The Philipsburg mining district is a Mo-Cu porphyry system with associated Cordilleran polymetallic veins. Geochronology was employed to date the porphyry (~66 Ma, U/Pb in zircon) and molybdenite mineralization from the veins (~76 Ma, Re-Os). Age results suggest that the two-mineralization events model proposed by Lund et al. (2018) for the Butte district can be applied to the Philipsburg deposit. Furthermore, common fertility indicators from zircon trace elements were analyzed with variable success to characterize the existing Mo-Cu mineralization of the Philipsburg porphyry. This raises concerns about the benefits of this method and/or the importance of sampling, which could impact exploration for similar porphyry deposits.
","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits (SGA)","usgsCitation":"Beaucamp, C.M., Gammons, C.H., Thompson, J.M., and Stein, H.J., 2025, Ages and trace element fertility of porphyry-related mineralization in the Philipsburg polymetallic district, Montana, with a comparison to Butte, 18th SGA Biennial Meeting, v. 2, Golden, CO, August 3-7, 2025, p. 356-359.","productDescription":"4 p.","startPage":"356","endPage":"359","ipdsId":"IP-173924","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":499505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499504,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111,\n 47\n ],\n [\n -114.5,\n 47\n ],\n [\n -114.5,\n 45.25\n ],\n [\n -111,\n 45.25\n ],\n [\n -111,\n 47\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beaucamp, Celine M.E.","contributorId":353952,"corporation":false,"usgs":false,"family":"Beaucamp","given":"Celine","middleInitial":"M.E.","affiliations":[{"id":84532,"text":"Montana Technological University, Butte, MT, USA","active":true,"usgs":false}],"preferred":false,"id":934813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gammons, Chris","contributorId":140801,"corporation":false,"usgs":false,"family":"Gammons","given":"Chris","affiliations":[{"id":13574,"text":"Montana Tech of the University of Montana, Butte, MT","active":true,"usgs":false}],"preferred":false,"id":934814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":934815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stein, Holly J. 0000-0002-9709-7165","orcid":"https://orcid.org/0000-0002-9709-7165","contributorId":210107,"corporation":false,"usgs":false,"family":"Stein","given":"Holly","email":"","middleInitial":"J.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":true,"id":934816,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271485,"text":"70271485 - 2025 - Water temperature regimes and thermal drivers in semi-natural and flow-regulated rivers of the northern Great Plains","interactions":[],"lastModifiedDate":"2025-12-15T16:35:21.447687","indexId":"70271485","displayToPublicDate":"2025-09-15T09:39:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Water temperature regimes and thermal drivers in semi-natural and flow-regulated rivers of the northern Great Plains","docAbstract":"Rivers of the northern Great Plains have lacked long-term, continuous water temperature assessments, and there is limited information on thermal regimes of these systems and factors driving water temperature. We collected and assembled 2001–2022 water temperature data from 18 sites on four reaches of three rivers that differ in anthropogenic impacts: semi-natural Yellowstone River (YR), flow-impacted Milk River (MK), 351-km of the Missouri River affected by hypolimnetic releases from Fort Peck Dam (FPD), and the semi-natural Missouri River (MR3093) upstream from FPD. Objectives were to: (1) compare May–September mean daily water temperature (Tw), day of year of maximum water temperature (Tmaxdoy), and maximum water temperature (Twmax) among reaches, (2) evaluate air temperature (Ta), river discharge (Qw), and dam-release water temperature (Twdam) as Tw drivers, and (3) model longitudinal recovery of Tw downstream from FPD. Mean Tw and Twmax were greatest at the YR, MR3093 and MK sites, and significantly less through 291-km downstream from FPD. Tmaxdoy at initial sites downstream from FPD was delayed 43–69 days relative to the semi-natural reach upstream from FPD. Ta was the primary correlate of Tw for the semi-natural sites; whereas, Twdam and Ta varied inversely as primary drivers for sites downstream from FPD. Thermal recovery from hypolimnetic releases was incomplete 291-km downstream from FPD and warming persisted 351-km downstream. Results quantify the varied water temperature regimes of rivers in the northern Great Plains and improve understanding of controls affecting Tw among reaches. Water temperature attributes of semi-natural reaches could be used as restoration targets for 300-km of Missouri River presently impacted by hypolimnetic releases.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.70040","usgsCitation":"Braaten, P., Ritter, T.D., Haddix, T.M., Fuller, D.B., Hunziker, J.R., and Hargrave, J.G., 2025, Water temperature regimes and thermal drivers in semi-natural and flow-regulated rivers of the northern Great Plains: River Research and Applications, v. 41, no. 10, p. 2073-2091, https://doi.org/10.1002/rra.70040.","productDescription":"19 p.","startPage":"2073","endPage":"2091","ipdsId":"IP-173819","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":495744,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.70040","text":"Publisher Index Page"},{"id":495708,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.74009289929737,\n 48.87888526247494\n ],\n [\n -109.74009289929737,\n 46.45771203249336\n ],\n [\n -103.34512548963949,\n 46.45771203249336\n ],\n [\n -103.34512548963949,\n 48.87888526247494\n ],\n [\n -109.74009289929737,\n 48.87888526247494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Braaten, Patrick 0000-0003-3362-420X pbraaten@usgs.gov","orcid":"https://orcid.org/0000-0003-3362-420X","contributorId":152682,"corporation":false,"usgs":true,"family":"Braaten","given":"Patrick","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":948921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritter, T. 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To explore this possibility, we developed an ML-based workflow for hyperspectral imaging of river bathymetry using an ensemble of regression trees (HIRBERT). This approach involves using paired observations of depth and reflectance to select wavelength bands as predictors and then train a depth retrieval model; applying the model to the image yields a spatially continuous bathymetric map. We used data from five rivers with diverse morphologies and optical characteristics to assess whether HIRBERT can (1) provide more accurate depth estimates than a band ratio-based algorithm and (2) extend the range of depths detectable via remote sensing. Relative to single band combinations identified via optimal band ratio analysis (OBRA), regression tree ensembles improved depth retrieval performance, with observed versus predicted (OP) regression R2 values increasing for all five sites. Similarly, HIRBERT provided more reliable depth estimates than OBRA over the full range of depths present along each river. These results suggest that by incorporating additional spectral information from multiple wavelength bands, ML could enhance bathymetric mapping across a range of river environments. In addition, we show how graphical tools can facilitate interpretation of ML-based depth retrieval models and yield insight regarding relationships between depth and reflectance. The HIRBERT workflow is packaged in free, standalone software developed to support applications in river research and management. Although ML can enhance remote sensing of river bathymetry, the limitations of this approach must also be acknowledged: Field measurements of water depth are required to train a depth retrieval model and the resulting model should only be applied to the image from which the training data were derived. The inherently image-specific nature of this approach implies that developing generalized regression tree ensembles that could be applied at larger scales would require additional research.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.70155","usgsCitation":"Legleiter, C.J., Kinzel, P.J., Overstreet, B., and Harrison, L.R., 2025, Hyperspectral imaging of river bathymetry using an ensemble of regression trees: Earth Surface Processes and Landforms, v. 50, no. 12, e70155, 20 p., https://doi.org/10.1002/esp.70155.","productDescription":"e70155, 20 p.","ipdsId":"IP-176358","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":495594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nebraska, Oregon, Wyoming","otherGeospatial":"Deschutes River, Kootenai River, Niobrara River, Sacramento River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -126.50208043183841,\n 49\n ],\n [\n -126.50208043183841,\n 38.571428742902185\n ],\n [\n -99.8528658799654,\n 38.571428742902185\n ],\n [\n -99.8528658799654,\n 49\n ],\n [\n -126.50208043183841,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":948790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":948791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overstreet, Brandon 0000-0001-7845-6671 boverstreet@usgs.gov","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":169201,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"boverstreet@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrison, Lee R. 0000-0002-5219-9280","orcid":"https://orcid.org/0000-0002-5219-9280","contributorId":361416,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","middleInitial":"R.","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":948793,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271695,"text":"70271695 - 2025 - A soil velocity model for improved ground motion simulations in the U. S. Pacific Northwest","interactions":[],"lastModifiedDate":"2025-09-19T15:07:45.204834","indexId":"70271695","displayToPublicDate":"2025-09-15T07:53:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17454,"text":"Seismica","active":true,"publicationSubtype":{"id":10}},"title":"A soil velocity model for improved ground motion simulations in the U. S. Pacific Northwest","docAbstract":"Near-surface seismic velocity structure may significantly impact the intensity, duration, and frequency content of ground shaking during an earthquake. In this study, we compile 649 shear wave velocity (Vs) profiles throughout the U.S. Pacific Northwest and southern British Columbia (PNW) and use these measured profiles to develop a representative soil velocity model for four major Holocene soil provinces: Puget Lowlands, Willamette Valley, fill and alluvium, and `other' soils. The resulting soil velocity model shows good agreement to measured data for a wide range of site conditions, with variability between different geologic domains reflecting fundamental differences in depositional environments. We then show that using this regional soil velocity model in simulations of the 2001 M6.8 Nisqually, Washington earthquake improves the fit to observed high-frequency (≥ 0.5 Hz) ground motions in the Puget Sound region compared to simulations that do not incorporate shallow (≤ 200 m) seismic velocity structure. Overall, this work shows that incorporating localized soil velocity profiles into seismic velocity models is important for accurately estimating high-frequency ground motion and regional seismic hazard in earthquake simulations. Future earthquake simulations and hazard studies in the PNW could incorporate these soil velocity profiles to capture the region's distinct site response characteristics.
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Pacific Northwest: Seismica, v. 4, no. 2, 16 p., https://doi.org/10.26443/seismica.v4i2.1672.","productDescription":"16 p.","ipdsId":"IP-177573","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":496140,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.26443/seismica.v4i2.1672","text":"Publisher Index Page"},{"id":495803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.85877339027735,\n 49.01554453682621\n ],\n [\n -123.85877339027735,\n 47.33372471262203\n ],\n [\n -121.59818867979942,\n 47.33372471262203\n ],\n [\n -121.59818867979942,\n 49.01554453682621\n ],\n [\n -123.85877339027735,\n 49.01554453682621\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":949044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":949045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, Ian P. 0000-0003-2622-2691","orcid":"https://orcid.org/0000-0003-2622-2691","contributorId":293630,"corporation":false,"usgs":true,"family":"Stone","given":"Ian","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":949046,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271448,"text":"70271448 - 2025 - Decision support tools for brown pelican management in the northern Gulf of America (Gulf of Mexico)","interactions":[],"lastModifiedDate":"2025-11-21T22:11:02.518963","indexId":"70271448","displayToPublicDate":"2025-09-15T07:45:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Decision support tools for brown pelican management in the northern Gulf of America (Gulf of Mexico)","docAbstract":"Management plans with clear priorities can help to achieve brown pelican Pelecanus occidentalis conservation objectives in the northern Gulf of America (Gulf of Mexico). Efforts to establish clear priorities can be hindered by information gaps, especially those related to the uncertainty associated with changing conditions that influence brown pelican populations. We addressed these gaps by creating a model that uses island-specific conditions (e.g., geomorphology; predator-related conditions; brown pelican terrestrial nesting, roosting, and loafing habitats) to predict the nest count as a proxy for breeding pairs on the island. We used the model and 2000–2015 brown pelican nest count data to estimate if breeding pair targets that we identified or estimated for 10 U.S Fish and Wildlife Service Gulf Coast Biological Planning Units were met while accounting for uncertainty. Our results indicate that breeding pair targets were met in 7 of the 10 units by existing conditions. Our confidence in judging nest deficits tended to decrease from west to east because the model over-predicted total nests in the east Gulf Coast. Using an island from our data, we show how the model could be used to quantify the uncertainty of nest count outcomes under simulated changes in island conditions. The model indicated that the island's existing conditions most probably result in nests (probability = 0.51) and that increasing the area of nesting habitat (shrubs) could increase the probability of nests from 49% to 70%. Increasing shrub habitat in the model also increased nest count uncertainty by 60%, but this was due to a greater probability of larger nest counts. Our model suggests that nest count uncertainty could be reduced by improving data on island size, shrub area, and predator presence, depending on the unit and how isolated the island is from the mainland. These tools could help managers understand and incorporate the uncertainty associated with creating island conditions that are intended to help achieve brown pelican conservation objectives.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70103","usgsCitation":"Cronin, J.P., Tirpak, B., Dale, L.L., Robenski, V.L., Tirpak, J.M., Wilson, B.C., Vermillion, W.G., and Schoolmaster, D.R., 2025, Decision support tools for brown pelican management in the northern Gulf of America (Gulf of Mexico): Journal of Wildlife Management, v. 89, no. 8, e70103, 20 p., https://doi.org/10.1002/jwmg.70103.","productDescription":"e70103, 20 p.","ipdsId":"IP-140380","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":495598,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.5084812535037,\n 29.23655829920672\n ],\n [\n -97.80290228785537,\n 25.370449130055917\n ],\n [\n -80.69650208536123,\n 24.779624492928477\n ],\n [\n -83.47993279622662,\n 30.702187900532124\n ],\n [\n -94.73880975756701,\n 30.697298309312025\n ],\n [\n -97.5084812535037,\n 29.23655829920672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tirpak, Blair E. 0000-0002-2679-8378","orcid":"https://orcid.org/0000-0002-2679-8378","contributorId":343682,"corporation":false,"usgs":false,"family":"Tirpak","given":"Blair E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":948795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dale, Leah L. 0000-0002-3480-9954","orcid":"https://orcid.org/0000-0002-3480-9954","contributorId":243547,"corporation":false,"usgs":false,"family":"Dale","given":"Leah","middleInitial":"L.","affiliations":[{"id":48726,"text":"Cherokee Nations Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":948796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robenski, Virginia L.","contributorId":243548,"corporation":false,"usgs":false,"family":"Robenski","given":"Virginia","middleInitial":"L.","affiliations":[{"id":48726,"text":"Cherokee Nations Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":948797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tirpak, John M. 0000-0003-1937-9754","orcid":"https://orcid.org/0000-0003-1937-9754","contributorId":361417,"corporation":false,"usgs":false,"family":"Tirpak","given":"John","middleInitial":"M.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":948798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Barry C.","contributorId":361418,"corporation":false,"usgs":false,"family":"Wilson","given":"Barry","middleInitial":"C.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":948799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vermillion, William G.","contributorId":361419,"corporation":false,"usgs":false,"family":"Vermillion","given":"William","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":948800,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schoolmaster, Donald R. Jr. 0000-0003-0910-4458","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":221551,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","suffix":"Jr.","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948801,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273430,"text":"70273430 - 2025 - Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration","interactions":[],"lastModifiedDate":"2026-01-13T15:35:23.650384","indexId":"70273430","displayToPublicDate":"2025-09-13T08:09:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration","docAbstract":"Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with data and model complexity (i.e., model adequacy). We present a new framework to discriminate among candidate models prior to calibration that formalizes prior-to-calibration model adequacy into a metric to implicitly balance prior model output data coverage with model complexity represented by prior output (co)variance. The prior model adequacy metric “Mahalanobis distance deviation” quantifies the deviation of (a) the set of squared Mahalanobis distances of data from a prior model output distribution from (b) the set of squared Mahalanobis distances of data from their own distribution. A new data worth metric “discernment value” is also presented which quantifies the value of data for screening less-adequate models prior to calibration. Discernment value is calculated from the change in variance of a weighted average of prior model outputs from all candidate models due to less-adequate model outputs receiving lower weight. The framework is demonstrated using a one-dimensional groundwater flow model with eight possible configurations. A synthetic data network is used to test the framework. Results show the framework identifies the candidate models most similar to the true model used to create the synthetic data. Discernment values show variation in the value of different data types and locations for screening less-adequate models.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040323","usgsCitation":"Pleasants, M.S., Fienen, M., Essaid, H.I., Blomquist, J.D., Yang, J., and Ye, M., 2025, Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration: Water Resources Research, v. 61, no. 9, e2025WR040323, 28 p., https://doi.org/10.1029/2025WR040323.","productDescription":"e2025WR040323, 28 p.","ipdsId":"IP-173111","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":498695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040323","text":"Publisher Index Page"},{"id":498584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Pleasants, Mark Shannon 0000-0002-9864-5282","orcid":"https://orcid.org/0000-0002-9864-5282","contributorId":365071,"corporation":false,"usgs":true,"family":"Pleasants","given":"Mark","middleInitial":"Shannon","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":953659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":953661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, Jing","contributorId":192311,"corporation":false,"usgs":false,"family":"Yang","given":"Jing","affiliations":[],"preferred":false,"id":953663,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ye, Ming","contributorId":194184,"corporation":false,"usgs":false,"family":"Ye","given":"Ming","email":"","affiliations":[],"preferred":false,"id":953664,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271352,"text":"cir1559 - 2025 - Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps","interactions":[],"lastModifiedDate":"2026-02-03T15:24:37.637334","indexId":"cir1559","displayToPublicDate":"2025-09-12T11:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1559","displayTitle":"Summary of Selenium in the Lower Gunnison River Basin, Colorado—Information and Data Gaps","title":"Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps","docAbstract":"The Cretaceous Mancos Shale is a geologic source of selenium in the lower Gunnison River Basin. Natural weathering processes and human activity mobilize selenium from the Mancos Shale and derived materials, and surface water, groundwater, and sediment all affect the transport of selenium from source areas to receiving streams and biota. Selenium accumulates through the aquatic food chain, and its toxic effects can result in invertebrate mortality and mortality, decreased reproduction, and deformities to fish and birds. The Bureau of Reclamation, in cooperation with the State of Colorado and Gunnison River Basin water users, is implementing a Selenium Management Program to reduce selenium concentrations in the lower Gunnison River Basin of Colorado. Goals of the Selenium Management Program are to (1) achieve compliance with the State of Colorado chronic aquatic-life standard for dissolved selenium (4.6 micrograms per liter) in the Gunnison River near Grand Junction, Colorado; (2) sufficiently improve water-quality conditions to assist in the recovery of endangered species in the Gunnison and Colorado Rivers by reducing selenium concentrations; and (3) support continued water uses in the basin.
Many previous studies have contributed to the understanding of selenium in the environment; however, monitoring and research data gaps exist in the lower Gunnison River Basin. The purpose of this report is to summarize information regarding selenium in the lower Gunnison River Basin and describe strategies for scientific research and monitoring to potentially improve understanding of selenium sources; processes affecting the mobilization, transport, and fate of selenium; and the effects of selenium-mitigation projects in the lower Gunnison River Basin. Monitoring and research data gaps discussed in this report include geologic mapping and geochemical source characterization, long-term and ongoing monitoring of the surface-water and groundwater networks, developing and refining statistical models, characterizing selenium on suspended sediment, modeling selenium in the food web, evaluating best management practices, and more.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1559","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board, the Bureau of Reclamation, the Colorado River Water Conservation District, the U.S. Fish and Wildlife Service, the Bureau of Land Management, and the Natural Resources Conservation Service","usgsCitation":"Gidley, R.G., Leib, K.J., and Williams, C.A., 2025, Summary of selenium in the lower Gunnison River Basin, Colorado—Information and data gaps: U.S. Geological Survey Circular 1559, 44 p., https://doi.org/10.3133/cir1559.","productDescription":"vi, 44 p.","onlineOnly":"Y","ipdsId":"IP-139023","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":495449,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1559/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1559"},{"id":496026,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118831.htm","linkFileType":{"id":5,"text":"html"}},{"id":495259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1559/cir1559.pdf","text":"Report","size":"36.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1559"},{"id":495258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1559/coverthb.jpg"},{"id":495444,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1559/cir1559.xml"},{"id":495443,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1559/images"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109,\n 39.5\n ],\n [\n -109,\n 37.5\n ],\n [\n -106.5,\n 37.5\n ],\n [\n -106.5,\n 39.5\n ],\n [\n -109,\n 39.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
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Box 25046, Mail Stop 415
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A mineral systems approach to mineral exploration provides a comprehensive framework for understanding ore deposit formation by examining the geodynamic, magmatic, hydrothermal, and sedimentary processes responsible for mineralization, alteration, and remobilization of economic mineral deposits. Temporal and thermal constraints on ore genesis are crucial for refining mineral system models and guiding predictive exploration strategies. Geochronology and thermochronology offer invaluable insights into the timing and thermal evolution of ore-forming processes, whereas isotopic analyses provide critical information on the source and geochemical history of ore-forming fluids. Combining these methodologies have proven highly effective for mineral exploration in regions like Australia, however, their combined application has been limited in the United States.
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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":947583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":947584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":947585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engle, Zachary T. 0000-0002-6412-7727","orcid":"https://orcid.org/0000-0002-6412-7727","contributorId":300814,"corporation":false,"usgs":true,"family":"Engle","given":"Zachary","email":"","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":947586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Anna T.","contributorId":360754,"corporation":false,"usgs":false,"family":"Miller","given":"Anna","middleInitial":"T.","affiliations":[{"id":40487,"text":"USGS (former employee)","active":true,"usgs":false}],"preferred":false,"id":947587,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271358,"text":"70271358 - 2025 - Origin of the high Pd/Pt ratio of the J-M Reef, Stillwater Complex Montana USA","interactions":[],"lastModifiedDate":"2025-09-17T15:50:42.913471","indexId":"70271358","displayToPublicDate":"2025-09-12T10:47:37","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Origin of the high Pd/Pt ratio of the J-M Reef, Stillwater Complex Montana USA","docAbstract":"The J-M Reef of the Stillwater Complex exhibits a high and consistent Pd/Pt ratio (~3.8). This ratio results from the equilibration of an immiscible sulfide liquid with a relatively high Pd/Pt silicate melt rather than an unusually Pd- and Pt-enriched parental melt. Numerical modeling suggests that the original silicate melt contained typical mantle-derived concentrations of Pd and Pt (~10–20 ppb Pd/Pt ~1). The partitioning of Pt and Pd between sulfide liquid and silicate melt alone cannot explain the consistently high Pd/Pt ratio across variable melt-to-sulfide mass ratios (R factors). Instead Pt-depletion caused by the early fractionation of Pt-alloy from S-undersaturated silicate magma likely established the high Pd/Pt signature. High Pd/Pt ratios can form through batch equilibration of sulfide liquid with silicate melt if partition coefficients are extremely high (>10⁶). Alternatively Pd enrichment may result from sulfide upgrading within the resident footwall mush under smaller partition coefficients (10⁴–10⁶) in this model the instantaneous R factors remain low (R ≈ 100–700). This limits the impact of Pt and Pd partitioning on sulfide composition and helps explain the Pd-enriched character of the J-M Reef.
","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Jenkins, M., and Smith, W.D., 2025, Origin of the high Pd/Pt ratio of the J-M Reef, Stillwater Complex Montana USA, 18th SGA Biennial Meeting, v. II, Golden, CO, August 3-7, 2025, p. 603-606.","productDescription":"4 p.","startPage":"603","endPage":"606","ipdsId":"IP-175537","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495640,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","otherGeospatial":"J-M Reef Stillwater Complex","volume":"II","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, William D.","contributorId":361061,"corporation":false,"usgs":false,"family":"Smith","given":"William","middleInitial":"D.","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":948211,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270168,"text":"70270168 - 2025 - Synergy between geology and geophysics in graphite mineral resource assessment","interactions":[],"lastModifiedDate":"2025-09-19T15:12:58.12429","indexId":"70270168","displayToPublicDate":"2025-09-12T10:05:31","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Synergy between geology and geophysics in graphite mineral resource assessment","docAbstract":"Graphite is designated as a critical mineral by the U.S. Government due to its essential role in modern technology and its vulnerability to supply chain disruption. To evaluate domestic graphite resources, the U.S. Geological Survey (USGS) conducted two airborne electromagnetic (AEM) surveys as part of the Earth Mapping Resources Initiative (Earth MRI) over prospective areas in the southern Appalachians of Alabama and the Seward Peninsula of Alaska. These surveys aimed to refine areas of interest by revealing subsurface electrical resistivity patterns indicative of graphite-bearing rocks. The results of the AEM surveys were integrated with existing geological knowledge and supplemented by field observations to assess the likelihood of undiscovered resources in these regions. This multidisciplinary approach combined geophysical techniques with traditional geological methods, enhancing the understanding of graphite potential in areas that may have been previously overlooked. The findings from this initiative are expected to contribute significantly to the ongoing efforts to secure a reliable domestic supply of graphite, thereby reducing import reliance and supporting national interests in mineral resource management.","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Macqueen, P.G., Case, G.N., Bedrosian, P.A., Hammarstrom, J.M., Karl, S., Lederer, G.W., Bollen, E.M., Whitmore, J., VanDervoort, D., Emond, A.M., Fusso, L., Brown, P.J., Walsh, G., Labay, K.A., Stokes, M., and Stewart, A., 2025, Synergy between geology and geophysics in graphite mineral resource assessment, 18th SGA Biennial Meeting, v. 3, Golden, CO, August 3-7, 2025, p. 1235-1238.","productDescription":"4 p.","startPage":"1235","endPage":"1238","ipdsId":"IP-176049","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495804,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings","linkFileType":{"id":5,"text":"html"}}],"volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Macqueen, Patricia Grace 0000-0001-7692-3416","orcid":"https://orcid.org/0000-0001-7692-3416","contributorId":337137,"corporation":false,"usgs":true,"family":"Macqueen","given":"Patricia","email":"","middleInitial":"Grace","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":945623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Case, George N.D. 0000-0001-9826-5661 gcase@usgs.gov","orcid":"https://orcid.org/0000-0001-9826-5661","contributorId":224941,"corporation":false,"usgs":true,"family":"Case","given":"George","email":"gcase@usgs.gov","middleInitial":"N.D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":945624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":945625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":945626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karl, Susan M. 0000-0003-1559-7826","orcid":"https://orcid.org/0000-0003-1559-7826","contributorId":225408,"corporation":false,"usgs":true,"family":"Karl","given":"Susan M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":945627,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945628,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bollen, Elizabeth M.","contributorId":304625,"corporation":false,"usgs":false,"family":"Bollen","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":945629,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitmore, John 0000-0003-2444-9825","orcid":"https://orcid.org/0000-0003-2444-9825","contributorId":359482,"corporation":false,"usgs":false,"family":"Whitmore","given":"John","affiliations":[{"id":13327,"text":"Geological Survey of Alabama","active":true,"usgs":false}],"preferred":false,"id":945630,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"VanDervoort, Dane 0000-0003-3376-005X","orcid":"https://orcid.org/0000-0003-3376-005X","contributorId":359483,"corporation":false,"usgs":false,"family":"VanDervoort","given":"Dane","affiliations":[{"id":13327,"text":"Geological Survey of Alabama","active":true,"usgs":false}],"preferred":false,"id":945631,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Emond, Abraham M.","contributorId":216313,"corporation":false,"usgs":false,"family":"Emond","given":"Abraham","email":"","middleInitial":"M.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":945632,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fusso, Logan 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0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":355444,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":945635,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Labay, Keith A. 0000-0002-6763-3190 klabay@usgs.gov","orcid":"https://orcid.org/0000-0002-6763-3190","contributorId":217714,"corporation":false,"usgs":true,"family":"Labay","given":"Keith","email":"klabay@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":945636,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stokes, Martha 0000-0002-2838-8380","orcid":"https://orcid.org/0000-0002-2838-8380","contributorId":269608,"corporation":false,"usgs":true,"family":"Stokes","given":"Martha","email":"","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":945637,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Stewart, Andrew Arnold 0000-0002-3948-3148","orcid":"https://orcid.org/0000-0002-3948-3148","contributorId":359485,"corporation":false,"usgs":true,"family":"Stewart","given":"Andrew Arnold","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":945638,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70271476,"text":"70271476 - 2025 - Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA","interactions":[],"lastModifiedDate":"2025-09-17T14:57:28.463629","indexId":"70271476","displayToPublicDate":"2025-09-12T09:49:07","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA","docAbstract":"Recent mapping of the underexplored Clementine prospect in southwestern Montana has revealed evidence of hydrothermal alteration and mineralized breccia vein gossan interpreted to represent the upper expression of a Cretaceous, sediment-hosted copper porphyry system. The prospect is at the nexus of several Cretaceous granites, including the pre-mineralization Butte Granite and Big Hole Canyon plutons and local pre- to post-mineralization granite intrusions. Here, 3D magnetic inversions and stable isotope data are used to evaluate the spatial and genetic relationship of mineralization and Cretaceous magmatism. Magnetic inversions reveal a zone of high magnetic susceptibility beneath the prospect that is related to an exposure of unaltered, likely post-mineralization granite. The granite appears to connect to the Big Hole Canyon pluton at depth, suggesting it is a late-stage differentiate of the cooling, pre-mineralization pluton that may have been one of several potential heat sources for the mineral system at Clementine. This is supported by carbon isotope values of graphite that indicate organic material in shale of the Cretaceous Kootenai Formation was subject to metamorphism. Preliminary light hydrogen isotope values of actinolite hydrothermal orbs suggest formation following magmatic outgassing during thermal advection from an underlying intrusion.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 18th Biennial SGA Meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Magnin, B.P., McIntosh, J.A., and Brimhall, G.H., 2025, Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA, in Proceedings of the 18th Biennial SGA Meeting, v. 2, p. 471-474.","productDescription":"4 p.","startPage":"471","endPage":"474","ipdsId":"IP-175774","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495608,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"}],"country":"United States","state":"Montana","otherGeospatial":"Clementine prospect","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113,\n 45.9167\n ],\n [\n -113,\n 45.5\n ],\n [\n -112.5,\n 45.5\n ],\n [\n -112.5,\n 45.9167\n ],\n [\n -113,\n 45.9167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Magnin, Benjamin Patrick 0000-0001-9951-4404","orcid":"https://orcid.org/0000-0001-9951-4404","contributorId":300679,"corporation":false,"usgs":true,"family":"Magnin","given":"Benjamin","email":"","middleInitial":"Patrick","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":948883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brimhall, George H.","contributorId":361483,"corporation":false,"usgs":false,"family":"Brimhall","given":"George","middleInitial":"H.","affiliations":[{"id":86298,"text":"Clementine Exploration LLC","active":true,"usgs":false}],"preferred":false,"id":948884,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272024,"text":"70272024 - 2025 - Complex sound scattering layer and water-column dynamics over a mesophotic coral ecosystem: Southwest Puerto Rico, U.S.A.","interactions":[],"lastModifiedDate":"2025-12-01T16:47:18.117009","indexId":"70272024","displayToPublicDate":"2025-09-12T09:41:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Complex sound scattering layer and water-column dynamics over a mesophotic coral ecosystem: Southwest Puerto Rico, U.S.A.","docAbstract":"A nearly 5-month record of high-resolution temperature and acoustic backscatter profiles from the upper insular slope off southwest Puerto Rico reveals complex sound scattering layer (SSL) dynamics over a mesophotic coral ecosystem (MCE). The SSLs exhibited both diel and reverse diel vertical migration, thin layer (< 5 m) and multiple layer formations, depth modulation due to internal waves, and vertical layering in the absence of water column stratification. The long-term observations also capture SSL and water column dynamics across changing seasons and two category five hurricanes, Irma and María. The SSLs, likely comprosed of zooplankton, represent an important food source for both the sessile (e.g., corals and sponges) and mobile (e.g., fish) MCE taxa, and their effective vertical mobility underscores their importance to trophic connectivity between the upper and lower slope MCEs, as well as the shelf. Our results also underscore the challenges in adequately resolving zooplankton aggregations using conventional sampling techniques.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00338-025-02747-1","usgsCitation":"Cheriton, O.M., Storlazzi, C.D., Sherman, C.E., Rosenberger, K.J., and Schizas, N.V., 2025, Complex sound scattering layer and water-column dynamics over a mesophotic coral ecosystem: Southwest Puerto Rico, U.S.A.: Coral Reefs, v. 44, p. 2147-2154, https://doi.org/10.1007/s00338-025-02747-1.","productDescription":"8 p.","startPage":"2147","endPage":"2154","ipdsId":"IP-172712","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496424,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-025-02747-1","text":"Publisher Index Page"},{"id":496409,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.26443611756584,\n 18.08156998737445\n ],\n [\n -67.26443611756584,\n 17.906141767871972\n ],\n [\n -66.87248059498367,\n 17.906141767871972\n ],\n [\n -66.87248059498367,\n 18.08156998737445\n ],\n [\n -67.26443611756584,\n 18.08156998737445\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2025-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherman, Clark E. 0000-0003-0758-7900","orcid":"https://orcid.org/0000-0003-0758-7900","contributorId":259180,"corporation":false,"usgs":false,"family":"Sherman","given":"Clark","middleInitial":"E.","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":949757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":949758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schizas, Nikolaos V.","contributorId":362022,"corporation":false,"usgs":false,"family":"Schizas","given":"Nikolaos","middleInitial":"V.","affiliations":[],"preferred":false,"id":949829,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271470,"text":"70271470 - 2025 - RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models","interactions":[],"lastModifiedDate":"2025-09-17T14:16:15.20186","indexId":"70271470","displayToPublicDate":"2025-09-12T09:10:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models","docAbstract":"Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments.
","language":"English","publisher":"MDPI","doi":"10.3390/rs17183165","usgsCitation":"Cheang, C.W., Byrd, K., Enwright, N., Buscombe, D.D., Sherwood, C.R., and Gesch, D.B., 2025, RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models: Remote Sensing, v. 17, no. 18, 3165, 23 p., https://doi.org/10.3390/rs17183165.","productDescription":"3165, 23 p.","ipdsId":"IP-181890","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":495740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17183165","text":"Publisher Index Page"},{"id":495620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Louisiana, North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.31465945206622,\n 36.559174434474485\n ],\n [\n -77.88584228510663,\n 36.559174434474485\n ],\n [\n -77.88584228510663,\n 33.91023238346908\n ],\n [\n -75.31465945206622,\n 33.91023238346908\n ],\n [\n -75.31465945206622,\n 36.559174434474485\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.10192326737439,\n 30.45731991199513\n ],\n [\n -87.10192326737439,\n 29.369208398587546\n ],\n [\n -84.13516902365296,\n 29.369208398587546\n ],\n [\n -84.13516902365296,\n 30.45731991199513\n ],\n [\n -87.10192326737439,\n 30.45731991199513\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.1992249314043,\n 29.913844234939134\n ],\n [\n -91.59031694232786,\n 29.08029462857938\n ],\n [\n -88.91511480110469,\n 28.968839824460204\n ],\n [\n -88.91511480110469,\n 30.147672625947735\n ],\n [\n -90.0571698662545,\n 30.030758430443434\n ],\n [\n -91.1992249314043,\n 29.913844234939134\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"18","noUsgsAuthors":false,"publicationDate":"2025-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheang, Chak Wa 0009-0007-5254-2863","orcid":"https://orcid.org/0009-0007-5254-2863","contributorId":361478,"corporation":false,"usgs":true,"family":"Cheang","given":"Chak","middleInitial":"Wa","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":948875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":172431,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":948876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":214839,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":948878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":948879,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gesch, Dean B. 0000-0002-8992-4933","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":361479,"corporation":false,"usgs":false,"family":"Gesch","given":"Dean","middleInitial":"B.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":948880,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272040,"text":"70272040 - 2025 - GIScience in the era of Artificial Intelligence: A research agenda towards Autonomous GIS","interactions":[],"lastModifiedDate":"2025-11-13T16:08:13.781827","indexId":"70272040","displayToPublicDate":"2025-09-12T08:59:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5089,"text":"Annals of GIS","active":true,"publicationSubtype":{"id":10}},"title":"GIScience in the era of Artificial Intelligence: A research agenda towards Autonomous GIS","docAbstract":"The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/19475683.2025.2552161","usgsCitation":"Li, Z., Ning, H., Gao, S., Janowicz, K., Li, W., Arundel, S., Yang, C., Bhaduri, B., Wang, S., Zhu, A., Gahegan, M., Shekhar, S., Ye, X., McKenzie, G., Cervone, G., and Hodgson, M., 2025, GIScience in the era of Artificial Intelligence: A research agenda towards Autonomous GIS: Annals of GIS, 36 p., https://doi.org/10.1080/19475683.2025.2552161.","productDescription":"36 p.","ipdsId":"IP-177135","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":496421,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19475683.2025.2552161","text":"Publisher Index Page"},{"id":496402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Zhenlong 0000-0002-8938-5466","orcid":"https://orcid.org/0000-0002-8938-5466","contributorId":362008,"corporation":false,"usgs":false,"family":"Li","given":"Zhenlong","affiliations":[{"id":86418,"text":"The Pennsylvania State Univesrity","active":true,"usgs":false}],"preferred":false,"id":949811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ning, Huan 0000-0003-3698-3240","orcid":"https://orcid.org/0000-0003-3698-3240","contributorId":362009,"corporation":false,"usgs":false,"family":"Ning","given":"Huan","affiliations":[{"id":86418,"text":"The Pennsylvania State Univesrity","active":true,"usgs":false}],"preferred":false,"id":949812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gao, Song","contributorId":346312,"corporation":false,"usgs":false,"family":"Gao","given":"Song","email":"","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":949813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Janowicz, Krzysztof","contributorId":149671,"corporation":false,"usgs":false,"family":"Janowicz","given":"Krzysztof","email":"","affiliations":[],"preferred":false,"id":949814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":949815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":949816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yang, Chaowei 0000-0001-7768-4066","orcid":"https://orcid.org/0000-0001-7768-4066","contributorId":362010,"corporation":false,"usgs":false,"family":"Yang","given":"Chaowei","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":949817,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bhaduri, Budhendra 0000-0003-1555-1377","orcid":"https://orcid.org/0000-0003-1555-1377","contributorId":362011,"corporation":false,"usgs":false,"family":"Bhaduri","given":"Budhendra","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":949818,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wang, Shaoweng","contributorId":362012,"corporation":false,"usgs":false,"family":"Wang","given":"Shaoweng","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":949819,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhu, A-Xing 0000-0002-5725-0460","orcid":"https://orcid.org/0000-0002-5725-0460","contributorId":362013,"corporation":false,"usgs":false,"family":"Zhu","given":"A-Xing","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":949820,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gahegan, Mark","contributorId":362014,"corporation":false,"usgs":false,"family":"Gahegan","given":"Mark","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":949821,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shekhar, Shashi","contributorId":362015,"corporation":false,"usgs":false,"family":"Shekhar","given":"Shashi","affiliations":[{"id":33108,"text":"University of Minnesota Twin Cities","active":true,"usgs":false}],"preferred":false,"id":949822,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ye, Xinyue 0000-0001-8838-9476","orcid":"https://orcid.org/0000-0001-8838-9476","contributorId":362016,"corporation":false,"usgs":false,"family":"Ye","given":"Xinyue","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":949823,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McKenzie, Grant 0000-0003-3247-2777","orcid":"https://orcid.org/0000-0003-3247-2777","contributorId":362018,"corporation":false,"usgs":false,"family":"McKenzie","given":"Grant","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":949825,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Cervone, Guido 0000-0002-6509-0735","orcid":"https://orcid.org/0000-0002-6509-0735","contributorId":362019,"corporation":false,"usgs":false,"family":"Cervone","given":"Guido","affiliations":[{"id":86418,"text":"The Pennsylvania State Univesrity","active":true,"usgs":false}],"preferred":false,"id":949826,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hodgson, Michael 0000-0002-1800-5833","orcid":"https://orcid.org/0000-0002-1800-5833","contributorId":362020,"corporation":false,"usgs":false,"family":"Hodgson","given":"Michael","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":949827,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70271911,"text":"70271911 - 2025 - Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake","interactions":[],"lastModifiedDate":"2025-09-24T15:13:40.752725","indexId":"70271911","displayToPublicDate":"2025-09-12T08:05:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake","docAbstract":"The challenges and the importance of preserving legacy instrumental records of earthquakes are now well-recognized (e.g., Richards & Hellweg, 2020, https://doi.org/10.1785/0220200053). Seismologists may not be aware of parallel challenges and opportunities with legacy macroseismic data for earthquakes in the United States. For much of the 20th century, macroseismic data were collected by a series of U.S. government agencies using a standard questionnaire distributed on postcards. Published summaries of postcards provide macroseismic data akin to modern Did You Feel It? questionnaire responses. In this paper we focus on the M 6.5 Fickle Hill, California earthquake, on 21 December 1954 (Hellweg et al., 2025) as a proof-of-concept, illustrating the potential of what we dub Did They Feel It? (DTFI) data to improve our understanding of significant 20th century U.S. earthquakes for which instrumental data are sparse. Legacy macroseismic data interpreted following modern conventions can potentially constrain traditional ShakeMaps at a level of detail and accuracy that in some respects rival maps for modern earthquakes. The updated ShakeMap for the 1954 Fickle Hill earthquake, also drawing from recently published media and first-person accounts, supports the location, depth, and stress drop value estimated from available instrumental data (Hellweg et al., 2025).
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025EA004437","usgsCitation":"Hough, S.E., Dengler, L., McPherson, R., Hagos, L., and Hellweg, M., 2025, Did they feel it? Legacy maroseismic data illuminates an engimatic 20th century earthquake: Earth and Space Science, v. 12, no. 9, e2025EA004437, 45 p., https://doi.org/10.1029/2025EA004437.","productDescription":"e2025EA004437, 45 p.","ipdsId":"IP-178554","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":496154,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025ea004437","text":"Publisher Index Page"},{"id":496011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.36941833393237,\n 41.366992125273725\n ],\n [\n -124.36941833393237,\n 39.97380581515134\n ],\n [\n -123.19324471908419,\n 39.97380581515134\n ],\n [\n -123.19324471908419,\n 41.366992125273725\n ],\n [\n -124.36941833393237,\n 41.366992125273725\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":949341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dengler, Lori","contributorId":197374,"corporation":false,"usgs":false,"family":"Dengler","given":"Lori","affiliations":[],"preferred":false,"id":949342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McPherson, Robert","contributorId":336975,"corporation":false,"usgs":false,"family":"McPherson","given":"Robert","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":949343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagos, Lijam","contributorId":300811,"corporation":false,"usgs":false,"family":"Hagos","given":"Lijam","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":949344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hellweg, Margaret","contributorId":360602,"corporation":false,"usgs":false,"family":"Hellweg","given":"Margaret","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":949345,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271754,"text":"70271754 - 2025 - Shear surface undulations modulate clayey gouge strength and contribute to divergent landslide acceleration","interactions":[],"lastModifiedDate":"2025-09-23T14:57:15.409496","indexId":"70271754","displayToPublicDate":"2025-09-12T07:51:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Shear surface undulations modulate clayey gouge strength and contribute to divergent landslide acceleration","docAbstract":"Deep-sea corals and sponges (DSCS) are signature taxa of deep-water habitats, but ecological mechanisms that drive their geographic distributions can be difficult to uncover due to the challenges of surveying deep-water ecosystems and limited oceanographic data. A comparison of species distribution models was made for three DSCS (Antipathes dendochristos, Plumarella longispina, and an unidentified sponge morphotype known as Porifera #2), two of which are associated with young-of-the-year and adult rockfish taxa (Sebastes spp.). Models were built using generalized additive models (GAMs) that accounted for spatial autocorrelation. These models were compared to Maxent models, a commonly used method. All models utilized bathymetrically derived variables (including depth, slope, and Bathymetric Position Index) and output from a coupled physical-biogeochemical ocean model (including current direction and magnitude, food abundance, and dissolved oxygen). Direction of benthic ocean currents played an important role in predictions, pointing to large-scale ecological processes that may determine presence of DSCS. GAMs outperformed Maxent models and predicted more ecologically interpretable patterns. Additionally we quantified the predicted amount of suitable habitat that is currently located within some protected areas of the Southern California Bight and show that many hot spots occur outside protected areas. Given the importance of DSCS for multiple demersal fish species of commercial or conservation concerns, this research provides valuable information that natural resource managers can use as a tool in the Southern California Bight.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2025.105546","usgsCitation":"Kreidler, N., Buchheister, A., Huff, D.D., Fiechter, J., Yoklavich, M., and Henderson, M., 2025, A comparison of deep-sea coral and sponge species distribution models and the impact of ocean currents in the Southern California Bight: Deep Sea Research Part II: Topical Studies in Oceanography, v. 224, 105546, 20 p., https://doi.org/10.1016/j.dsr2.2025.105546.","productDescription":"105546, 20 p.","ipdsId":"IP-160765","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern California Bight","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.77195451682024,\n 34.63450539301438\n ],\n [\n -120.71062295847764,\n 34.067353050853896\n ],\n [\n -116.95296762825086,\n 32.64962732243558\n ],\n [\n -117.36447279653606,\n 33.96407055399892\n ],\n [\n -120.77195451682024,\n 34.63450539301438\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"224","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kreidler, Nissa","contributorId":278592,"corporation":false,"usgs":false,"family":"Kreidler","given":"Nissa","email":"","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":952055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buchheister, Andre","contributorId":363827,"corporation":false,"usgs":false,"family":"Buchheister","given":"Andre","affiliations":[{"id":86743,"text":"California Polytechnic State University Humboldt","active":true,"usgs":false}],"preferred":false,"id":952056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huff, David D.","contributorId":363828,"corporation":false,"usgs":false,"family":"Huff","given":"David","middleInitial":"D.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":952057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fiechter, Jerome","contributorId":272532,"corporation":false,"usgs":false,"family":"Fiechter","given":"Jerome","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":952058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yoklavich, Mary","contributorId":363829,"corporation":false,"usgs":false,"family":"Yoklavich","given":"Mary","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":952059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":952060,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271433,"text":"70271433 - 2025 - Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals","interactions":[],"lastModifiedDate":"2025-12-01T16:34:29.87096","indexId":"70271433","displayToPublicDate":"2025-09-11T09:02:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals","docAbstract":"In today’s rapidly changing economic landscape, understanding market responsiveness to price changes and the factors influencing commodity prices has become increasingly relevant. Price elasticities serve as indicators of how variations in market conditions affect supply and demand, providing insights into the sensitivity of commodity markets to price fluctuations. This paper presents a comprehensive analysis of price elasticities of supply and demand for 74 non-fuel mineral commodities including precious metals, base metals, minor metals, and industrial minerals that are utilized across various industries. We employ various econometric techniques, including fixed effects models for panel data and two-stage dynamic ordinary least squares (2S-DOLS) alongside autoregressive distributed lag (ARDL) models for time series analysis, to derive robust estimates of price elasticities. Our findings reveal variability in elasticities among different commodities and indicate that all studied mineral commodities exhibit price inelastic supply and demand in the short run, which we define as one year for the purposes of our analysis, given that the data is all annual. This research provides original estimates of price responsiveness for a wide range of commodities that have not been previously addressed in the literature, thereby enhancing the understanding of market dynamics in the mineral sector. Given that price elasticities can be influenced by factors such as market structure, technological advancements, mining costs, and industry-specific demand drivers, we use variables that serve as proxies for these factors.
","language":"English","publisher":"Springer","doi":"10.1007/s13563-025-00537-3","usgsCitation":"Shojaeddini, E., Alonso, E., Nassar, N.T., Pineault, D., Allen, S.M., Brainard, J.L., McCaffrey, D.M., O'Brien, T.M., Padilla, A.J., and Ryter, J.W., 2025, Understanding market sensitivity: Estimation of supply and demand elasticities for non-fuel minerals: Mineral Economics, v. 38, p. 985-996, https://doi.org/10.1007/s13563-025-00537-3.","productDescription":"12 p.","startPage":"985","endPage":"996","ipdsId":"IP-180072","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":495732,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13563-025-00537-3","text":"Publisher Index Page"},{"id":495491,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2025-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Shojaeddini, Ensieh 0000-0001-9584-6399","orcid":"https://orcid.org/0000-0001-9584-6399","contributorId":346849,"corporation":false,"usgs":true,"family":"Shojaeddini","given":"Ensieh","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso, Elisa 0000-0002-0090-8284","orcid":"https://orcid.org/0000-0002-0090-8284","contributorId":223015,"corporation":false,"usgs":true,"family":"Alonso","given":"Elisa","email":"","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pineault, David 0009-0001-6801-4711","orcid":"https://orcid.org/0009-0001-6801-4711","contributorId":352217,"corporation":false,"usgs":true,"family":"Pineault","given":"David","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Sydney M. 0000-0001-6560-3548","orcid":"https://orcid.org/0000-0001-6560-3548","contributorId":359608,"corporation":false,"usgs":true,"family":"Allen","given":"Sydney","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brainard, Jamie L. 0000-0002-1712-0821","orcid":"https://orcid.org/0000-0002-1712-0821","contributorId":201465,"corporation":false,"usgs":true,"family":"Brainard","given":"Jamie","middleInitial":"L.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948748,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCaffrey, Dalton M. 0000-0002-2539-4865","orcid":"https://orcid.org/0000-0002-2539-4865","contributorId":298840,"corporation":false,"usgs":true,"family":"McCaffrey","given":"Dalton","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948749,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O'Brien, Timothy M. 0009-0007-7178-100X","orcid":"https://orcid.org/0009-0007-7178-100X","contributorId":361401,"corporation":false,"usgs":true,"family":"O'Brien","given":"Timothy","middleInitial":"M.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948750,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Padilla, Abraham J. 0000-0002-8371-533X","orcid":"https://orcid.org/0000-0002-8371-533X","contributorId":290608,"corporation":false,"usgs":true,"family":"Padilla","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948751,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ryter, John W. 0000-0002-0343-7553","orcid":"https://orcid.org/0000-0002-0343-7553","contributorId":345416,"corporation":false,"usgs":true,"family":"Ryter","given":"John","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":948752,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70273022,"text":"70273022 - 2025 - Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.","interactions":[],"lastModifiedDate":"2025-12-12T15:14:04.925076","indexId":"70273022","displayToPublicDate":"2025-09-11T08:08:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.","docAbstract":"Understanding habitat connectivity is critical for managing nonindigenous aquatic species (NAS) spread. Dams and watershed boundaries can be impassable to NAS during typical conditions but may become temporarily passable during flooding. The goal of our project was to develop an approach for identifying locations of aquatic connectivity at a fine spatial scale along watershed boundaries using readily available data. To develop this approach, we focused on the potential for range expansion of invasive fish in the United States via possible cross-boundary habitat connections. First, we developed an index using metrics of elevation, watershed size, and geology at regular points along a watershed boundary to stratify points by likelihood of connectivity during high precipitation (>20 mm of precipitation in a 3-day period). We then used a subset of points across a gradient of connectivity likelihoods to gather Landsat-derived observed surface water data and developed a statistical model to predict surface water presence from landscape characteristics. We applied the model throughout the entire watershed boundary to identify locations of hydrologic connectivity during high-water events. The presence of surface water on watershed boundaries was predicted by the interactions between watershed boundary point elevation relative to the minimum adjacent HUC-12 elevations and watershed boundary point elevation relative to neighboring point elevations (marginal R2 = 0.94). Our approach can be used to identify potential areas of surface water connectivity between watersheds quickly and easily at a fine spatial scale using readily available, remotely sensed data that can inform conservation and management actions across disciplines.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2025.1646017","usgsCitation":"Pfaff, P.J., Coulter, A.A., Schall, B.J., Davis, T., Chipps, S.R., and Coulter, D.P., 2025, Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.: Frontiers in Environmental Science, v. 113, 1646017, 8 p., https://doi.org/10.3389/fenvs.2025.1646017.","productDescription":"1646017, 8 p.","ipdsId":"IP-168696","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2025.1646017","text":"Publisher Index Page"},{"id":497465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.5860882678942,\n 47.0340515938843\n ],\n [\n -98.5860882678942,\n 42.75965927049364\n ],\n [\n -96.3287308953151,\n 42.75965927049364\n ],\n [\n -97.02339781306394,\n 45.96566324768915\n ],\n [\n -97.13756830247006,\n 47.16863340208883\n ],\n [\n -98.5860882678942,\n 47.0340515938843\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"113","noUsgsAuthors":false,"publicationDate":"2025-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pfaff, Peter J.","contributorId":363920,"corporation":false,"usgs":false,"family":"Pfaff","given":"Peter","middleInitial":"J.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":952106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coulter, Alison A.","contributorId":363922,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","middleInitial":"A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":952107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schall, Benjamin J.","contributorId":363925,"corporation":false,"usgs":false,"family":"Schall","given":"Benjamin","middleInitial":"J.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":952108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Tanner","contributorId":348518,"corporation":false,"usgs":false,"family":"Davis","given":"Tanner","affiliations":[{"id":83369,"text":"South Dakota Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":952109,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952110,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coulter, David P.","contributorId":363929,"corporation":false,"usgs":false,"family":"Coulter","given":"David","middleInitial":"P.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":952111,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271914,"text":"70271914 - 2025 - An exploration of the relative influence of physical models for Omori’s law","interactions":[],"lastModifiedDate":"2025-09-24T15:41:11.311135","indexId":"70271914","displayToPublicDate":"2025-09-10T10:36:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"An exploration of the relative influence of physical models for Omori’s law","docAbstract":"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":70271698,"text":"70271698 - 2025 - Ultraviolet and visible remote sensing of volcanic gases","interactions":[],"lastModifiedDate":"2025-09-19T14:52:18.799677","indexId":"70271698","displayToPublicDate":"2025-09-10T09:49:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Ultraviolet and visible remote sensing of volcanic gases","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. Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":950300,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271381,"text":"70271381 - 2025 - Multi-stage crustal thickening, surface uplift, and collision in the western Himalaya-Karakoram-Tibet orogen revealed by chemical mohometry","interactions":[],"lastModifiedDate":"2025-09-11T15:03:42.311751","indexId":"70271381","displayToPublicDate":"2025-09-10T07:53:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Multi-stage crustal thickening, surface uplift, and collision in the western Himalaya-Karakoram-Tibet orogen revealed by chemical mohometry","docAbstract":"The Himalaya-Karakoram-Tibet (HKT) orogen provides an unrivaled opportunity to study the dynamic linkages between deep and surface processes during collisional orogenesis. 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":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.
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zone","interactions":[],"lastModifiedDate":"2025-11-20T16:23:06.555018","indexId":"70272284","displayToPublicDate":"2025-09-08T09:17:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone","docAbstract":"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.
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