious disease risks to marine aquaculture worldwide. Little is known about the presence of NNV along the Atlantic coast of the United States, aside from the presence of barfin flounder nervous necrosis virus (BFNNV) in coldwater species in the northern part of this range. Herein we conducted surveillance for NNV from 2020 to 2022 in the mid-Atlantic region of the United States in black sea bass Centropristis striata, a serranid fish that is found throughout the eastern U.S. coast. Molecular detection methods have identified and characterized red-spotted grouper nervous necrosis virus (RGNNV) sequences at low prevalence throughout the years. Further, in 2022, a higher prevalence of a novel NNV genotype, tentatively named black sea bass nervous necrosis virus (BSBNNV), was characterized for the first time. Though virus isolation was unsuccessful, this study was the first to genetically identify NNV in this region and in this species. These findings highlight the need for further research on NNV to understand epidemiology and virulence in the context of marine fisheries and an emerging marine aquaculture industry in the United States.
","language":"English","publisher":"MDPI","doi":"10.3390/v17091234","usgsCitation":"Lovy, J., Abbadi, M., Toffan, A., Das, N., Neugebauer, J., Batts, W., and Clarke, P., 2025, Detection and genetic characterization of red-spotted grouper nervous necrosis virus and a novel genotype of nervous necrosis virus in black sea bass from the U.S. Atlantic coast: Viruses, v. 17, no. 9, 1234, 19 p., https://doi.org/10.3390/v17091234.","productDescription":"1234, 19 p.","ipdsId":"IP-181771","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":496328,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v17091234","text":"Publisher Index Page"},{"id":496264,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Atlantic coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.66376207947636,\n 40.441483784005726\n ],\n [\n -74.69874772981566,\n 40.441483784005726\n ],\n [\n -74.69874772981566,\n 39.2532247332031\n ],\n [\n -73.66376207947636,\n 39.2532247332031\n ],\n [\n -73.66376207947636,\n 40.441483784005726\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Lovy, Jan 0000-0003-2704-0822","orcid":"https://orcid.org/0000-0003-2704-0822","contributorId":331539,"corporation":false,"usgs":true,"family":"Lovy","given":"Jan","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":949626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbadi, Miriam","contributorId":361912,"corporation":false,"usgs":false,"family":"Abbadi","given":"Miriam","affiliations":[{"id":86382,"text":"Istituto Zooprofilattico Sperimentale delle Venezie, Viale dell’Università 10, 35020 Legnaro (Padova), Italy","active":true,"usgs":false}],"preferred":false,"id":949627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toffan, Anna","contributorId":361913,"corporation":false,"usgs":false,"family":"Toffan","given":"Anna","affiliations":[{"id":86382,"text":"Istituto Zooprofilattico Sperimentale delle Venezie, Viale dell’Università 10, 35020 Legnaro (Padova), Italy","active":true,"usgs":false}],"preferred":false,"id":949628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Das, Nilanjana","contributorId":337003,"corporation":false,"usgs":false,"family":"Das","given":"Nilanjana","email":"","affiliations":[{"id":80944,"text":"Office of Fish and Wildlife Health and Forensics, New Jersey Fish and Wildlife, Oxford, NJ 07863, USA","active":true,"usgs":false}],"preferred":false,"id":949629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neugebauer, James","contributorId":361914,"corporation":false,"usgs":false,"family":"Neugebauer","given":"James","affiliations":[{"id":86385,"text":"Office of Fish and Wildlife Health and Forensics, New Jersey Fish and Wildlife, Oxford, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":949630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Batts, William 0000-0002-6469-9004","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":359732,"corporation":false,"usgs":false,"family":"Batts","given":"William","affiliations":[{"id":85434,"text":"Formerly USGS Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":949631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clarke, Peter","contributorId":361915,"corporation":false,"usgs":false,"family":"Clarke","given":"Peter","affiliations":[{"id":86386,"text":"Bureau of Marine Fisheries, New Jersey Fish and Wildlife, Nacote Creek, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":949632,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271742,"text":"70271742 - 2025 - Causal interpretations can be based on mechanistic knowledge","interactions":[],"lastModifiedDate":"2025-12-01T16:39:54.020377","indexId":"70271742","displayToPublicDate":"2025-09-10T09:51:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Causal interpretations can be based on mechanistic knowledge","docAbstract":"The Rocky Mountain Population (RMP) of trumpeter swans Cygnus buccinator (hereafter, swans) in North America includes breeders in the Greater Yellowstone Area (GYA) and other western states (together, United States segment) and western provinces of Canada (Canada segment). Conservation concern for the United States segment stems from its slow population growth and the resident nature of GYA swans, which intermingle with migrating Canada segment swans in wintering habitats. Thus, understanding variation in migratory behavior and habitat use by swans in the two population segments can inform how management actions may affect the RMP. We used telemetry data from 55 RMP swans captured in the western United States to understand their movements and habitat use. For 45 swans (60 swan-years) that spent the summer in the United States, distance traveled between breeding and wintering areas ranged from 0 km (i.e., no migration in 22% of swan-years) to 473 km, with an average of nonzero movements of 118 ± 95 km (SD). Swans traveled farther distances when maximum temperatures were lower. For 10 swans (16 swan-years) that spent the summer in Canada, five appeared to molt but not to nest, and four appeared to nest in one or more years. Migration timing was similar for molting and nesting swans. All five molting swans and one nesting swan spent at least one previous summer in the GYA. Migratory connectivity of all birds was weaker in years when more swans migrated to Canada for the summer. During the breeding season, Canada swans used low-elevation lakes, but United States swans used high-elevation lakes. Both groups of swans increased use of crop fields outside of the breeding season. Our study shows interchange between the United States and Canada segments, a finding that challenges the efficacy of existing population designations. Furthermore, variation in movement behavior of GYA swans suggests possible actions, such as restoring winter habitats to increase swan distribution and migration, to support swan conservation.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70096","usgsCitation":"Poessel, S.A., Sanders, T., Long, W., Kristof, A., Reishus, B., Proett, M., Gower, C., Ibrahim, N., and Katzner, T.E., 2025, Movements and habitat use vary across the Rocky Mountain Population of trumpeter swans: Journal of Wildlife Management, v. 89, no. 8, e70096, 18 p., https://doi.org/10.1002/jwmg.70096.","productDescription":"e70096, 18 p.","ipdsId":"IP-160496","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":496640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -138.95754939868905,\n 61.560322423115394\n ],\n [\n -118.55526728999622,\n 51.12368923776994\n ],\n [\n -119.05891663327156,\n 42.82280620245445\n ],\n [\n -113.19458823923267,\n 41.306395580626145\n ],\n [\n -110.6147155407601,\n 41.23543486615125\n ],\n [\n -111.72918253654919,\n 48.78609382462486\n ],\n [\n -114.68487126300441,\n 52.72581807685856\n ],\n [\n -131.60641572663843,\n 61.0005751873353\n ],\n [\n -138.95754939868905,\n 61.560322423115394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Poessel, Sharon A. 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":168465,"corporation":false,"usgs":true,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A.","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":950525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Todd","contributorId":357733,"corporation":false,"usgs":false,"family":"Sanders","given":"Todd","affiliations":[{"id":85545,"text":"U.S. Fish and Wildlife Service, Division of Migratory Bird Management","active":true,"usgs":false}],"preferred":false,"id":950526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, William","contributorId":242920,"corporation":false,"usgs":false,"family":"Long","given":"William","affiliations":[{"id":48582,"text":"(deceased)","active":true,"usgs":false}],"preferred":false,"id":950527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kristof, Andrea","contributorId":362455,"corporation":false,"usgs":false,"family":"Kristof","given":"Andrea","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":950528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reishus, Brandon","contributorId":362456,"corporation":false,"usgs":false,"family":"Reishus","given":"Brandon","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":950529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Proett, Matt","contributorId":362457,"corporation":false,"usgs":false,"family":"Proett","given":"Matt","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":950530,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gower, Claire","contributorId":362458,"corporation":false,"usgs":false,"family":"Gower","given":"Claire","affiliations":[{"id":39047,"text":"Montana Fish, Wildlife, and Parks","active":true,"usgs":false}],"preferred":false,"id":950531,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ibrahim, Nicole","contributorId":362461,"corporation":false,"usgs":false,"family":"Ibrahim","given":"Nicole","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":950532,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191909,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd","email":"tkatzner@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":950533,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272169,"text":"70272169 - 2025 - Assessing survey design for long-term population trend detection in piping plovers","interactions":[],"lastModifiedDate":"2025-11-18T15:45:14.370821","indexId":"70272169","displayToPublicDate":"2025-09-10T08:39:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Assessing survey design for long-term population trend detection in piping plovers","docAbstract":"Determining appropriate spatio-temporal scales for monitoring migratory shorebirds is challenging. Effective surveys must detect population trends without excessive or insufficient sampling, yet many programs lack formal evaluations of survey effectiveness. Using data from 2012 to 2019 on Louisiana’s barrier islands (Whiskey, west Raccoon, east Raccoon, and Trinity), we assessed how spatial and temporal scales influence population trend inference for piping plovers (Charadrius melodus). Point count data were aggregated to grid sizes from 50 to 200 m and analyzed using Bayesian dynamic occupancy models. We found occupancy and colonization estimates varied by spatial resolution, with space–time autocorrelation common across scales. Smaller islands (east and west Raccoon) yielded higher trend detection power due to better detectability, while larger islands (Trinity and Whiskey) showed lower power. Detectability, more than sampling frequency, drove trend inference. Models incorporating spatial autocorrelation outperformed traditional Frequentist approaches but showed poorer fit at coarser scales. These findings underscore how matching analytical scale to ecological processes and selecting appropriate models can influence predictions. Power analysis revealed that increasing survey frequency may improve inference, especially in low-detectability areas. Overall, our study highlights how careful scale selection, model diagnostics, and survey design can enhance monitoring efficiency and support long-term conservation of migratory shorebirds.
","language":"English","publisher":"MDPI","doi":"10.3390/land14091846","usgsCitation":"Bohnett, E., Schulz, J., Dobbs, R., Hoctor, T., Ahmad, B., Rashid, W., and Waddle, J., 2025, Assessing survey design for long-term population trend detection in piping plovers: Land, v. 14, no. 9, 1846, 25 p., https://doi.org/10.3390/land14091846.","productDescription":"1846, 25 p.","ipdsId":"IP-180225","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":496734,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land14091846","text":"Publisher Index Page"},{"id":496588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Isles Dernieres, Raccoon Island, Trinity Island, Whiskey Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.35300936814708,\n 29.370915739158065\n ],\n [\n -91.35300936814708,\n 29.010416129236035\n ],\n [\n -90.53724293701912,\n 29.010416129236035\n ],\n [\n -90.53724293701912,\n 29.370915739158065\n ],\n [\n -91.35300936814708,\n 29.370915739158065\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bohnett, Eve","contributorId":272548,"corporation":false,"usgs":false,"family":"Bohnett","given":"Eve","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":950294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulz, Jessica","contributorId":330111,"corporation":false,"usgs":false,"family":"Schulz","given":"Jessica","affiliations":[{"id":52994,"text":"New Hampshire Department of Environmental Services","active":true,"usgs":false}],"preferred":false,"id":950295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobbs, Robert C. 0000-0002-9079-7249 rdobbs@usgs.gov","orcid":"https://orcid.org/0000-0002-9079-7249","contributorId":200300,"corporation":false,"usgs":false,"family":"Dobbs","given":"Robert C.","email":"rdobbs@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":950296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoctor, Thomas","contributorId":330115,"corporation":false,"usgs":false,"family":"Hoctor","given":"Thomas","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":950297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ahmad, Bilal","contributorId":330120,"corporation":false,"usgs":false,"family":"Ahmad","given":"Bilal","email":"","affiliations":[{"id":78816,"text":"University of Swat, Pakistan","active":true,"usgs":false}],"preferred":false,"id":950298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rashid, Wajid","contributorId":330121,"corporation":false,"usgs":false,"family":"Rashid","given":"Wajid","email":"","affiliations":[{"id":78816,"text":"University of Swat, Pakistan","active":true,"usgs":false}],"preferred":false,"id":950299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":215911,"corporation":false,"usgs":true,"family":"Waddle","given":"J. 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However, these efforts are hindered by conflicting interpretations on the number and timing of collisional events, and the timing of crustal thickening and associated surface uplift. Here, we resolve this with quantitative paleo-crustal thickness estimates in the northwestern HKT orogen. We show that: (a) the paleo-Asian margin had thick crust (50–60 km) at least 65 Ma prior to terminal collision, consistent with a continental arc setting, (b) crustal thickening to 60 km or more occurred at ca. 60–50 Ma in the Kohistan-Ladakh arc and by 40–25 Ma in the paleo-Asian margin, indicating a multi-stage Himalayan collision, and (c) modern crustal thicknesses in the northwestern HKT have been sustained since ca. 40–25 Ma suggesting an orogenic steady-state in which crustal thickening, crustal flow, and surface uplift have been balanced by erosion.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GC012287","usgsCitation":"Hillenbrand, I.W., and Guevara, V.E., 2025, Multi-stage crustal thickening, surface uplift, and collision in the western Himalaya-Karakoram-Tibet orogen revealed by chemical mohometry: Geophysical Research Letters, v. 26, no. 9, e2025GC012287, 12 p., https://doi.org/10.1029/2025GC012287.","productDescription":"e2025GC012287, 12 p.","ipdsId":"IP-176047","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":495721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gc012287","text":"Publisher Index Page"},{"id":495318,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Himalaya-Karakoram-Tibet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 76.9315577415208,\n 32.20096031337238\n ],\n [\n 76.9315577415208,\n 29.60948255862013\n ],\n [\n 81.65814316613967,\n 29.60948255862013\n ],\n [\n 81.65814316613967,\n 32.20096031337238\n ],\n [\n 76.9315577415208,\n 32.20096031337238\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":948329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guevara, Victor E.","contributorId":361175,"corporation":false,"usgs":false,"family":"Guevara","given":"Victor","middleInitial":"E.","affiliations":[{"id":40457,"text":"Amherst College","active":true,"usgs":false}],"preferred":false,"id":948330,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271204,"text":"sir20245118 - 2025 - Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019","interactions":[],"lastModifiedDate":"2026-02-03T15:22:21.725184","indexId":"sir20245118","displayToPublicDate":"2025-09-09T15:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5118","displayTitle":"Spatiotemporal Variability of Algal Biomass and Nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019","title":"Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019","docAbstract":"Cyanobacterial harmful algal blooms (CyanoHABs) have become increasingly common, threatening the security of water resources globally. The U.S. Geological Survey conducted high-resolution nearshore mapping surveys using boat-mounted multiparameter sondes and nitrate sensors during the summer and fall of 2019 on Owasco Lake and Seneca Lake, two lakes with documented CyanoHABs in the Finger Lakes region of New York State. Discrete sensor measurements and water-quality samples were collected at fixed points along survey routes and continuous data were generated at open-water monitoring platforms. This investigation examined whether water-quality information from nearshore surveys was representative of open-water conditions and if nearshore surveys could be used to identify areas with localized nearshore CyanoHABs and potential sources of nutrients not captured by tributary sampling.
In addition to comparisons across methods, nearshore concentrations of nitrate and chlorophyll were evaluated relative to tributary outlets, cyanobacterial abundance and biovolume at discrete locations, and the locations of near-surface CyanoHABs that were designated as “confirmed with high toxins” by the New York State Department of Environmental Conservation. Nitrate and chlorophyll concentrations were comparable across methods for each lake, although concentration ranges were typically higher for nearshore mapping datasets than for nearshore discrete datasets. Nearshore surveys indicated areas of nitrate enrichment that varied temporally in both lakes. Orthophosphate was not routinely detected. Across methods, median chlorophyll concentrations were higher for the summer survey than for the fall survey in Owasco Lake. Nearshore chlorophyll concentrations varied more temporally in Owasco Lake than in Seneca Lake.
Phytoplankton and cyanobacterial abundance and biovolume were about five times higher in Owasco Lake than in Seneca Lake. Cyanobacteria dominated the phytoplankton community in most samples, and Microcystis comprised the bulk of the cyanobacterial biovolume. The most abundant potential cyanotoxin-producing (specifically microcystins) genera were Microcystis, Synechococcus, Aphanocapsa, and Pseudanabaena. The cyanobacterial community composition was comparable between open-water monitoring platforms and nearshore samples. Microcystins were detected in seven survey samples from Owasco Lake, in one survey sample from Seneca Lake, and in one sample each from the open-water monitoring platforms on Owasco and Seneca Lakes that were collected about 7 days before the fall surveys. Microcystin detections were not consistently associated with high cyanobacterial cell counts or cyanotoxin-producing genera.
Results from nearshore surveys were comparable to open-water monitoring platforms and discrete nearshore observations in the absence of nearshore or open-water CyanoHABs in these systems during the study. Patterns of nearshore concentrations of nitrate and chlorophyll from nearshore surveys may aid in the identification of areas with localized nitrate loading and shifts in phytoplankton abundance and community composition.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245118","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation and the New York State Department of Health","usgsCitation":"Stouder, M.D.W., Gifford, S.R., Gutchess, K.M., Finkelstein, K.M., Johnston, B.D., Beaulieu, K.M., Rosen, J.J., Essig, M.L., and Foster, G.M., 2025, Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019: U.S. Geological Survey Scientific Investigations Report 2024–5118, 39 p., https://doi.org/10.3133/sir20245118.","productDescription":"Report: viii, 39 p.; 2 Appendixes; 2 Data Releases","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-136099","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":495115,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5118/sir20245118_app2.pdf","text":"Appendix 2","size":"397 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5118 Appendix 2","linkHelpText":"- Standard Operating Procedure for the Analysis of Total Microcystins and Nodularins in Discrete Water-Quality Samples for the Cyanobacterial Harmful Algal Blooms Advanced Monitoring Pilot Study"},{"id":495113,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9046YOS","text":"USGS data release","linkHelpText":"Field data for an evaluation of sensors for continuous monitoring of harmful algal blooms in the Finger Lakes, New York, 2018–2020"},{"id":495129,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98P1VV6","text":"USGS data release","linkHelpText":"High-resolution spatial water-quality and discrete phytoplankton data, Owasco Lake, Seneca Lake, and Skaneateles Lake, Finger Lakes Region, New York, 2018–2019"},{"id":495205,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5118/sir20245118.XML"},{"id":495111,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5118/images"},{"id":495110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5118/sir20245118.pdf","text":"Report","size":"9.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5118 PDF"},{"id":495155,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5118/coverthb.jpg"},{"id":495204,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245118/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5118 HTML"},{"id":495114,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5118/sir20245118_app1.pdf","text":"Appendix 1","size":"657 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5118 Appendix 1","linkHelpText":"- Quality Assurance Project Plan for Discrete Water-Quality Samples, Measurements, and Shoreline Surveys Conducted for the Cyanobacterial Harmful Algal Blooms Advanced Monitoring Pilot Study"}],"country":"United States","state":"New York","otherGeospatial":"Finger Lakes region, Owasco Lake, Seneca Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.99541024728366,\n 42.88134266146028\n ],\n [\n -76.99541024728366,\n 42.3766690451576\n ],\n [\n -76.82099577233303,\n 42.3766690451576\n ],\n [\n -76.82099577233303,\n 42.88134266146028\n ],\n [\n -76.99541024728366,\n 42.88134266146028\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.55679821172299,\n 42.9076046331341\n ],\n [\n -76.55679821172299,\n 42.75261670559294\n ],\n [\n -76.44184136620188,\n 42.75261670559294\n ],\n [\n -76.44184136620188,\n 42.9076046331341\n ],\n [\n -76.55679821172299,\n 42.9076046331341\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Urbanization reshapes dissolved organic matter (DOM) sources, transport, and transformations through changes in vegetation, hydrology, and management of waste and water. Yet the impacts of urbanization on DOM are variable within and among cities. Predicting heterogeneous responses to urbanization is challenged by diverse human activities and underlying biophysical variation along stream networks. Using data from the 486 largest urban areas in the continental United States and seven focal cities, we identified macro and local scale urban gradients in social, built, and biophysical factors that are expected to shape DOM. We used these gradients and the literature to develop hypotheses about heterogeneity in DOM quantity and quality within and among cities. Interactions among landscape and infrastructure attributes across spatial and temporal scales result in heterogeneous responses in DOM. Characterizing and quantifying these inconsistent responses to urbanization in contrasting settings may help to better understand heterogeneity and identify generalities among urban watersheds.
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basin","interactions":[],"lastModifiedDate":"2025-09-10T14:21:34.022261","indexId":"70271364","displayToPublicDate":"2025-09-09T09:16:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10942,"text":"PNAS Nexus","active":true,"publicationSubtype":{"id":10}},"title":"Extremophile hotspots linked to containerized industrial waste dumping in a deep-sea basin","docAbstract":"Decaying barrels on the seafloor linked to DDT contamination have raised concerns about the public health implications of decades old industrial waste dumped off the coast of Los Angeles. To explore their contents, we collected sediment cores perpendicular to five deep-sea barrels. The concentration of DDT and its breakdown products were highly elevated relative to control sites yet did not vary with distance from the barrels, suggesting that they were not associated with the contamination. Sediment cores collected through white halos surrounding three barrels were enriched in calcite and had elevated pH. The associated microbial communities were low diversity and dominated by alkalophilic bacteria with metagenome-assembled genomes adapted to high pH. A solid concretion sampled between a white halo and barrel was composed of brucite, a magnesium hydroxide mineral that forms at high pH. Based on these findings, we postulate that leakage of containerized alkaline waste triggered the formation of mineral concretions that are slowly dissolving and raising the pH of the surrounding sediment pore water. This selects for taxa adapted to extreme alkalinity and drives the precipitation of “anthropogenic” carbonates forming white halos, which serve as a visual identifier of barrels that contained alkaline waste. Remarkably, containerized alkaline waste discarded >50 years ago represents a persistent pollutant creating localized mineral formations and microbial communities that resemble those observed at some hydrothermal systems. These formations were observed at one-third of the visually identified barrels in the San Pedro Basin and have unforeseen, long-term consequences for benthic communities in the region.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/pnasnexus/pgaf260","usgsCitation":"Gutleben, J., Podell, S., Mizell, K., Sweeney, D., Neira, C., Levin, L.A., and Jensen, P.R., 2025, Extremophile hotspots linked to containerized industrial waste dumping in a deep-sea basin: PNAS Nexus, v. 4, no. 9, pgaf260, 11 p., https://doi.org/10.1093/pnasnexus/pgaf260.","productDescription":"pgaf260, 11 p.","ipdsId":"IP-176533","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":495761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/pnasnexus/pgaf260","text":"Publisher Index Page"},{"id":495275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Pedro basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.61291617535386,\n 34.514462698011144\n ],\n [\n -120.61291617535386,\n 32.94564082277532\n ],\n [\n -117.80700327525463,\n 32.94564082277532\n ],\n [\n -117.80700327525463,\n 34.514462698011144\n ],\n [\n -120.61291617535386,\n 34.514462698011144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutleben, Johanna","contributorId":361076,"corporation":false,"usgs":false,"family":"Gutleben","given":"Johanna","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Podell, Sheila","contributorId":361078,"corporation":false,"usgs":false,"family":"Podell","given":"Sheila","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":948221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweeney, Douglas","contributorId":361081,"corporation":false,"usgs":false,"family":"Sweeney","given":"Douglas","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neira, Carlos","contributorId":361084,"corporation":false,"usgs":false,"family":"Neira","given":"Carlos","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948223,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Levin, Lisa A.","contributorId":361086,"corporation":false,"usgs":false,"family":"Levin","given":"Lisa","middleInitial":"A.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948224,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Paul R.","contributorId":361089,"corporation":false,"usgs":false,"family":"Jensen","given":"Paul","middleInitial":"R.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":948225,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273049,"text":"70273049 - 2025 - Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling","interactions":[],"lastModifiedDate":"2025-12-12T15:25:24.213331","indexId":"70273049","displayToPublicDate":"2025-09-09T09:08:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling","docAbstract":"Freshwater mussels are critical to the health of freshwater systems, but their populations are declining dramatically throughout the world. The limited resources available for freshwater mussel conservation necessitates the geographic prioritization of conservation-related actions. However, lack of knowledge about freshwater mussel spatial distributions hinders decision making in this context. In this study, we assessed the distribution of twelve native freshwater mussel species across six Northeastern states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine) in the United States using data collected from lentic and lotic environments by eight state agencies. We first modeled individual distributions using a maximum entropy (MaxEnt) model and then compiled distribution models to assess the distribution of freshwater mussel species richness. We also determined geographic prioritization for three conservation-related actions: species surveys, land protection, and population restoration of species of high conservation concern. We found that the percent of catchments predicted to have species occurrence (based on a probability threshold) varied across species, with Elliptio complanata (Eastern elliptio) predicted to occur in the greatest percent of available catchments (33.92%) and Alasmidonta heterodon (Dwarf wedgemussel) expected in the smallest percent (5.30%). The predicted overall species richness within our modeled catchments ranged from zero to all twelve species, with an average of two species per catchment. Although conservation priorities vary depending on the conservation action of interest, we found some areas of consistent importance including much of Maine and the southern reaches of the Connecticut River. An improved understanding of freshwater mussel distribution in a landscape framework will enable managers to implement more precise and efficient conservation interventions for these essential aquatic species.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0324387","usgsCitation":"O’Brien, R.S., DiRenzo, G.V., Roy, A.H., Carmignani, J., Quinones, R.M., Rogers, J.B., and Swartz, B.I., 2025, Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling: PLoS ONE, v. 20, no. 9, e0324387, 20 p., https://doi.org/10.1371/journal.pone.0324387.","productDescription":"e0324387, 20 p.","ipdsId":"IP-175157","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497699,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0324387","text":"Publisher Index Page"},{"id":497466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 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\"}}]}","volume":"20","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Brien, Rebecca S.M.","contributorId":363993,"corporation":false,"usgs":false,"family":"O’Brien","given":"Rebecca","middleInitial":"S.M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":952157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":952158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carmignani, Jason","contributorId":360465,"corporation":false,"usgs":false,"family":"Carmignani","given":"Jason","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":952160,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quinones, Rebecca M.","contributorId":120271,"corporation":false,"usgs":true,"family":"Quinones","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":952161,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Jennifer B.","contributorId":359344,"corporation":false,"usgs":false,"family":"Rogers","given":"Jennifer","middleInitial":"B.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":952162,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swartz, Beth I.","contributorId":364001,"corporation":false,"usgs":false,"family":"Swartz","given":"Beth","middleInitial":"I.","affiliations":[{"id":39965,"text":"Maine Department of Inland Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":952163,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271439,"text":"70271439 - 2025 - Evaluating mass flow meter measurements from chambers for greenhouse gas emissions from orphan wells and other point sources","interactions":[],"lastModifiedDate":"2025-09-15T14:10:51.273265","indexId":"70271439","displayToPublicDate":"2025-09-09T09:07:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":926,"text":"Atmospheric Measurement Techniques","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating mass flow meter measurements from chambers for greenhouse gas emissions from orphan wells and other point sources","docAbstract":"This study evaluates the performance of a rigid gas flux chamber equipped with a mass flow meter (MFM) for measuring gas emissions from leaking orphan wells and similar pressure-driven gas point sources. We conducted a series of laboratory and field experiments to evaluate the sensitivity, stability, and dynamic range of an MFM chamber system and found an optimal method for sealing the chamber to the ground to isolate the emission source. From these results, we estimate the effects of different soil gas permeabilities on measurements and identify the uncertainty of environmental processes that can impact measurements. Simulations of an MFM chamber are compared to those of a dynamic flux chamber to contrast the data derived with both methodologies and illustrate the potential for measuring high variability leaks with the MFM chamber. Using a low flow resistance MFM and a chamber well-sealed to the ground, it is possible to measure leaks down to 1.08 x 10-3 cubic meters per hour (m3 h−1) (refenced to 25°/1 atm), corresponding to 0.77 grams per hour (g h−1) methane or 2.11 g h−1 carbon dioxide, with a mean uncertainty of 0.89 % relative standard deviation. Environmental processes such as heated gas inside the chamber from solar gain, wind blowing across the chamber vent, and changing humidity in the chamber, can cause variation in MFM measurements. Over 11 d of continuous monitoring under varying weather conditions, the standard deviation of the environmentally sourced signals was found to be 7.40 x 10-3 m3 h−1 (equivalent to or 5.27 g h−1 methane or 14.45 g h−1 carbon dioxide). Strategies to obtain the highest quality data from MFM chambers include burying the edges of the chamber below the surface sufficiently deep to seal the chamber edges against gas flow and soaking the dirt with water to lower the chances of escaping gases, while monitoring the gas flow and adjusting the chamber seal to achieve a maximum flow rate.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/amt-18-4207-2025","usgsCitation":"Haase, K., and Gianoutsos, N.J., 2025, Evaluating mass flow meter measurements from chambers for greenhouse gas emissions from orphan wells and other point sources: Atmospheric Measurement Techniques, v. 18, p. 4207-4226, https://doi.org/10.5194/amt-18-4207-2025.","productDescription":"20 p.","startPage":"4207","endPage":"4226","ipdsId":"IP-174760","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":495731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/amt-18-4207-2025","text":"Publisher Index Page"},{"id":495492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":205943,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":948759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948760,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273998,"text":"70273998 - 2025 - Non-lethal detection of Renibacterium salmoninarum in Greenback Cutthroat Trout Oncorhynchus clarkii stomias comparing mucus, blood, and ovarian fluid samples to kidney tissues","interactions":[],"lastModifiedDate":"2026-02-25T14:31:06.650676","indexId":"70273998","displayToPublicDate":"2025-09-09T08:38:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Non-lethal detection of Renibacterium salmoninarum in Greenback Cutthroat Trout Oncorhynchus clarkii stomias comparing mucus, blood, and ovarian fluid samples to kidney tissues","title":"Non-lethal detection of Renibacterium salmoninarum in Greenback Cutthroat Trout Oncorhynchus clarkii stomias comparing mucus, blood, and ovarian fluid samples to kidney tissues","docAbstract":"Objective
Renibacterium salmoninarum, the causative agent of bacterial kidney disease, poses a major threat to both wild and aquaculture salmonid populations. Traditional detection methods typically involve lethal sampling to collect kidney tissues but are often impractical for species of conservation concern. This study evaluates nonlethal sampling techniques for detecting R. salmoninarum in Greenback Cutthroat Trout Oncorhynchus clarkii stomias by comparing mucus, blood, and ovarian fluid samples to conventional kidney tissue.
Methods
During the 2019 spawning season, we collected samples from 781 adult fish and tested for R. salmoninarum via direct fluorescent antibody test (DFAT) and quantitative polymerase chain reaction (qPCR).
Results
A total of 25 and 256 kidney tissues were positive by DFAT and qPCR, respectively. Of the three nonlethal samples tested, mucus swabs showed the highest percent correlation for detection with positive kidney tissues (DFAT = 47.6%, qPCR = 41.7%). Blood and ovarian fluid samples showed a lower percent correlation with positive kidney tissues (blood: DFAT = 12.0%, qPCR = 1.2%; ovarian fluid: DFAT = 12.5%, qPCR = 21.4%).
Conclusions
Our results suggest that nonlethal mucus swabbing could serve as a practical alternative for monitoring R. salmoninarum, especially in conservation efforts where minimizing fish mortality is critical.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jahafs/vsaf013","collaboration":"Colorado Parks and Wildlife","usgsCitation":"Tawni, F.B., Fetherman, E.R., Winkelman, D.L., 2025, Non-lethal detection of Renibacterium salmoninarum in Greenback Cutthroat Trout Oncorhynchus clarkii stomias comparing mucus, blood, and ovarian fluid samples to kidney tissues: Journal of Aquatic Animal Health, v. 37, no. 4, p. 192-198, https://doi.org/10.1093/jahafs/vsaf013.","productDescription":"7 p.","startPage":"192","endPage":"198","ipdsId":"IP-177786","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500835,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jahafs/vsaf013","text":"Publisher Index Page"},{"id":500407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Colorado Parks and Wildlife Poudre Rearing Unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.12260150413303,\n 40.98121418795711\n ],\n [\n -109.12260150413303,\n 37.019295224941985\n ],\n [\n -102.05306903469565,\n 37.019295224941985\n ],\n [\n -102.05306903469565,\n 40.98121418795711\n ],\n [\n -109.12260150413303,\n 40.98121418795711\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Tawni, Firestone B.R.","contributorId":366599,"corporation":false,"usgs":false,"family":"Tawni","given":"Firestone","middleInitial":"B.R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":956081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fetherman, Eric R.","contributorId":366600,"corporation":false,"usgs":false,"family":"Fetherman","given":"Eric","middleInitial":"R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":956082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271345,"text":"sir20255071 - 2025 - Effects of restoration work on Kootenai River Acipenser transmontanus (white sturgeon) critical habitat, Kootenai River, northern Idaho, 2011–22","interactions":[],"lastModifiedDate":"2026-02-03T15:21:34.489808","indexId":"sir20255071","displayToPublicDate":"2025-09-09T07:21:20","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":"2025-5071","displayTitle":"Effects of Restoration Work on Kootenai River Acipenser Transmontanus (White Sturgeon) Critical Habitat, Kootenai River, Northern Idaho, 2011–22","title":"Effects of restoration work on Kootenai River Acipenser transmontanus (white sturgeon) critical habitat, Kootenai River, northern Idaho, 2011–22","docAbstract":"Between 2011 and 2018, the Kootenai River Habitat Restoration Project, led by the Kootenai Tribe of Idaho, implemented restoration treatments to enhance the natural recruitment of the critically endangered Acipenser transmontanus (white sturgeon) and other fish native to the Kootenai River. These restoration treatments in the Straight and Braided Reaches of the Kootenai River are intended to increase flow depths and velocities to encourage Kootenai sturgeon to spawn in more suitable areas of the channel and to keep spawning gravels clean of fine sediment. This study assessed the effects of these restoration treatments on channel morphology, flow depths, velocities, pool extent, and suspended sediment entrainment in the study reach. Topographic surfaces representing channel morphology before (2011) and after construction (2020 and 2022) were used to quantify elevation changes and net volumetric change and to investigate changes in flow depths and depth-averaged velocities with two-dimensional hydraulic simulations. Effects of the restoration treatments on suspended sediment entrainment in the study reach were investigated using measurements of suspended sediment concentration collected between 2006 and 2023.
From 2011 to 2020, about 70 percent of the study reach showed detectable elevation change, but indeterminant volumetric change, suggesting redistribution of sediment but no notable change in transport capacity. Hydraulic simulations showed increased flow depths during bankfull conditions and variable change in depth averaged velocity during the receding limb of the spring freshet. Pool area and volume increased by 62 and 72 percent, respectively, and the average distance between pools declined. From 2020 to 2022, hydraulic simulations showed slight decreases in flow depths and pool metrics, suggesting sediment deposition in pools. Measured suspended sediment concentrations showed statistically significant declines upstream and downstream from the study reach, indicating a reduction in sediment entering the reach rather than restoration treatments driving a reduction in fine sediment entrainment. Findings from this work can guide future restoration efforts on the Kootenai River or other similar channels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255071","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Kenworthy, M.K., and Dudunake, T.J., 2025, Effects of restoration work on Kootenai River Acipenser transmontanus (white sturgeon) critical habitat, Kootenai River, northern Idaho, 2011–22: U.S. Geological Survey Scientific Investigations Report 2025–5071, 35 p., https://doi.org/10.3133/sir20255071.","productDescription":"Report: viii, 34 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150340","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":495230,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5071/images"},{"id":495228,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5071"},{"id":495227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5071/sir20255071.pdf","text":"Report","size":"7.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5071"},{"id":495226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5071/coverthb.jpg"},{"id":495229,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908KXMN","text":"USGS data release","description":"USGS data release","linkHelpText":"Impacts of restoration work on Kootenai River white sturgeon critical habitat, 2011–2022, Kootenai River, Idaho"},{"id":495231,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5071/sir20255071.XML"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.42129718355793,\n 48.76207255787526\n ],\n [\n -116.42129718355793,\n 48.68026818020829\n ],\n [\n -116.11918686246813,\n 48.68026818020829\n ],\n [\n -116.11918686246813,\n 48.76207255787526\n ],\n [\n -116.42129718355793,\n 48.76207255787526\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Temporal patterns in chemistry of headwater streams reflect responses of water and elemental cycles to perturbations occurring at local to global scales. We evaluated multi-scale temporal patterns in up to 32 y of monthly observations of stream chemistry (ammonium, calcium, dissolved organic carbon, nitrate, total dissolved phosphorus, and sulfate) in 22 reference catchments within the northern temperate zone of North America. Multivariate autoregressive state-space (MARSS) models were applied to quantify patterns at multi-decadal, seasonal, and shorter intervals during a period that encompassed warming climate, seasonal changes in precipitation, and regional declines in atmospheric deposition. Significant long-term trends in solute concentrations within a subset of the catchments were consistent with recovery from atmospheric deposition (e.g., calcium, nitrate, sulfate) and increased precipitation (e.g., dissolved organic carbon). Lack of evidence for multi-decadal trends in most catchments suggests resilience of northern temperate ecosystems or that subtle net effects of simultaneous changes in climate and disturbance regimes do not result in directional trends. Synchronous seasonal oscillations of solute concentrations occurred across many catchments, reflecting shared climate and biotic drivers of seasonality within the northern temperate zone. Despite shared patterns among catchments at a seasonal scale, multi-scale temporal patterns were statistically distinct among even adjacent headwater catchments, implying that local attributes of headwater catchments modify the signals imparted by atmospheric phenomena and regional disturbances. To effectively characterize hydrologic and biogeochemical responses to changing climate and disturbance regimes, catchment monitoring programs could include multiple streams with contributing areas that encompass regional heterogeneity in vegetation, topography, and elevation. Overall, detection of long-term patterns and trends requires monitoring multiple catchments at a frequency that captures periodic variation (e.g., seasonality) and a duration encompassing the perturbations of interest.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10533-025-01263-2","usgsCitation":"Harms, T.K., Hood, J., Scheuerell, M.D., Creed, I., Campbell, J.L., Fernandez, I.J., Higgins, S.N., Johnson, S.L., Shanley, J.B., Sebestyen, S., Webster, K.L., and Yoa, H., 2025, Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone: Biogeochemistry, v. 168, 72, 19 p., https://doi.org/10.1007/s10533-025-01263-2.","productDescription":"72, 19 p.","ipdsId":"IP-167949","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-025-01263-2","text":"Publisher Index Page"},{"id":496696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.78854045934415,\n 57.31227395978971\n ],\n [\n -126.56774947282855,\n 36.21030831674423\n ],\n [\n -69.53376916748583,\n 35.89418743935734\n ],\n [\n -49.19753148607294,\n 46.04477310474076\n ],\n [\n -55.28204218823373,\n 56.67586141571607\n ],\n [\n -136.78854045934415,\n 57.31227395978971\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"168","noUsgsAuthors":false,"publicationDate":"2025-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Harms, Tamara K.","contributorId":362630,"corporation":false,"usgs":false,"family":"Harms","given":"Tamara","middleInitial":"K.","affiliations":[{"id":13325,"text":"University of California Riverside","active":true,"usgs":false}],"preferred":false,"id":950672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hood, Jim","contributorId":362633,"corporation":false,"usgs":false,"family":"Hood","given":"Jim","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":950673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Creed, Irena F.","contributorId":204051,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":950675,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, John L.","contributorId":362636,"corporation":false,"usgs":false,"family":"Campbell","given":"John","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fernandez, I. 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L.","contributorId":362641,"corporation":false,"usgs":false,"family":"Webster","given":"K.","middleInitial":"L.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950682,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yoa, H.","contributorId":362642,"corporation":false,"usgs":false,"family":"Yoa","given":"H.","affiliations":[{"id":86544,"text":"Ontario Ministry of Environment","active":true,"usgs":false}],"preferred":false,"id":950683,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70271349,"text":"70271349 - 2025 - Analysis of a human-mediated microbioinvasion: The global spread of the benthic foraminifer Trochammina hadai Uchio, 1962","interactions":[],"lastModifiedDate":"2025-09-09T13:42:44.403245","indexId":"70271349","displayToPublicDate":"2025-09-08T08:38:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2391,"text":"Journal of Micropalaeontology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Analysis of a human-mediated microbioinvasion: The global spread of the benthic foraminifer Trochammina hadai Uchio, 1962","title":"Analysis of a human-mediated microbioinvasion: The global spread of the benthic foraminifer Trochammina hadai Uchio, 1962","docAbstract":"A non-indigenous species (NIS) of benthic foraminifera was first identified in a core collected in 1993 in San Francisco Bay, California, USA, and subsequently identified as Trochammina hadai Uchio, 1962. Archived samples and literature reviews were used to determine that the species, which is native to Asia, arrived in San Francisco Bay between the early 1960s and 1983. Through molecular analyses of specimens, archived samples and literature reviews from 1930–1983, and site surveys of harbors and estuaries along the western North American seaboard in 1994–2024, in total more than 2500 samples, we documented the presence of T. hadai at 73 locations in the USA and four in Canada. Trochammina hadai has also been recovered at nine sites in Sweden, two in France, three in Brazil, and two locations at one site in Australia. The rapid temporal and geographic spread of the NIS T. hadai in a non-native location is illustrated by a time series from 1930 to 2024 in San Francisco Bay. Between 1980 and 1986, the species' range expanded from low abundance (1.5 %) at a single site to cover nearly the entire South Bay with > 70 % abundance at some locations. By 1995 and continuing into 2010, the species expanded its range into the central and northern portions of San Francisco Bay, commonly with abundances of > 30 % and sometimes exceeding 70 %. This expansion may predate 1995, but a lack of samples makes it difficult to be more precise. Unfortunately, two Pb-210 and Cs-137-dated cores (BC01 and BC02) recovered from northern South Bay and Central Bay did not clarify this point, but additional cores may. Trochammina hadai is an infaunal opportunist that thrives in polluted locations. We surmise the species was introduced along the west coast of the USA in Puget Sound between 1902 and the 1920s, with cultivated oysters and oyster larvae and associated plant matter and residual sediment. This probably also happened in some areas of France, Sweden, and Brazil, where Japanese oysters were introduced in 1966, 1970, and 1975, respectively. After World War II, commercial shipping expanded dramatically and, with it, the release of ballast water and sediment in receiving ports, which introduced NIS worldwide. This primary vector of introduction occurred in large industrial harbors in several countries, sometimes followed by secondary introductions in small industrial centers and marinas by mud attached to the anchors and anchor chains of smaller boats.
","language":"English","publisher":"Copernicus","doi":"10.5194/jm-44-275-2025","usgsCitation":"McGann, M., Holzmann, M., Bouchet, V.M., Disaró, S.T., Eichler, P.P., Haig, D.W., Himson, S.J., Kitazato, H., Pavard, J., Polovodova Asteman, I., Rodrigues, A.R., Tremblin, C.M., Tsuchiya, M., Williams, M., O'Brien, P., Asplund, J., Axelsson, M., and Lorenson, T., 2025, Analysis of a human-mediated microbioinvasion: The global spread of the benthic foraminifer Trochammina hadai Uchio, 1962: Journal of Micropalaeontology, v. 44, no. 2, p. 275-317, https://doi.org/10.5194/jm-44-275-2025.","productDescription":"43 p.","startPage":"275","endPage":"317","ipdsId":"IP-172381","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":495388,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/jm-44-275-2025","text":"Publisher Index 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Sweden","active":true,"usgs":false}],"preferred":false,"id":948163,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":948164,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70271356,"text":"70271356 - 2025 - Changes in aeolian saltation cloud properties with wind speed and ripples","interactions":[],"lastModifiedDate":"2025-09-10T15:09:10.458291","indexId":"70271356","displayToPublicDate":"2025-09-08T08:05:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"Changes in aeolian saltation cloud properties with wind speed and ripples","docAbstract":"Aeolian sediment transport shapes landscapes on Earth and other planetary surfaces, yet key uncertainties remain in how the near-bed saltation cloud responds to changing wind and surface conditions. Leveraging recent advances in image-based particle tracking, we conducted wind tunnel experiments using high-speed imaging and Particle Tracking Velocimetry to quantify sand grain trajectories in saturated saltation clouds over both flat and rippled beds. Our open-source PTV workflow resolved particle motions within millimeters of the bed across a range of wind speeds. Supporting previous results, we find that mean particle velocities do not scale linearly with wind speed; instead, changes in particle velocity distributions—including skewness and kurtosis—emerge as wind strength and sediment flux increase. At higher transport rates, distinctions among saltation, reptation, and creep within the particle distribution become more smoothed, suggesting a continuum spectrum of particle behavior rather than discrete transport modes. Our new dataset of particle trajectories over an active rippled bed shows distinctions in particle speed across the aspects. On ripple stoss slopes, fast saltating grains co-occur with slow creeping particles, while lee slopes are depleted of slower grains, consistent with shadowing effects. These observations support a feedback between ripple morphology and near-bed particle trajectories, with implications for how splash events redistribute sediment momentum. This study contributes new high-resolution empirical data that illuminate how saltation cloud structure evolves with wind forcing and bedform development, advancing our understanding of aeolian sediment transport under complex, dynamic conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2025.100996","usgsCitation":"Kelley, M., Walker, I.J., Schmeeckle, M.W., Swann, C., Dorn, R., Roberts, M., and O'Brien, P., 2025, Changes in aeolian saltation cloud properties with wind speed and ripples: Aeolian Research, v. 74, 100996, 16 p., https://doi.org/10.1016/j.aeolia.2025.100996.","productDescription":"100996, 16 p.","ipdsId":"IP-171990","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Madeline Margaret 0009-0003-6406-2307","orcid":"https://orcid.org/0009-0003-6406-2307","contributorId":353253,"corporation":false,"usgs":true,"family":"Kelley","given":"Madeline Margaret","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Ian J. 0000-0001-5719-5310","orcid":"https://orcid.org/0000-0001-5719-5310","contributorId":361056,"corporation":false,"usgs":false,"family":"Walker","given":"Ian","middleInitial":"J.","affiliations":[{"id":86173,"text":"Department of Geography, UC Santa Barbara, Santa Barbara, CA 93106-4060, USA","active":true,"usgs":false}],"preferred":false,"id":948200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmeeckle, Mark W.","contributorId":178432,"corporation":false,"usgs":false,"family":"Schmeeckle","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":948201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swann, Christy","contributorId":258305,"corporation":false,"usgs":false,"family":"Swann","given":"Christy","email":"","affiliations":[{"id":40754,"text":"Naval Research Lab","active":true,"usgs":false}],"preferred":false,"id":948202,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dorn, Ron 0000-0003-1343-4556","orcid":"https://orcid.org/0000-0003-1343-4556","contributorId":361057,"corporation":false,"usgs":false,"family":"Dorn","given":"Ron","affiliations":[{"id":86175,"text":"School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, U.S.A","active":true,"usgs":false}],"preferred":false,"id":948203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, Michaela","contributorId":361058,"corporation":false,"usgs":false,"family":"Roberts","given":"Michaela","affiliations":[{"id":86175,"text":"School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, U.S.A","active":true,"usgs":false}],"preferred":false,"id":948204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Brien, Patrick 0000-0002-8956-2741","orcid":"https://orcid.org/0000-0002-8956-2741","contributorId":361059,"corporation":false,"usgs":false,"family":"O'Brien","given":"Patrick","affiliations":[{"id":86177,"text":"School of the Environment, Trent University, Peterborough, ON, K9L 0G2, Canada","active":true,"usgs":false}],"preferred":false,"id":948205,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70274105,"text":"70274105 - 2025 - Impacts of onshore wind energy production on biodiversity","interactions":[],"lastModifiedDate":"2026-02-25T15:11:33.524949","indexId":"70274105","displayToPublicDate":"2025-09-08T08:04:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23309,"text":"Nature Biodiversity Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of onshore wind energy production on biodiversity","docAbstract":"Wind is increasingly used as a renewable source of energy worldwide. However, harvesting wind energy can have negative consequences for biodiversity. In this Review, we summarize the growth of onshore wind power, its impacts on species and ecosystems, and how those impacts are assessed and mitigated. Across the construction, operation and decommissioning stages, wind facilities are associated with wildlife fatality and behavioural change as well as alteration, loss and fragmentation of terrestrial and aerial habitat. These negative consequences can be mitigated by avoiding construction of wind turbines at sensitive sites, detecting and deterring wildlife, curtailing turbines to reduce fatalities, and replacing lost habitats. Uncertainty about wildlife populations and their demographic parameters, the rate and extent of build-out of onshore wind energy, and best practices for mitigation, as well as variability in regulatory requirements by country or region, all contribute to the difficulty of predicting the consequences of this technology for biodiversity. Scenario-based modelling that incorporates population- and community-level consequences to biodiversity from varying degrees of wind energy development — including the cumulative effects of multiple facilities — is key to addressing this uncertainty.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s44358-025-00078-1","usgsCitation":"Katzner, T., Nelson, D.M., Marques, A.T., Voigt, C.C., Lambertucci, S.A., Rebolo, N., Bernard, E., Diehl, R.H., Murgatroyd, M., 2025, Impacts of onshore wind energy production on biodiversity: Nature Biodiversity Reviews, no. 1, p. 567-580, https://doi.org/10.1038/s44358-025-00078-1.","productDescription":"14 p.","startPage":"567","endPage":"580","ipdsId":"IP-174500","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":500506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"1","noUsgsAuthors":false,"publicationDate":"2025-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":956551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":956552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marques, Ana Teresa","contributorId":366998,"corporation":false,"usgs":false,"family":"Marques","given":"Ana","middleInitial":"Teresa","affiliations":[{"id":87526,"text":"Campus de Vairão, Portugal","active":true,"usgs":false}],"preferred":false,"id":956553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voigt, Christian C.","contributorId":366999,"corporation":false,"usgs":false,"family":"Voigt","given":"Christian","middleInitial":"C.","affiliations":[{"id":87527,"text":"Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":956554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lambertucci, Sergio A","contributorId":292399,"corporation":false,"usgs":false,"family":"Lambertucci","given":"Sergio","email":"","middleInitial":"A","affiliations":[{"id":62895,"text":"National Scientific and Technical Research Council","active":true,"usgs":false}],"preferred":false,"id":956555,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rebolo, Natalia","contributorId":367000,"corporation":false,"usgs":false,"family":"Rebolo","given":"Natalia","affiliations":[{"id":87528,"text":"INIBIOMA Universidad Nacional del Comahue—CONICET, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":956556,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bernard, Enrico","contributorId":367001,"corporation":false,"usgs":false,"family":"Bernard","given":"Enrico","affiliations":[{"id":87528,"text":"INIBIOMA Universidad Nacional del Comahue—CONICET, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":956557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":956558,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murgatroyd, Megan","contributorId":367002,"corporation":false,"usgs":false,"family":"Murgatroyd","given":"Megan","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":956559,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70271463,"text":"70271463 - 2025 - Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","interactions":[],"lastModifiedDate":"2025-09-17T14:00:53.292778","indexId":"70271463","displayToPublicDate":"2025-09-08T07:56:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Speleothem evidence for Late Miocene extreme Arctic amplification – An analogue for near-future anthropogenic climate change?","docAbstract":"The Miocene provides an excellent climatic analogue for near-future runaway anthropogenic warming, with atmospheric CO2 concentrations and global average temperatures similar to those projected for the coming century under extreme-emissions scenarios. However, the magnitude of Miocene Arctic warming remains unclear due to the scarcity of reliable proxy data. Here we use stable oxygen isotope and trace element analyses, alongside clumped isotope and fluid inclusion palaeothermometry of speleothems to reconstruct palaeo-environmental conditions near the Siberian Arctic coast during the Tortonian (8.68 ± 0.09 Ma). Stable oxygen isotope records suggest warmer-than-present temperatures. This is supported by temperature estimates based on clumped isotopes and fluid inclusions giving mean annual air temperatures between +6.6 and +11.1 °C, compared with −12.3 °C today. Trace elements records reveal a highly seasonal hydrological environment.
Our estimate of > 18 °C of Arctic warming supports the wider consensus of a warmer-than-present Miocene and provides a rare palaeo-analogue for future Arctic amplification under high-emissions scenarios. The reconstructed increase in mean surface temperature far exceeds temperatures projected in fully coupled global climate models, even under extreme-emissions scenarios. Given that climate models have consistently underestimated the extent of recent Arctic amplification, our proxy data suggest Arctic warming may exceed current projections.
An unknown occurrence of oil was detected near Avak Creek on Native lands on the North Slope of Alaska. Determining the source of oil was imperative for allowing stakeholders (Federal, State, and local government agencies and the landowner, an Alaska Native corporation) to make timely and informed decisions and mount a mitigation response, if required. The regional and local geological framework of the Avak Creek site was constructed using seismic surveys, well data, and basin modeling results, to identify local petroleum systems, map structural geometry and faults, define source rock thermal maturity distributions, and infer likely oil-migration pathways. Molecular hydrocarbon fingerprints (biomarkers, diamondoids, compound-specific isotopes) of the oil were compared to those of local and regional oil seeps, exploration well tests, and produced oils. Biomarker acid distributions characterized the history and extent of petroleum biodegradation. Integrating subsurface and geochemical parameters, the oil is interpreted to be a natural seep generated locally, predominantly from the Brookian Lower Cretaceous Hue Shale/gamma-ray zone, rather than an anthropogenic source of pollution. Results highlight sophisticated analytical technologies used to characterize complex, compositionally altered hydrocarbons. Results also advance our understanding of Brookian source rock distribution, subsurface petroleum migration pathways, and Arctic Alaska petroleum systems.
","conferenceTitle":"32nd International Meeting on Organic Geochemistry (IMOG) 2025","conferenceDate":"September 7-11, 2025","conferenceLocation":"Porto, Portugal","language":"English","publisher":"European Association of Geoscientists & Engineers","doi":"10.3997/2214-4609.202533156","usgsCitation":"Botterell, P.J., Houseknecht, D.W., Wycech, J.B., Moldowan, J.M., Lillis, P.G., Smith, R.A., and Maher, K., 2025, Avak Creek oil occurrence, North Slope, Alaska: Newly discovered oil seep on Native lands, near village of Utqiagvik, 32nd International Meeting on Organic Geochemistry (IMOG) 2025, v. 2025, Porto, Portugal, September 7-11, 2025, 2 p., https://doi.org/10.3997/2214-4609.202533156.","productDescription":"2 p.","ipdsId":"IP-175494","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":495630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Utqiagvik","volume":"2025","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, David W 0000-0002-9633-6910","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":361485,"corporation":false,"usgs":false,"family":"Houseknecht","given":"David","middleInitial":"W","affiliations":[{"id":86299,"text":"USGS Geology, Energy & Minerals Science Center (RET)","active":true,"usgs":false}],"preferred":false,"id":948886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wycech, Jody Brae 0000-0002-7073-3037","orcid":"https://orcid.org/0000-0002-7073-3037","contributorId":303104,"corporation":false,"usgs":true,"family":"Wycech","given":"Jody","email":"","middleInitial":"Brae","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moldowan, J. Mike","contributorId":361486,"corporation":false,"usgs":false,"family":"Moldowan","given":"J.","middleInitial":"Mike","affiliations":[{"id":50465,"text":"Biomarker Technologies, Inc.","active":true,"usgs":false}],"preferred":false,"id":948888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948889,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Rebecca A. 0000-0002-9823-706X rsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9823-706X","contributorId":201349,"corporation":false,"usgs":true,"family":"Smith","given":"Rebecca","email":"rsmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":948890,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Kimberley","contributorId":361487,"corporation":false,"usgs":false,"family":"Maher","given":"Kimberley","affiliations":[{"id":86300,"text":"Alaska Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":948891,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272292,"text":"70272292 - 2025 - Simple bagged movement models for telemetry data","interactions":[],"lastModifiedDate":"2025-11-20T16:07:50.517031","indexId":"70272292","displayToPublicDate":"2025-09-07T09:05:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Simple bagged movement models for telemetry data","docAbstract":"Determining which statistical methods are appropriate for data is both user and data dependent and prone to change as new methodology becomes available. This process encompasses model ideation, model selection, and determining appropriate use of statistical methods. Literature on models for animal movement emerging in the past two decades has yielded a rich collection of statistical methods garnering much deserved positive attention. Among such efforts, there is limited investigation of the broader place for simple machine learning methodology in animal movement modeling. We propose a bagged (i.e., bootstrap aggregated) animal movement model using simple, off-the-shelf machine learning algorithms. The model is intuitive, retains statistical inference about characteristics of animal movement (i.e., estimated from model-based summary statistics), and only requires knowledge of elementary statistical and machine learning analysis to understand. We show by simulation that our model can provide unbiased estimates of pertinent characteristics of animal movement (e.g., daily displacement) in the presence of large and realistic location error. We believe that increasing accessible literature on simple machine learning animal movement models provides valuable pedagogical and practical support for researchers using statistical models to study animal movement.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72060","usgsCitation":"Whetten, A.B., Hefley, T.J., Haukos, D.A., and Brewer, D.E., 2025, Simple bagged movement models for telemetry data: Ecology and Evolution, v. 15, no. 9, e72060, 14 p., https://doi.org/10.1002/ece3.72060.","productDescription":"e72060, 14 p.","ipdsId":"IP-178248","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72060","text":"Publisher Index Page"},{"id":496692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Whetten, Andrew B.","contributorId":362668,"corporation":false,"usgs":false,"family":"Whetten","given":"Andrew","middleInitial":"B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":950708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hefley, Trevor J.","contributorId":362671,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","middleInitial":"J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":950709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, Dustin E.","contributorId":362674,"corporation":false,"usgs":false,"family":"Brewer","given":"Dustin","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":950711,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274542,"text":"70274542 - 2025 - Small fish, big implications: Considerations for an ecosystem approach to capelin fisheries management","interactions":[],"lastModifiedDate":"2026-04-01T22:23:26.635675","indexId":"70274542","displayToPublicDate":"2025-09-06T15:09:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Small fish, big implications: Considerations for an ecosystem approach to capelin fisheries management","docAbstract":"Climate-driven changes in the Subarctic will directly impact capelin populations and the ecosystem they inhabit, including their predators, prey, and physical habitats. Consequently, incorporating ecosystem considerations in future capelin fisheries management is crucial. In this study, a multidisciplinary group of experts critically evaluated whether the current capelin stock assessment and management frameworks for the four main capelin stocks in the Barents Sea (BS), Iceland-East Greenland-Jan Mayen (IEGJM), Newfoundland and Labrador shelf (NL) and Alaska (AK) align with the principles of an Ecosystem Approach to Fisheries Management (EAFM). An evidence-based ranking of our knowledge on current capelin dynamics across ecological, economic, and social dimensions was conducted, using expert knowledge supported by literature. This exercise also identified data currently used for assessment and management, which highlighted that the existing capelin assessment frameworks include varying degrees of EAFM elements across stocks, such as considerations of trophic interactions, bottom-up processes, accounting for ecosystem uncertainty, and stakeholder engagement in the advisory process. Nonetheless, there is room for improvement where data and knowledge are lacking. We provide some key tactical (short-term) and strategic (long-term) recommendations from our perspective on what is required to ensure the sustainable management of capelin in the circumpolar region over the coming decades.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s11160-025-09986-z","usgsCitation":"Singh, W., Trochta, J.T., Hannah M. Murphy, H.M., McGowan, D.W., Adamack, A.T., Arimitsu, M.L., Barðarson, B., Björnsson, H., Bogstad, B., Boudreau, M., Chambers, C., Gjøsæter, H., Jansen, T., Jónsson, S.Þ., Kvamsdal, S., Lewis, R.S., Mikkelsen, N., Pedersen, T., Olafsdottir, A.H., Oostdijk, M., Silva, T., Skaret, G., Suryan, R.M., and Subbey, S., 2025, Small fish, big implications: Considerations for an ecosystem approach to capelin fisheries management: Reviews in Fish Biology and Fisheries, v. 35, p. 1899-1934, https://doi.org/10.1007/s11160-025-09986-z.","productDescription":"36 p.","startPage":"1899","endPage":"1934","ipdsId":"IP-173579","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":502063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11160-025-09986-z","text":"Publisher Index Page"},{"id":501975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2025-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Warsha","contributorId":368963,"corporation":false,"usgs":false,"family":"Singh","given":"Warsha","affiliations":[{"id":40381,"text":"Marine and Freshwater Research Institute, Iceland","active":true,"usgs":false}],"preferred":false,"id":958188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trochta, John T.","contributorId":368964,"corporation":false,"usgs":false,"family":"Trochta","given":"John","middleInitial":"T.","affiliations":[{"id":87684,"text":"2Institute of Marine Research, Norway","active":true,"usgs":false}],"preferred":false,"id":958189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hannah M. Murphy, Hannah M.","contributorId":368965,"corporation":false,"usgs":false,"family":"Hannah M. 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In 2015, the Bureau of Land Management (BLM) temporarily approved the use of polymer-based dust palliatives during the construction and operation of a solar energy facility and, in 2019, on a mining access road in Clark County, Nevada. The areas treated with palliative are habitat to the desert tortoise. The desert tortoise consumes water opportunistically from puddles, saturated soils, or by the collection of precipitation on their carapaces. Since little is known about the toxicity of polymeric substances to the desert tortoise, the BLM is concerned with the exposure of the desert tortoise to palliative in stormwater runoff. The BLM collaborated with the US Geological Survey (USGS) to evaluate the transport of butyl acrylate vinyl acetate (BA-VA), the copolymer ingredient in the dust palliatives applied in the study, away from areas of application. BA-VA concentrations were measured in soils treated with palliative up to 90 days post-treatment, after which the copolymer became undetectable (< 0.55 mg/g). BA-VA concentrations in all stormwater samples within and outside treated areas were consistently below detection (< 0.20 mg/mL). Although stormwater and treated soils eroded from the solar facility application area were found to have BA-VA concentrations below detection (< 0.55 mg/g), it is likely that some BA-VA (parent or degradation product) was transported with suspended material. It is also likely that the amount of BA-VA transported away from areas of application was a small fraction of that applied.
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In this study, we investigate mechanisms that determine residual sediment fluxes using continuous measurements of bay-marsh sediment exchange conducted in a tidal creek spanning 13 months (753 tidal cycles) in an intertidal marsh recently subsidized with sediment via thin-layer placement. The maximum water level in each tidal cycle varied over seasonal and fortnightly timescales and was driven by a combination of the seasonal cycle in mean sea level (maximum in September, minimum in January) and the fortnightly spring-neap cycle. Residual water fluxes tended to be ebb-directed during overbank tides, possibly due to water crossing creekshed boundaries in the intertidal zone when water levels were sufficiently high. Sediment concentrations on the ebb of overbank tides exceeded those of their corresponding floods, but only for tidal cycles in which water temperatures exceeded 14°C. The interaction of these dynamics resulted in over 90% of the net sediment export from the creek occurring during overbank tides during warmer months—conditions met in 30% of the observed tidal cycles. These findings exemplify the importance of accounting for seasonality in sediment fluxes when assessing sediment budgets of salt marshes and illustrate how sediment budgets assessed with shorter duration datasets may exhibit seasonal bias. Additionally, they suggest that sediment retention for thin-layer sediment placement projects may be high over the course of the first year after sediment subsidies are deployed.
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