The tectonic evolution of and relation between the Yukon-Tanana terrane and the Lake George assemblage, as well as other associated tectonic assemblages in western Yukon and eastern Alaska, have been debated for decades. The Yukon-Tanana terrane is widely considered to be an allochthonous rifted fragment derived from the Laurentian continental margin, whereas the Lake George assemblage and associated assemblages are currently interpreted to be part of the parautochthonous continental margin of western North America (Laurentia). To address these topics, we present 40 new U-Pb zircon ages and 20 new whole-rock geochemical analyses. We incorporate these data into a new compilation of available geological mapping for a large area that straddles the Alaska-Yukon border, together with 34 previously published U-Pb age determinations and an extensive geochemical database of metaigneous rocks from Late Devonian to Early Mississippian and middle to late Permian assemblages in this area.
Magmatism in the Lake George assemblage and related assemblages occurred in two pulses from about 371 to 360 and from about 358 to 347 million years ago (Ma); geochemical discrimination diagrams indicate a large crustal component, possibly indicative of arc magmatism, for felsic metaigneous rocks and a range of tectonic environments for mafic rocks. Magmatism in the Fortymile River and related assemblages, and parts of the Nasina assemblage—all parts of the Yukon-Tanana terrane—are mainly Early Mississippian and span a crystallization age range from about 361 to 343 Ma; geochemical discrimination diagrams for these rocks indicate primarily arc geochemical signatures for both mafic and felsic rocks. Middle to late Permian crystallization ages (about 261–253 Ma) are indicated for felsic metaigneous rocks in the Klondike assemblage and some of the felsic metaigneous rocks in the Nasina assemblage. Based on our mapping, we propose the existence of a possible unconformity between the Mississippian and Permian felsic metavolcanic rocks within the Nasina assemblage that is marked by sporadic occurrences of stretched-pebble conglomerate.
Our combined database supports the well-established model of a magmatic arc comprising the Fortymile River and Finlayson assemblages of the rifted Yukon-Tanana terrane continental fragment on which a middle to late Permian arc (Klondike assemblage) was later built. The assemblages of the Yukon-Tanana terrane were subsequently intruded by Late Triassic to Early Jurassic granitoids, presumably during reaccretion of the Yukon-Tanana terrane to the continental margin. Permian and Late Triassic to Early Jurassic intrusions have not been mapped in the now structurally lower plate Lake George assemblage; their absence is one of the lines of evidence that have been used to support the parautochthonous, rather than allochthonous, origin of the Lake George assemblage and related assemblages. Our new data, together with previously published ranges of igneous crystallization ages and geochemical tectonic signatures of the Late Devonian to Early Mississippian magmatic rocks in the Lake George assemblage and associated assemblages and in the Fortymile River, Nasina, and correlated assemblages of the Yukon-Tanana terrane, indicate that the currently accepted interpretation of the Lake George assemblage and associated rocks being part of parauthochthonous North America is not the only possible interpretation of this tectonic entity. Approximately half of the dated intrusive rocks in the Lake George assemblage are contemporaneous with the metaigneous rocks of the Yukon-Tanana terrane arc (<361 Ma). We speculate that our approximately 361 Ma U-Pb age for quartz syenite in part of the North American continental margin in south-central Yukon defines the beginning of rifting of the Laurentian margin. Although the currently favored model of prolonged middle Paleozoic subduction and extension in both the Yukon-Tanana terrane and parautochthonous North America allows for simultaneous middle Paleozoic magmatism on both sides of the Slide Mountain Ocean, we now propose an alternative hypothesis in which the Lake George assemblage represents a deeper part of the rifted Yukon-Tanana terrane arc. If this is the case, the absence of Permian and Late Triassic to Early Jurassic arc rocks in the Lake George assemblage could be explained either by the arcs of these ages not being wide enough to have affected the Lake George assemblage or by tectonic displacement of these arc rocks away from the Lake George assemblage.
Our approximately 259 Ma U-Pb zircon age and geochemical analyses of metarhyolite in the Seventymile terrane in Alaska, which comprises remnants of the back-arc basin that separated the Yukon-Tanana terrane from the Laurentian continental margin, confirm the presence of a late middle Permian volcanic arc component to the terrane. Our approximately 319 Ma U-Pb zircon age from the Chicken assemblage (as redefined in this study) in eastern Alaska, combined with previously reported fossil ages and a U-Pb zircon age from this assemblage, indicate that it is a Late Mississippian to Early Pennsylvanian arc assemblage. We propose several other relatively young, locally developed arc assemblages outboard of the ancient continental margin of Laurentia that may correlate with the Chicken assemblage, but we consider its origin to remain an enigma.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1888","usgsCitation":"Dusel-Bacon, C., and Mortensen, J.K., 2024, New U-Pb geochronology and geochemistry of Paleozoic metaigneous rocks from western Yukon and eastern Alaska, cross-border synthesis, and implications for tectonic models (ver. 1.1, December 2024): U.S. Geological Survey Professional Paper 1888, 100 p., https://doi.org/10.3133/pp1888.","productDescription":"Report: vi, 100 p.; Data Release","numberOfPages":"100","onlineOnly":"Y","ipdsId":"IP-120238","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":494234,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117305.htm","linkFileType":{"id":5,"text":"html"}},{"id":432900,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/pp/1888/images"},{"id":432899,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1888/pp1888.xml"},{"id":432898,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1888/pp1888.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432896,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93ZWGA1","text":"USGS Data Release","description":"Dusel-Bacon, C., and Mortensen, J.K., 2023, New U-Pb geochronology and geochemistry of Paleozoic metaigneous rocks from western Yukon and eastern Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/P93ZWGA1.","linkHelpText":"New U-Pb geochronology and geochemistry of Paleozoic metaigneous rocks from western Yukon and eastern Alaska"},{"id":432901,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/pp1888/full"},{"id":432897,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1888/covrthb.jpg"},{"id":465115,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1888/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -165.8250144876443,\n 71.34744883614135\n ],\n [\n -165.8250144876443,\n 53.1023500477161\n ],\n [\n -121.35235823764475,\n 53.1023500477161\n ],\n [\n -121.35235823764475,\n 71.34744883614135\n ],\n [\n -165.8250144876443,\n 71.34744883614135\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"ver. 1.0: September 4, 2024; ver. 1.1: December 16, 2024","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
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Many conservation actions must be implemented with limited data. This is especially true when planning recovery efforts for extirpated populations, such as grizzly bears (Ursus arctos) within the Bitterroot Ecosystem (BE), where strategies for reestablishing a resident population are being evaluated. Here, we applied individual-based movement models developed for a nearby grizzly bear population to predict habitat use in and near the BE, under scenarios of natural recolonization, reintroduction, and a combination. All simulations predicted that habitat use by grizzly bears would be higher in the northern half of the study area. Under the natural recolonization scenario, use was concentrated in Montana, but became more uniform across the northern BE in Idaho over time. Use was more concentrated in east-central Idaho under the reintroduction scenario. Assuming that natural recolonization continues even if bears are reintroduced, use remained widespread across the northern half of the BE and surrounding areas. Predicted habitat maps for the natural recolonization scenario aligned well with outlier and GPS collar data available for grizzly bears in the study area, with Spearman rank correlations of ≥0.93 and mean class values of ≥9.1 (where class 10 was the highest relative predicted use; each class 1–10 represented 10% of the landscape). In total, 52.4% of outlier locations and 79% of GPS collar locations were in class 10 in our predicted habitat maps for natural recolonization. Simulated grizzly bears selected habitats over a much larger landscape than the BE itself under all scenarios, including multiple-use and private lands, similar to existing populations that have expanded beyond recovery zones. This highlights the importance of recognizing and planning for the role of private lands in recovery efforts, including understanding resources needed to prevent and respond to human-grizzly bear conflict and maintain public acceptance of grizzly bears over a large landscape.
The effort to map terrestrial biodiversity, in recent years limited mostly to the use of broadband multispectral remote sensing at decameter scales, can be greatly enhanced by harnessing hyperspectral imagery. Interpretation of hyperspectral imagery may be aided by the Mixture Residual (MR) spectral preprocessing transformation. MR integrates the benefits of spectral mixture analysis with the absorption peak-enhancing characteristics of continuum removal. MR characterizes each pixel as a linear combination of generic end-members estimating the spectral continuum, from which the residual of each wavelength is computed and treated as a source of additional information. Using Hyperspectral Precursor of the Application Mission (PRISMA) imagery, we tested the ability of MR-transformed reflectance as compared to untransformed surface reflectance (SR) to map plant associations and land cover using ground truthing and random forest classifications across four landscapes within the North American Coastal Plain. We used a forward stepwise selection algorithm to choose bands for each classification and subsequently compared these between SR and MR. Our MR classifications distinguished land cover with 5% greater balanced accuracy on average than the SR-based classifications across all four landscapes. The MR-based classification that integrated data from all landscapes into a unified model encompassing all 21 land cover types achieved a 76% average balanced accuracy over three iterations. Generally, MR utilized the near-infrared region to a greater degree than SR while deemphasizing the green peak. Based on our results, MR improves the accuracy of mapping terrestrial biodiversity, likely extending to other current and planned satellite hyperspectral missions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JG008217","usgsCitation":"Rogers, J.A., Robertson, K.M., Hawbaker, T., and Sousa, D.J., 2024, Classifying plant communities in the North American Coastal Plain with PRISMA spaceborne hyperspectral imagery and the spectral mixture residual: JGR Biogeosciences, v. 129, no. 9, e2024JG008217, 19 p., https://doi.org/10.1029/2024JG008217.","productDescription":"e2024JG008217, 19 p.","ipdsId":"IP-165238","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":439180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jg008217","text":"Publisher Index Page"},{"id":433495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rogers, Jennifer A.","contributorId":244616,"corporation":false,"usgs":false,"family":"Rogers","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":912306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Kevin M.","contributorId":298157,"corporation":false,"usgs":false,"family":"Robertson","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":912307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":912308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sousa, Daniel J.","contributorId":343899,"corporation":false,"usgs":false,"family":"Sousa","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":16253,"text":"Department of Geography, San Diego State University","active":true,"usgs":false}],"preferred":false,"id":912309,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263063,"text":"70263063 - 2024 - Modeling regional occupancy of fishes using acoustic telemetry: A model comparison framework applied to lake trout","interactions":[],"lastModifiedDate":"2025-01-29T16:01:54.585935","indexId":"70263063","displayToPublicDate":"2024-09-03T08:56:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Modeling regional occupancy of fishes using acoustic telemetry: A model comparison framework applied to lake trout","docAbstract":"Acoustic telemetry is a common tool used in fisheries management to estimate fish space use (i.e., occupancy) from a local habitat scale to entire systems. Numerous analytical models have been developed to estimate different aspects of fish movement from telemetry datasets, yet evaluations of model performance and comparisons among models are limited. Here, we develop a framework to evaluate model estimates of regional occupancy in large and fragmented systems using an acoustic receiver array in Lake Champlain. We simulated the tracks of 100 acoustically tagged fish using a random walk function and created detection events based on receiver positions and distance-based detection probability. Regional occupancy for the simulated data was estimated by six movement models that ranged in analytical complexity, and results were compared to the true distributions for each simulated track to evaluate model error. The six movement models included: (1) a basic residency index using detections alone; (2) a residency index using last-observation-carried-forward; (3) a centers of activity model; (4) linear and non-linear interpolations (i.e., least-cost paths); and (5 and 6) two dynamic Brownian bridge movement models generated using separate packages in R. We developed a model selection process to compare model performance and select the optimal analysis based on simulation error. This process showed significant differences in model performance among the six movement models based on model error. Overall, the model generating least-cost paths using linear and non-linear interpolations consistently provided the most accurate regional occupancy estimates. Based on these simulation results, we applied this model to a case study that evaluated patterns in the regional distribution of stocked lake trout (Salvelinus namaycush) in Lake Champlain, which demonstrated distinct regional occupancy of two stocked lake trout groups. These results demonstrate potential for large variability in interpretation of acoustic telemetry data for describing regional fish distribution dependent on the analytical method used.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40317-024-00380-3","usgsCitation":"Futia, M., Binder, T., Henderson, M., and Marsden, J., 2024, Modeling regional occupancy of fishes using acoustic telemetry: A model comparison framework applied to lake trout: Animal Biotelemetry, v. 12, 25, 16 p., https://doi.org/10.1186/s40317-024-00380-3.","productDescription":"25, 16 p.","ipdsId":"IP-164562","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489756,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-024-00380-3","text":"Publisher Index Page"},{"id":481459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.45559820823414,\n 45.14081170765235\n ],\n [\n -73.45559820823414,\n 44.25840593080014\n ],\n [\n -73.1040357082343,\n 44.25840593080014\n ],\n [\n -73.1040357082343,\n 45.14081170765235\n ],\n [\n -73.45559820823414,\n 45.14081170765235\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Futia, Matthew H.","contributorId":350119,"corporation":false,"usgs":false,"family":"Futia","given":"Matthew H.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":925424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binder, Thomas R.","contributorId":350120,"corporation":false,"usgs":false,"family":"Binder","given":"Thomas R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":925425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":925426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsden, J. Ellen","contributorId":350121,"corporation":false,"usgs":false,"family":"Marsden","given":"J. Ellen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":925427,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70258100,"text":"70258100 - 2024 - Ranking of 10 global one-arc-second DEMs reveals limitations in terrain morphology representation","interactions":[],"lastModifiedDate":"2024-09-04T12:01:17.673138","indexId":"70258100","displayToPublicDate":"2024-09-03T06:54:07","publicationYear":"2024","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":"Ranking of 10 global one-arc-second DEMs reveals limitations in terrain morphology representation","docAbstract":"A detailed analysis is made of horizontal-component geomagnetic-disturbance data acquired at the Colaba observatory in India recording the Carrington magnetic storm of September 1859. Prior to attaining its maximum absolute value, disturbance at Colaba increased with an e-folding timescale of 0.46 hr (28 min). Following its maximum, absolute disturbance at Colaba decreased as a trend having an e-folding timescale of 0.31 hr (19 min). Both of these timescales are much shorter than those characterizing the drift period of ring-current ions. Furthermore, over one 28-min interval when absolute disturbance was increasing, the data indicate an absolute rate of change of ≥2,436 nT/hr. If this is representative of disturbance generated by a symmetric magnetospheric ring current, then, assuming a standard and widely used parameterization, an interplanetary electric field of ≥451 mV/m is indicated. An idealized and extreme solar-wind dynamic pressure could, conceivably, reduce this bound on the interplanetary electric field to ≥202 mV/m. If the parameterization for electric-field extrapolation is accurate, but the field strengths obtained are deemed implausible, then it can be concluded that the Colaba disturbance data were significantly affected by partial-ring, field-aligned, or ionospheric currents. The same conclusion is supported by the shortness of the e-folding timescales characterizing the Colaba data. Several prominent studies of the Carrington event need to be reconsidered.
As climate change effects intensify, key life history events may become decoupled from necessary biotic and abiotic resources. For species of management concern on Department of Defense (DoD) lands, these shifts in phenology may prove difficult to address without a mechanistic understanding of the drivers of such changes. We sought to determine the causes and effects of phenological shifts on species of management concern by using observational and experimental data to develop and test population viability models. Our objectives were to (i) identify the patterns and drivers of adult breeding and juvenile emigration phenology for four pond-breeding salamanders (three of management concern), (ii) determine how shifts in phenology and abiotic resources affect the strength of species interactions, community structure, and population viability, and (iii) provide management options to mitigate shifts in phenology that may impact ongoing conservation and recovery efforts.
","language":"English","publisher":"U.S. Department of Defense","collaboration":"Department of Defense; Virginia Tech; Southern Illinois University-Edwardsville; Appalachian State Univerisity","usgsCitation":"Walls, S., Anderson, T.L., Chandler, H.C., Haas, C.A., and Davenport, J., 2024, Predicting the persistence of salamanders: consequences of phenological shifts for species of management concern on DoD lands, xiii, 91 p.","productDescription":"xiii, 91 p.","ipdsId":"IP-154081","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":463014,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://serdp-estcp.mil/projects/details/de8539d8-7234-4de2-878b-04a3e7299b1a/rc-2703-project-overview"},{"id":463067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":215987,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":916226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Thomas L.","contributorId":345296,"corporation":false,"usgs":false,"family":"Anderson","given":"Thomas","email":"","middleInitial":"L.","affiliations":[{"id":82537,"text":"Southern Illinois University-Edwardsville","active":true,"usgs":false}],"preferred":false,"id":916227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Houston C.","contributorId":342515,"corporation":false,"usgs":false,"family":"Chandler","given":"Houston","email":"","middleInitial":"C.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":916228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haas, Carola A.","contributorId":208321,"corporation":false,"usgs":false,"family":"Haas","given":"Carola","email":"","middleInitial":"A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":916229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davenport, Jon M.","contributorId":126727,"corporation":false,"usgs":false,"family":"Davenport","given":"Jon M.","affiliations":[{"id":6583,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, USA 59812","active":true,"usgs":false}],"preferred":false,"id":916230,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266905,"text":"70266905 - 2024 - Recognition of artificial gases formed during drill-bit metamorphism using advanced mud gas","interactions":[],"lastModifiedDate":"2025-05-15T15:04:15.890062","indexId":"70266905","displayToPublicDate":"2024-09-02T07:58:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10757,"text":"Energies","active":true,"publicationSubtype":{"id":10}},"title":"Recognition of artificial gases formed during drill-bit metamorphism using advanced mud gas","docAbstract":"Drill-bit metamorphism (DBM) is the process of thermal degradation of drilling fluid at the interface of the bit and rock due to the overheating of the bit. The heat generated by the drill when drilling into a rock formation promotes the generation of artificial hydrocarbon and non-hydrocarbon gas, changing the composition of the gas. The objective of this work is to recognize and evaluate artificial gases originating from DBM in wells targeting oil accumulations in pre-salt carbonates in the Santos Basin, Brazil. For the evaluation, chromatographic data from advanced mud gas equipment, drilling parameters, drill type, and lithology were used. The molar concentrations of gases and gas ratios (especially ethene/ethene+ethane and dryness) were analyzed, which identified the occurrence of DBM. DBM is most severe when wells penetrate igneous and carbonate rocks with diamond-impregnated drill bits. The rate of penetration, weight on bit, and rotation per minute were evaluated together with gas data but did not present good correlations to assist in identifying DBM. The depth intervals over which artificial gases formed during DBM are recognized should not be used to infer pay zones or predict the composition and properties of reservoir fluids because the gas composition is completely changed.","language":"English","publisher":"MDPI","doi":"10.3390/en17174383","usgsCitation":"Leon, J., Penteado, H., Ellis, G.S., Milkov, A., and Filho, J., 2024, Recognition of artificial gases formed during drill-bit metamorphism using advanced mud gas: Energies, v. 17, no. 17, 4383, 15 p., https://doi.org/10.3390/en17174383.","productDescription":"4383, 15 p.","ipdsId":"IP-156439","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":490123,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en17174383","text":"Publisher Index Page"},{"id":485995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Santos Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -47.95829074516948,\n -24.158423608072184\n ],\n [\n -48.78636605095795,\n -27.5769025278343\n ],\n [\n -46.99648407706377,\n -28.685560867609183\n ],\n [\n -43.4776286149596,\n -28.710262272210713\n ],\n [\n -41.53986377011067,\n -24.167147426819017\n ],\n [\n -43.19143671242696,\n -22.156723909933447\n ],\n [\n -47.95829074516948,\n -24.158423608072184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"17","noUsgsAuthors":false,"publicationDate":"2024-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Leon, Janaina A. de Lima","contributorId":355194,"corporation":false,"usgs":false,"family":"Leon","given":"Janaina A. de Lima","affiliations":[{"id":84724,"text":"Petrobras, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":937093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penteado, Henrique Luiz de Barros","contributorId":355195,"corporation":false,"usgs":false,"family":"Penteado","given":"Henrique Luiz de Barros","affiliations":[{"id":84724,"text":"Petrobras, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":937094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":937095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Milkov, Alexei V.","contributorId":355196,"corporation":false,"usgs":false,"family":"Milkov","given":"Alexei V.","affiliations":[{"id":13027,"text":"Department of Geology and Geological Engineering, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":937096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Filho, João Graciano Mendonça","contributorId":355197,"corporation":false,"usgs":false,"family":"Filho","given":"João Graciano Mendonça","affiliations":[{"id":84726,"text":"Federal University of Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":937097,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261010,"text":"70261010 - 2024 - Insights on gas hydrate formation and growth within an interbedded sand reservoir from well logging at the Qiongdongnan Basin, South China Sea","interactions":[],"lastModifiedDate":"2024-11-20T15:04:25.941164","indexId":"70261010","displayToPublicDate":"2024-09-02T07:56:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Insights on gas hydrate formation and growth within an interbedded sand reservoir from well logging at the Qiongdongnan Basin, South China Sea","docAbstract":"Although variable well log resolution and its control on saturation estimation has been studied, it has not been directly applied to a specific location to explore the nature of gas hydrate within a sand reservoir. We applied in-situ measurements of resistivities, neutron porosity, and gamma ray at two sites in the Qiongdongnan Basin, South China Sea (QDN-W05–2021 and QDN-W08–2021) to investigate the reservoir parameters of a hydrate-bearing sand reservoir. Our results show that gas hydrate is distributed in 5 zones with a total thickness of 10.7 m and an average saturation of 69% at the QDN-W05–2021 site, while they are distributed in 2 zones with a total thickness of 4.3 m and an average saturation of 49% at the QDN-W08–2021 site. We found that variances in saturations estimated from lateral-extra deep button (RX), phase shift (P40H-P40L), and attenuation (A40H-A40L) resistivities within the laterally mapped continuous sand body were affected by the nature of gas hydrate occurrences. Results indicate gas hydrate forms and accumulates at the center of the sand layer and tends to be less or not present toward the top and base. Integrated with seismic data, the in-situ measurements provide insights in the evolution of a mushroom-shaped, hydrate-gas reservoir system. In the system, free gas is likely horizontally transported from the top-center of the gas chimney to the surrounding areas in the early stage dominated by a warm-gas environment, whereas hydrate forms in the opposite pathway starting from the surrounding areas in the following stage with temperature reducing. Our study suggests that high-resolution in-situ measurements not only are a tool to identify the physical properties, but also can be used to help explain the physical process of hydrate growth and accumulation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2024.107343","usgsCitation":"Kang, D., Zhang, Z., Lu, J., Phillips, S.C., Liang, J., Deng, W., Zhong, C., and Meng, D., 2024, Insights on gas hydrate formation and growth within an interbedded sand reservoir from well logging at the Qiongdongnan Basin, South China Sea: Marine Geology, v. 475, 107343, 14 p., https://doi.org/10.1016/j.margeo.2024.107343.","productDescription":"107343, 14 p.","ipdsId":"IP-167278","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":498062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2024.107343","text":"Publisher Index Page"},{"id":464339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Qiongdongnan Basin, South China Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 109.8098221507899,\n 17.666985235695577\n ],\n [\n 109.8098221507899,\n 15.348061719259704\n ],\n [\n 117.49933295499756,\n 15.348061719259704\n ],\n [\n 117.49933295499756,\n 17.666985235695577\n ],\n [\n 109.8098221507899,\n 17.666985235695577\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"475","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kang, Dongju","contributorId":208555,"corporation":false,"usgs":false,"family":"Kang","given":"Dongju","email":"","affiliations":[],"preferred":false,"id":918899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zijian","contributorId":346398,"corporation":false,"usgs":false,"family":"Zhang","given":"Zijian","email":"","affiliations":[{"id":82862,"text":"Research Institute of Tsinghua University in Shenzhen; Prime Ocean Technology Inc","active":true,"usgs":false}],"preferred":false,"id":918900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Jing’an","contributorId":346399,"corporation":false,"usgs":false,"family":"Lu","given":"Jing’an","email":"","affiliations":[{"id":68688,"text":"Guangzhou Marine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liang, Jinqiang","contributorId":346400,"corporation":false,"usgs":false,"family":"Liang","given":"Jinqiang","email":"","affiliations":[{"id":68688,"text":"Guangzhou Marine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Deng, Wei","contributorId":316745,"corporation":false,"usgs":false,"family":"Deng","given":"Wei","email":"","affiliations":[{"id":68688,"text":"Guangzhou Marine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918904,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhong, Chao","contributorId":346401,"corporation":false,"usgs":false,"family":"Zhong","given":"Chao","email":"","affiliations":[{"id":68688,"text":"Guangzhou Marine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918905,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meng, Dajiang","contributorId":346402,"corporation":false,"usgs":false,"family":"Meng","given":"Dajiang","email":"","affiliations":[{"id":68688,"text":"Guangzhou Marine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918906,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70260984,"text":"70260984 - 2024 - 2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County","interactions":[],"lastModifiedDate":"2024-11-19T19:53:51.891323","indexId":"70260984","displayToPublicDate":"2024-09-01T13:42:45","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County","docAbstract":"Western San Diego County is dominated by shrublands supporting biologically diverse native plant and animal communities. Widespread urbanization has led to regional habitat loss and fragmentation, and many species in these shrubland communities are rare, threatened, or endangered. Large-scale, multiple-species conservation planning has resulted in a regional preserve system that focuses on these shrubland communities. Several large-scale threats are leading to type conversion from shrub-dominated to non-native invasive annual grass-dominated vegetation. To understand the changes that are occurring to native shrublands, we have developed a vegetation monitoring program with several components at multiple spatial scales, focused on quantifying coastal sage scrub (CSS) and chaparral vegetation community characteristics. Several drivers of change associated with type conversion of native shrubland to non-native annual grassland have been identified by previous research including increasing fire frequency, nitrogen deposition from air pollution, and prolonged and intense drought associated with changing climate.\nLoss of ecological integrity indices have been proposed as useful measures of the threat of degradation and type conversion of shrublands in San Diego County. For this study, ecological integrity is defined as a system’s ability to maintain species’ relationships and functions comparable to natural habitat in the region. Previous studies have identified the percent cover of invasive non-native annual grasses as a proxy for overall ecological degradation (loss of integrity) that is consistent across native taxonomic groups. Increased cover of non-native grass is associated with lower integrity of the shrubland vegetation community as shrub-associated plant and animal species are replaced by species preferring grassy and disturbed habitats. \nThe objectives of this CSS and chaparral vegetation community monitoring plan are to:\n1) Determine the distribution, composition, structure, and integrity of CSS and chaparral vegetation communities on conserved lands in western San Diego County,\n2) Identify whether these attributes of the vegetation communities are changing over time, and\n3) Evaluate relationships of known drivers of change (threats) and environmental factors in association with changes in vegetation community attributes.\nThe CSS and chaparral vegetation community monitoring program is divided into four components: 1) vegetation mapping, 2) GIS/remote sensing office analysis of landscape-scale data, 3) permanent field plots using Unmanned Aerial Systems (UAS) and field data collections, and 4) animal and target species surveys and rapid assessment protocols. \nThe first component, which is not detailed in this vegetation monitoring plan, aims to map vegetation communities every 10-15 years based on a classification developed for western San Diego County. High resolution aerial imagery will be used to update the 2012 vegetation map and expand it across the entire study area. \nThe second component uses remote sensing models to annually track ecological integrity of shrublands across the study area and will include a map of areas of change and areas of stability over several decades. These landscape-scale integrity classifications will be used to analyze ecological processes, threats, and abiotic factors relative to changes to shrubland ecological integrity over time and space. \nThe third component includes field surveys of 100 permanent plots across areas historically mapped as shrublands. Surveys in the 1930s mapped vegetation types using plot data. By using this historical classification map, we included areas that have already type-converted from shrubland to non-native annual grassland. The plots were split between CSS (55 plots) and chaparral (45 plots) and stratified into four geographical eco-subregions to guarantee coverage over small patches of habitat along the heavily developed coast. Surveys will include the collection of UAS imagery at a very high resolution. Species-level identifications will be made from the imagery based on a plant list compiled of all species detected in the plot during a thorough field survey by botanists, combined with geo-referenced samples of plant species locations. In addition, herbaceous cover will be estimated in the field using nine 1-m diameter circles (one per subplot) to obtain ocular estimates of cover for each plant species within the circle frame. Soil samples will be collected and analyzed for important element compositions. These data will be analyzed to evaluate plot-level ecological integrity based on species composition and cover. Repeated monitoring will allow evaluation of changes in vegetation attributes over time with known drivers or threats and other environmental factors. In addition, analyses will focus on indicator species and various measures of biological diversity for the vegetation communities.\nFinally, animal species and rare plants will be assessed using either taxa-based rapid assessment protocols or specialized species-specific protocols for rarer species. The purpose of these assessments is to document the status, habitat, and threat covariates of specific species and confirm the species composition and diversity of animal taxonomic groups (e.g., pollinators). Diversity and abundance of animal species at vegetation plots will be used to refine measures and thresholds of ecological integrity. Rapid assessment protocols for animal taxonomic groups can include multiple detection methods such as, camera traps, cover boards, and bird point counts. Pollinators will be monitored at plots using a protocol currently being developed in conjunction with but separately from this plan. Target rare plant species will be monitored using the regional Inspect and Manage (IMG) protocol that measures the status of rare plant occurrences and habitat and threat covariates over time. Species-specific animal survey methods will be refined as these species are prioritized for future monitoring.\nThe goal of this monitoring program is to classify CSS and chaparral vegetation community integrity, identify areas of degradation across western San Diego County, and characterize drivers, and environmental factors associated with loss of ecological integrity. A combination of vegetation mapping, landscape-scale remote sensing, and field plots will be used to address all the aspects of our research questions. Data compiled and collected will be available to conservation partners to help inform future management decisions.","language":"English","publisher":"San Diego Association of Government Regional Habitat Conservation Taskforce","usgsCitation":"Perkins, E., Gould, P.R., Kingston, J., Brown, C., Preston, K.L., and Fisher, R., 2024, 2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County, 140 p.","productDescription":"140 p.","ipdsId":"IP-166858","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":464285,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.sdmmp.com/upload/SDMMP_Repository/0/d1hm9b5prngj2v306zfqs84y7tcxwk.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":464301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13399491171916,\n 32.5777941285686\n ],\n [\n -117.13399491171916,\n 32.54958248003706\n ],\n [\n -117.08507141928763,\n 32.54958248003706\n ],\n [\n -117.08507141928763,\n 32.5777941285686\n ],\n [\n -117.13399491171916,\n 32.5777941285686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perkins, Emily E. 0000-0002-6286-3480","orcid":"https://orcid.org/0000-0002-6286-3480","contributorId":225022,"corporation":false,"usgs":true,"family":"Perkins","given":"Emily E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gould, Philip Robert 0000-0002-8871-0968","orcid":"https://orcid.org/0000-0002-8871-0968","contributorId":294694,"corporation":false,"usgs":true,"family":"Gould","given":"Philip","email":"","middleInitial":"Robert","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kingston, Jennifer 0000-0002-9994-1972","orcid":"https://orcid.org/0000-0002-9994-1972","contributorId":258244,"corporation":false,"usgs":true,"family":"Kingston","given":"Jennifer","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Christopher W. 0000-0002-2545-9171","orcid":"https://orcid.org/0000-0002-2545-9171","contributorId":240860,"corporation":false,"usgs":true,"family":"Brown","given":"Christopher W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918803,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263730,"text":"70263730 - 2024 - Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings","interactions":[],"lastModifiedDate":"2025-02-20T16:44:12.502285","indexId":"70263730","displayToPublicDate":"2024-09-01T10:34:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3418,"text":"Soil Dynamics and Earthquake Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings","docAbstract":"Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity (VS) structure, which is the main ingredient for estimating the variability of site response. As such, VS can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus VS can substantially modify ground shaking during earthquakes. We apply a novel VS randomization approach to propagate the small-scale heterogeneities of VS to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of VS profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of VS small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.soildyn.2024.108945","usgsCitation":"Youssef, E., Cornou, C., Youssef Abdel Massih, D., Al-Bittar, T., Yong, A., and Hollender, F., 2024, Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings: Soil Dynamics and Earthquake Engineering, v. 106, 100945, 15 p., https://doi.org/10.1016/j.soildyn.2024.108945.","productDescription":"100945, 15 p.","ipdsId":"IP-160514","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489887,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.soildyn.2024.108945","text":"Publisher Index Page"},{"id":482283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France, United States","state":"California","city":"Saint-Paul-lez-Durance","otherGeospatial":"Cadarache downhole array, Treasure Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.38,\n 37.83\n ],\n [\n -122.38,\n 37.805\n ],\n [\n -122.36,\n 37.805\n ],\n [\n -122.36,\n 37.83\n ],\n [\n -122.38,\n 37.83\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 0,\n 45\n ],\n [\n 0,\n 42\n ],\n [\n 6,\n 42\n ],\n [\n 6,\n 45\n ],\n [\n 0,\n 45\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"106","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Youssef, Eliane","contributorId":351145,"corporation":false,"usgs":false,"family":"Youssef","given":"Eliane","affiliations":[{"id":55486,"text":"University of Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":927979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cornou, Cecile","contributorId":351146,"corporation":false,"usgs":false,"family":"Cornou","given":"Cecile","affiliations":[{"id":55486,"text":"University of Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":927980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youssef Abdel Massih, Dalia","contributorId":351147,"corporation":false,"usgs":false,"family":"Youssef Abdel Massih","given":"Dalia","affiliations":[{"id":83927,"text":"Lebanese University, Lebanon","active":true,"usgs":false}],"preferred":false,"id":927981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Al-Bittar, Tamara","contributorId":351148,"corporation":false,"usgs":false,"family":"Al-Bittar","given":"Tamara","affiliations":[{"id":83927,"text":"Lebanese University, Lebanon","active":true,"usgs":false}],"preferred":false,"id":927982,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hollender, Fabrice","contributorId":351149,"corporation":false,"usgs":false,"family":"Hollender","given":"Fabrice","affiliations":[{"id":83928,"text":"French Alternative Energies and Atomic Energy Commission","active":true,"usgs":false}],"preferred":false,"id":927984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266733,"text":"70266733 - 2024 - Scale‐dependent population drivers inform avian management in a declining saline lake ecosystem","interactions":[],"lastModifiedDate":"2025-05-12T14:28:10.171398","indexId":"70266733","displayToPublicDate":"2024-09-01T09:18:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Scale‐dependent population drivers inform avian management in a declining saline lake ecosystem","docAbstract":"Shrinking saline lakes provide irreplaceable habitat for waterbird species globally. Disentangling the effects of wetland habitat loss from other drivers of waterbird population dynamics is critical for protecting these species in the face of unprecedented changes to saline lake ecosystems, ideally through decision-making frameworks that identify effective management options and their potential outcomes. Here, we develop a framework to assess the effects of hypothesized population drivers and identify potential future outcomes of plausible management scenarios on a saline lake-reliant waterbird species. We use 36 years of monitoring data to quantify the effects of environmental conditions on the population size of a regionally important breeding colony of American white pelicans (Pelecanus erythrorhynchos) at Great Salt Lake, Utah, US, then forecast colony abundance under various management scenarios. We found that low lake levels, which allow terrestrial predators access to the colony, are probable drivers of recent colony declines. Without local management efforts, we predicted colony abundance could likely decline approximately 37.3% by 2040, although recent colony observations suggest population declines may be more extreme than predicted. Results from our population projection scenarios suggested that proactive approaches to preventing predator colony access and reversing saline lake declines are crucial for the persistence of the Great Salt Lake pelican colony. Increasing wetland habitat and preventing predator access to the colony together provided the most effective protection, increasing abundance 145.4% above projections where no management actions are taken, according to our population projection scenarios. Given the importance of water levels to the persistence of island-nesting colonial species, proactive approaches to reversing saline lake declines could likely benefit pelicans as well as other avian species reliant on these unique ecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.3021","usgsCitation":"Van Tatenhove, A., Neill, J., Norvell, R., Stuber, E.F., and Rushing, C., 2024, Scale‐dependent population drivers inform avian management in a declining saline lake ecosystem: Ecological Applications, v. 34, no. 7, e3021, 14 p., https://doi.org/10.1002/eap.3021.","productDescription":"e3021, 14 p.","ipdsId":"IP-154179","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.19271300986851,\n 41.73273309975224\n ],\n [\n -113.19271300986851,\n 40.558106500816905\n ],\n [\n -111.76650863756069,\n 40.558106500816905\n ],\n [\n -111.76650863756069,\n 41.73273309975224\n ],\n [\n -113.19271300986851,\n 41.73273309975224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Tatenhove, Aimee M.","contributorId":354882,"corporation":false,"usgs":false,"family":"Van Tatenhove","given":"Aimee M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":936621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neill, John","contributorId":354883,"corporation":false,"usgs":false,"family":"Neill","given":"John","affiliations":[{"id":49122,"text":"Utah Division of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":936622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norvell, Russell E.","contributorId":354884,"corporation":false,"usgs":false,"family":"Norvell","given":"Russell E.","affiliations":[{"id":49122,"text":"Utah Division of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":936623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":936624,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rushing, Clark S.","contributorId":354886,"corporation":false,"usgs":false,"family":"Rushing","given":"Clark S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":936625,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257629,"text":"ofr20231053 - 2024 - Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","interactions":[],"lastModifiedDate":"2026-01-28T17:31:19.551324","indexId":"ofr20231053","displayToPublicDate":"2024-08-30T12:45:57","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1053","displayTitle":"Learning from a High-Severity Fire Event: Conditions Following the 2018 Carr Fire at Whiskeytown National Recreation Area","title":"Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","docAbstract":"The 2018 Carr Fire burned more than 90 percent of Whiskeytown National Recreation Area, with much of the park burning at high severity. California yellow pine and mixed conifer forests are not well adapted to large, high-severity fires, and forest recovery after these events may be problematic. Large, high-severity fire patches pose difficulties for recruitment with interiors that are long distances from potential seed trees and may develop fuel structures that can promote further high-severity fire. This report details patterns of forest structure derived from field plots measured 2–3 years after the Carr Fire, providing a characterization of immediate fire effects. We coupled these observations with remotely sensed information, including data collected from unoccupied aircraft system surveys. The remotely sensed data were used to depict erosion after the Carr Fire as well as to create a high-resolution land cover classification map, a debris flow risk map and hazard assessment, and a post-fire canopy vegetation loss map. Results indicated high levels of tree mortality after the Carr Fire, including high-value old growth forest stands, supporting remotely sensed assessments of fire severity. The high-resolution tree mortality model also aligned well with other remotely sensed estimates of immediate burn severity. Results of the land cover classification illustrated the high percentage of dead vegetation remaining in the understory and canopy 8 months post-fire. Changes in vegetation height identified areas with canopy vegetation loss from 1- to 8-months post-fire. Pairing the post-fire debris accumulation with debris flow probabilities may identify high-risk debris flow areas. The results of this study will help inform future decisions concerning wildland fire and vegetation management strategies at Whiskeytown National Recreation Area and are broadly relevant for management in the aftermath of large, high-severity fires in mixed, dry coniferous forests in the western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231053","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Ecosystems Mission Area—Land Change Science Program","usgsCitation":"van Mantgem, P.J., Wright, M.C., Thorne, K.M., Beckmann, J., Buffington, K., Rankin, L.L., Colley, A., and Engber, E.A., 2024, Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey Open-File Report 2023–1053, 52 p., https://doi.org/10.3133/ofr20231053.","productDescription":"Report: viii, 52 p.; 2 Data Releases","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-145882","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":499189,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117307.htm","linkFileType":{"id":5,"text":"html"}},{"id":432970,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231053/full"},{"id":432965,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97Y21L1","text":"USGS Data Release","description":"Wright, M.C., Engber, E., and van Mantgem, P.J., 2024, Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey data release, available at https://doi.org/10.5066/P97Y21L1.","linkHelpText":"Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area"},{"id":432964,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GS9V1J","text":"USGS Data Release","description":"Thorne, K.M., Freeman, C.M., and Rankin, L.L., 2024, UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire: U.S. Geological Survey data release, available at https://doi.org/10.5066/P9GS9V1J.","linkHelpText":"UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire"},{"id":432969,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1053/images"},{"id":432968,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.xml"},{"id":432967,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432966,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1053/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.82661214645721,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.425804364692084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Extraordinary floods surged down the Yellowstone River and its tributaries in northwestern Wyoming and south-central Montana on June 13–15, 2022. During the flood, U.S. Geological Survey staff worked to maintain real-time data from streamgages by making field measurements of streamflow and repairing damaged equipment while communicating the latest streamflow information with the public and with local, State, and Federal agencies. After the flood, staff surveyed high-water marks, computed peak streamflow at streamgages unreachable during the flood, and updated flood-frequency estimates for streamgages in the Upper Yellowstone River Basin. Streamflows were the highest on record at 17 streamgages in the Upper Yellowstone River Basin. River stages were highest on record at most of those streamgages. The flood-related data and analyses are summarized in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243035","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation and the Federal Emergency Management Agency","usgsCitation":"Chase, K.J., Dutton, D., Hamilton, W.B., Siefken, S.A., Vander Voort, C., and Whiteman, A., 2024, June 2022 floods in the Upper Yellowstone River Basin: U.S. Geological Survey Fact Sheet 2024–3035, 6 p., https://doi.org/10.3133/fs20243035.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-164447","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":433365,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243035/full"},{"id":433364,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3035/images/"},{"id":433363,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.XML"},{"id":433362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024–3035"},{"id":492687,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117264.htm","linkFileType":{"id":5,"text":"html"}},{"id":433361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3035/coverthb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Upper Yellowstone River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.3465081870854,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 45.25268386886597\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The Shinnecock Indian Nation on Long Island, New York, faces challenges of shoreline retreat, saltwater intrusion, and flooding of the Tribal lands under changing climate and rising sea level. However, understanding of the dynamics of tidal circulation and waves and their impacts on the Shinnecock Indian Nation’s shoreline remains limited. This numerical study employs the integrated modeling capabilities of the hydrodynamic model Delft3D-FLOW and the spectral-wave model Simulating WAves Nearshore (SWAN) to investigate the circulation and wave dynamics along the shoreline of Shinnecock Indian Nation. The results of the 1-year long simulation indicate the majority of wind waves approach the Shinnecock Nation shorelines at normal wave angles, with yearly averaged offshore wave height of around 0.2 meter, maximum wave height reaching 0.65 meter, and yearly averaged offshore wave power of approximately 50 watts per meter. Boulders, acting as natural barriers, have been placed along the shoreline to reduce erosive wave forcing. Simulation results indicate the boulders to the north end effectively attenuate wave energy and reduce annual wave power, while the boulders near the two tidal ponds adjacent to the Tribal cemetery only have a slight influence on wave energy. There are large spatial variabilities in wave attenuation and current velocity reduction by the boulders. The model framework developed in this study can be utilized for the optimal design of nature-based solutions, guiding decisions on the placement of living shoreline structures and determining their optimal size. This study further identifies data and knowledge gaps as well as future research opportunities that can enhance the performance of numerical models and contribute to the scientific understanding of coastal processes and facilitate the optimal design of hybrid living shorelines in the future to achieve the maximum protective efficacy. This research can help to inform strategies for safeguarding vulnerable coastal communities and promoting resilience and sustainability of shoreline along the Shinnecock Indian Nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241050","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University","usgsCitation":"Zhu, L., Wang, H., Chen, Q., Capurso, W., and Noll, M., 2024, Numerical modeling of circulation and wave dynamics along the shoreline of Shinnecock Indian Nation in Long Island, New York: U.S. Geological Survey Open-File Report 2024–1050, 32 p., https://doi.org/10.3133/ofr20241050.","productDescription":"Report: viii, 32 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-163925","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":434899,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241050/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1050 HTML"},{"id":433221,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG0AAO","text":"USGS Data Release","linkHelpText":"Three-dimensional point cloud data collected with a scanning total station on the western shoreline of the Shinnecock Nation Tribal lands, Suffolk County, New York, 2022"},{"id":433217,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1050/images"},{"id":433215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1050/coverthb.jpg"},{"id":433218,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.pdf","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1050"},{"id":433219,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1050 XML"},{"id":499260,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117308.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Shinnecock Indian Nation relative to Shinnecock Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.53273633004311,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.90389205501435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"Excess nutrient loading and other factors are driving eutrophication and other negative effects on water-quality conditions in Lake Champlain and other receiving waters in Vermont. Two common best management practices were evaluated to determine how these practices can be optimized by targeting maintenance and operation to align better with seasonally driven needs, specifically to help municipalities remove a greater proportion of seasonal leaves and organic debris, reduce nutrient loading, and achieve water-quality goals.
To characterize solid materials typically removed by the municipal BMPs of catch-basin (CB) cleaning and street cleaning (SC), subsamples of CB and SC materials were collected each month from nine participating municipalities in central and northwestern Vermont between September 2017 and November 2018. Monthly and seasonal composites of CB and SC samples were created from the subsamples of available materials from all municipalities. Samples were analyzed for concentrations of total organic carbon, total Kjeldahl nitrogen, and total phosphorus (P), and separated into three particle-size fractions. Distribution of particle-size fractions was similar between CB and SC as both practices generally collect the coarser fraction of solid materials (greater than 125 micrometers in diameter). In the fall, however, the range of the coarser fraction of materials increased. This is attributed to the ability of SC to collect leaves and other light organic materials that commonly pass through a CB system designed to trap heavier materials.
Total organic carbon, total Kjeldahl nitrogen, and total P concentrations were highest in the catch-basin samples in the fall of 2017, and concentrations in the SC samples were highest in the fall of 2018. The collection of fewer samples in 2017 may account for some of the variability between fall 2017 and fall 2018 results. A subset of SC samples collected from piles representing specific street-cleaning routes in September and November 2018 were also analyzed. Materials collected in November were dominated by leaves, and the concentrations of the analyzed species of carbon, nitrogen, and phosphorus in some samples were more than double those in samples collected on the same street-cleaning routes in September.
The Vermont Department of Environmental Conservation and the University of Vermont developed estimates of load-reduction credits for CB and SC practices based on a policy developed by the Wisconsin Department of Natural Resources that determined the potential for credits associated with leaf-removal activities. This process also considered BMPs that were initiated during the U.S. Environmental Protection Agency’s Lake Champlain Basin Total Maximum Daily Load monitoring period (2000 to 2009) and adapted the Wisconsin Department of Natural Resources policies to apply to existing SC routes in the cooperating Vermont municipalities that possessed at least 17 percent tree cover. This exercise demonstrated that applying the Wisconsin Department of Natural Resources policy to existing street-cleaning routes possessing 17 percent or more tree cover would result in reductions in total P loads up to 65 percent of mandated target reductions, and about a 25 percent reduction on average.
Continuous simulations of stormwater runoff volume, and of loads of suspended sediments and total P, also were created for Englesby Brook Basin, an urbanized basin in Burlington and South Burlington that drains to Lake Champlain. Although the basin is more developed than the average of the nine cooperating municipalities, streamflow and P loading data collected by the U.S. Geological Survey were available to evaluate model performance. Simulations based on a year of average climatic conditions projected potential small reductions in total P of 0.08 to 0.10 percent as a result of CB cleaning and SC practices. Simulated weekly SC practices, however, reduced street-solid loads by as much as 7 percent. When the proportion of total P seen in fall SC materials collected in Vermont was applied to these simulated street-solid loads, estimated reductions of total P were about 29 percent. The combination of analytical results, estimated load-reduction credits, and simulated reductions indicate that targeted increases of SC activities to reduce leaf loading in the fall have the potential to reduce loading to receiving waters and could help regulated communities meet their water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235104","collaboration":"Prepared in cooperation with the Chittenden County Regional Planning Committee, the City of South Burlington, and the Vermont Department of Environmental Conservation","usgsCitation":"Sorenson, J.R., Pease, J.M., Foote, J.K., Chalmers, A.T., Ainley, D.H., and Williams, C.J., 2024, Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont: U.S. Geological Survey Scientific Investigations Report 2023–5104, 46 p., https://doi.org/10.3133/sir20235104.","productDescription":"Report: viii, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-121578","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":433177,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A44LIX","text":"USGS data release","linkHelpText":"Data supporting phosphorus load-reduction estimates from leaf-litter removal in central and northwestern Vermont"},{"id":499382,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117265.htm","linkFileType":{"id":5,"text":"html"}},{"id":433176,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.XML","description":"SIR 2023-5104 XML"},{"id":433174,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235104/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5104 HTML"},{"id":433173,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.pdf","text":"Report","size":"9.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5104 PDF"},{"id":433164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5104/coverthb.jpg"},{"id":433175,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5104/images/"}],"country":"United States","state":"Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.3,\n 44.875\n ],\n [\n -73.3,\n 44.15\n ],\n [\n -72.5,\n 44.15\n ],\n [\n -72.5,\n 44.875\n ],\n [\n -73.3,\n 44.875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
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The U.S. Geological Survey hosted a Mississippi River Science Forum with Federal agencies; Tribal, State, and local governments located in States that border the Mississippi River; academia; and other interested stakeholders. The purpose of the forum was to share current (2023) science; identify data gaps and areas of concern; and to prioritize next steps needed to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters along the Mississippi River. The forum was a directive for the U.S. Geological Survey in the Consolidated Appropriations Act of 2022 (Public Law 117—103, 136 Stat. 49).
Participants and stakeholders that attended the Mississippi River Science Forum indicated the following.
This report highlights data gaps and areas of concern discussed during the forum, and it identifies needs to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters with specific emphasis on data collection and measurement, and scientific investigation. The report also summarizes stakeholder input and feedback and outlines next steps identified by forum participants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241053","usgsCitation":"Nelson, J.C., Rebich, R.A., Jankowski, K., Edwards, T.M., Larson, J.H., Robertson, D.M., Sprague, L.A., Stackpoole, S.M., Summers, K.M., Cinotto, P.J., Rydlund, P.H., Churchill, C.J., Daniel, W.M., Mckenna, O.P., Middleton, B.A.,\nCarter, J., Hartley, S.B., Frey, J.W., and Warner, K.L., 2024, U.S. Geological Survey Mississippi River Science Forum—Summary of data and science needs and next steps: U.S. Geological Survey Open-File Report 2024–1053, 4 p.,\nhttps://doi.org/10.3133/ofr20241053.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-159348","costCenters":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"links":[{"id":433267,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241053/full"},{"id":433266,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1053/images/"},{"id":433265,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.XML"},{"id":433264,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1053"},{"id":433263,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1053/coverthb.jpg"}],"otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.59374999999999,\n 30.14512718337613\n ],\n [\n -90.263671875,\n 31.12819929911196\n ],\n [\n -90.52734374999999,\n 33.063924198120645\n ],\n [\n -88.505859375,\n 35.460669951495305\n ],\n [\n -86.66015624999999,\n 35.10193405724606\n ],\n [\n -84.0234375,\n 35.31736632923788\n ],\n [\n -81.82617187499999,\n 36.73888412439431\n ],\n [\n -79.89257812499999,\n 37.996162679728116\n ],\n [\n -78.92578124999999,\n 39.70718665682654\n ],\n [\n -76.201171875,\n 42.032974332441405\n ],\n [\n -76.025390625,\n 42.87596410238256\n ],\n [\n -77.080078125,\n 42.87596410238256\n ],\n [\n -79.189453125,\n 41.31082388091818\n ],\n [\n -83.232421875,\n 40.38002840251183\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -88.41796875,\n 41.376808565702355\n ],\n [\n -89.296875,\n 44.402391829093915\n ],\n [\n -90.17578124999999,\n 44.33956524809713\n ],\n [\n -89.384765625,\n 46.558860303117164\n ],\n [\n -92.900390625,\n 46.49839225859763\n ],\n [\n -93.955078125,\n 47.69497434186282\n ],\n [\n -96.767578125,\n 46.01222384063236\n ],\n [\n -103.18359375,\n 48.69096039092549\n ],\n [\n -109.86328125,\n 49.15296965617042\n ],\n [\n -112.06054687499999,\n 48.980216985374994\n ],\n [\n -112.763671875,\n 48.86471476180277\n ],\n [\n -112.412109375,\n 47.754097979680026\n ],\n [\n -111.97265625,\n 46.31658418182218\n ],\n [\n -112.32421875,\n 45.398449976304086\n ],\n [\n -113.5546875,\n 45.460130637921004\n ],\n [\n -111.796875,\n 44.08758502824516\n ],\n [\n -108.369140625,\n 42.16340342422401\n ],\n [\n -105.46875,\n 41.50857729743935\n ],\n [\n -105.29296874999999,\n 39.90973623453719\n ],\n [\n -105.8203125,\n 39.436192999314095\n ],\n [\n -105.29296874999999,\n 38.54816542304656\n ],\n [\n -104.58984375,\n 36.31512514748051\n ],\n [\n -105.1171875,\n 35.88905007936091\n ],\n [\n -105.29296874999999,\n 35.38904996691167\n ],\n [\n -103.095703125,\n 32.84267363195431\n ],\n [\n -99.931640625,\n 32.175612478499325\n ],\n [\n -95.625,\n 31.653381399664\n ],\n [\n -93.955078125,\n 31.052933985705163\n ],\n [\n -93.955078125,\n 29.458731185355344\n ],\n [\n -90.52734374999999,\n 28.459033019728043\n ],\n [\n -88.857421875,\n 28.536274512989916\n ],\n [\n -88.59374999999999,\n 30.14512718337613\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Midcontinent Regional Director’s Office
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
To assess changes in substrate conditions and the efficacy of artificially placed substrates at select sites on the Kootenai River near Bonners Ferry, Idaho, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, completed repeat bathymetric, velocimetric, and underwater videography surveys. Collectively, three project sites throughout the Kootenai River make up the Substrate Enhancement Pilot Project (SEPP), an effort intended to improve spawning and egg incubation viability at locations identified to be aquatic habitat limited for the endangered Kootenai River white sturgeon (Acipenser transmontanus). Following the placement of coarse substrates at each site, bathymetric, velocimetric, and underwater videography data were collected from 2012 to 2022 to assess the role of deposition and erosion on maintaining suitable white sturgeon spawning and incubation substrates. Minimal erosion and deposition occurred at all Substrate Enhancement Pilot Project sites, according to interannual and intra-annual net volumetric changes between bathymetric surveys. Depending on the timing of bathymetric surveys relative to the annual peak streamflow conditions, isolated locations of deposition or erosion were observed at each site and the potential for deposition or erosion was supported by measured mean depth-averaged velocities. This study concluded that variability of deposition and scour were common at each site throughout the monitoring period and may be attributed to fluctuations in streamflow. Repeat bathymetric, underwater videography, and velocity mapping surveys were used to verify the interstitial spaces and surfaces of substrates at each SEPP site remained free of fine sediments for intervals longer than a year but were susceptible to deposition between high streamflow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245070","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Dudunake, T.J., 2024, Substrate Enhancement Pilot Project—Monitoring summary and evaluation, Kootenai River, Idaho, 2012–22 (ver. 1.1, March 6, 2025): U.S. Geological Survey Scientific Investigations Report 2024–5070, 18 p., https://doi.org/10.3133/sir20245070.","productDescription":"Report: vii, 18 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150368","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":492698,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117304.htm","linkFileType":{"id":5,"text":"html"}},{"id":433328,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC824R","text":"USGS data release","description":"USGS data release","linkHelpText":"Kootenai river substrate enhancement pilot projects near Bonners Ferry, ID (ver. 3.0, January 2023)"},{"id":433326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5070"},{"id":433325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5070/coverthb.jpg"},{"id":433330,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.XML"},{"id":483010,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5070/VersionHistory.txt","description":"Version History"},{"id":433329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5070/images"},{"id":433332,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245070/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5070"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.10215863331214,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.646078728701696\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 29, 2024; Version 1.1: March 6, 2025","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Paleoenvironmental data are essential for reconstructing environmental conditions in the distant past, and these reconstructions strongly depend on proxies and age–depth models. Proxies are indirect measurements that substitute for variables that cannot be directly measured, such as past precipitation. Conversely, an age–depth model is a tool that correlates the observed proxy with a specific moment in time. Bayesian age–depth modelling has proved to be a powerful method for estimating sediment ages and their associated uncertainties. However, there remains considerable potential for further integration into proxy analysis. In this paper, we explore a mathematical justification and a computational approach that integrates uncertainty at the age–depth level and propagates it to the proxy scale in the form of a posterior predictive distribution. This method mitigates potential biases and errors by removing the need to assign a single age to a given proxy measurement. It allows for quantifying the likelihood that proxy data values correspond to modelled ages, thus enabling the quantification of uncertainty in both the temporal and proxy value domains. The use of Bayesian statistics in proxy analysis represents a relatively recent advancement. We aim to mathematically justify incorporating the Markov chain Monte Carlo output from age–depth models into proxy analysis and to present a novel methodology for constructing environmental reconstructions using this approach.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-024-00647-5","usgsCitation":"Aquino-Lopez, M.A., Anderson, L., Sanchez-Cabeza, J., Ruiz-Fernandez, A.C., and Christen, J.A., 2024, Bayesian approaches to proxy uncertainty quantification in paleoecology: A mathematical justification and practical integration: Journal of Agricultural, Biological and Environmental Statistics, v. 31, p. 162-175, https://doi.org/10.1007/s13253-024-00647-5.","productDescription":"14 p.","startPage":"162","endPage":"175","ipdsId":"IP-153062","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":463766,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466943,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s13253-024-00647-5","text":"Publisher Index Page"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2024-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Aquino-Lopez, Marco A.","contributorId":346064,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","email":"","middleInitial":"A.","affiliations":[{"id":82759,"text":"Cabridge University, UK","active":true,"usgs":false}],"preferred":false,"id":917924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanchez-Cabeza, Joan-Albert","contributorId":346065,"corporation":false,"usgs":false,"family":"Sanchez-Cabeza","given":"Joan-Albert","email":"","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruiz-Fernandez, Ana Carolina","contributorId":346066,"corporation":false,"usgs":false,"family":"Ruiz-Fernandez","given":"Ana","email":"","middleInitial":"Carolina","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christen, J. Andres","contributorId":346067,"corporation":false,"usgs":false,"family":"Christen","given":"J.","email":"","middleInitial":"Andres","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917928,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257885,"text":"70257885 - 2024 - Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","interactions":[],"lastModifiedDate":"2024-08-30T12:26:31.615205","indexId":"70257885","displayToPublicDate":"2024-08-29T07:24:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","docAbstract":"In freshwater forested wetlands, bald cypress knees (Taxodium distichum (L.) Rich.) have the potential to emit large amounts of methane (CH4), but only a few studies have examined their greenhouse gas contribution. In this study, we measured CH4 fluxes associated with cypress knees across various climate and flooding gradients of the Mississippi River Alluvial Valley in southcentral United States. Greenhouse gases were measured using a portable gas analyzer with a custom-made chamber placed over the knees. We also conducted 3D lidar scans of knees using a smartphone to estimate the surface area and volume of knees. We investigated the following: (1) What parameters influence CH4 fluxes (i.e., knee height, distance to stream, temperature, relative humidity, water level, precipitation)? and (2) Which type of knee shape measurement (i.e., cone, frustrum, or lidar scan) provides the best fit to model data while maximizing measurement efficiency? We found that knee CH4 flux rates ranged from − 0.005 to 182 mmol m− 2 d− 1. There were positive correlations between CH4 fluxes, water levels, and temperature, and a negative correlation with knee height. Sites that had been dry for longer periods of time emitted less CH4 than sites where the soil remained saturated. The frustrum shape produced a knee volume estimate that was within 12% of lidar scans, whereas cone shapes underestimate knee dimensions (-100%). Further research of emissions and fluxes in cypress knees could fill knowledge gaps within the carbon cycle and could represent a major component of wetland CH4 budgets.
Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.
Climate change is expected to influence aquatic habitats and associated fish populations, yet we know little about the impact on recreational anglers. Our goal was to explore whether interannual fluctuations in waterbody surface area and other explanatory variables could be used as indicators of changes in angler fishing effort. Our approach leveraged a combination of remotely sensed waterbody surface area, environmental and fish population data, and onsite angler survey monitoring data for Devils Lake, North Dakota, USA during the open-water fishing period (May 1st to August 31st) for 9 years (1992–2021). The information was used to develop a dynamic waterbody size-angler effort model. Changes in waterbody surface area reliably predicted changes in angler effort (r2 = 0.60). Increases in waterbody surface area led to increases in angler effort, and decreases in waterbody surface area led to decreases in angler effort. Our findings show promise that remotely sensed fluctuations in waterbody surface area could be used as an indicator of interannual angler effort dynamics. Dynamic waterbody size-angler effort models could provide managers the ability to predict changes in angler effort via climate-related hydrological cycles that affect the size and distribution of waterbodies on the landscape.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107156","usgsCitation":"Maldonado, M., Mahmood, T., Coulter, D., Coulter, A., Chipps, S.R., Siller, M., Neal, M., Saha, A., and Kaemingk, M., 2024, Water-level changes impact angler effort in a large lake: Implications for climate change: Fisheries Research, v. 279, 107156, 5 p., https://doi.org/10.1016/j.fishres.2024.107156.","productDescription":"107156, 5 p.","ipdsId":"IP-160734","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.fishres.2024.107156","text":"Publisher Index Page"},{"id":466011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Devils Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.36050675879237,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 48.39597416139583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"279","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maldonado, Matthew L.","contributorId":347887,"corporation":false,"usgs":false,"family":"Maldonado","given":"Matthew L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahmood, Taufique H.","contributorId":347888,"corporation":false,"usgs":false,"family":"Mahmood","given":"Taufique H.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, David P.","contributorId":347889,"corporation":false,"usgs":false,"family":"Coulter","given":"David P.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coulter, Alison A.","contributorId":347890,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922734,"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":922735,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siller, Maddy K.","contributorId":347891,"corporation":false,"usgs":false,"family":"Siller","given":"Maddy K.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neal, Michaela L.","contributorId":347892,"corporation":false,"usgs":false,"family":"Neal","given":"Michaela L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922737,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saha, Ayon","contributorId":347893,"corporation":false,"usgs":false,"family":"Saha","given":"Ayon","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922738,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kaemingk, Mark A.","contributorId":347895,"corporation":false,"usgs":false,"family":"Kaemingk","given":"Mark A.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922739,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261511,"text":"70261511 - 2024 - Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","interactions":[],"lastModifiedDate":"2024-12-12T15:26:18.641308","indexId":"70261511","displayToPublicDate":"2024-08-28T09:18:13","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"displayTitle":"Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","title":"Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","docAbstract":"The Eastern box turtle (Terrapene carolina carolina) population at the Jug Bay Wetlands Sanctuary, Lothian, MD has been monitored continuously for 29 years (1995-2023). We used open population capture-recapture models (Jolly-Seber) to estimate annual population size, survival probability, and recruitment rate. The model allows for unknown sex of individuals and includes information on individuals found dead. Our analysis documents a long-term decline of approximately 67% in box turtle population size at the Sanctuary over this nearly three-decade period. We estimate annual survival for both males and females, which does not show a systematic increase or decrease over time, averaging about 0.90 (95% CI: 0.86, 0.93) for females and 0.97 (95% CI: 0.94, 0.98) for males. Conversely, per-capita recruitment shows a marked decline over the first 15 years of the record, suggesting that population declines may be due to reduced recruitment. Conservation efforts for the species could benefit from a formal population viability analysis to understand the relative effects of survival and recruitment on changes in population size for this long-lived species.
","language":"English","publisher":"BioaRxiv","doi":"10.1101/2024.08.28.610102","usgsCitation":"Royle, A., Quinlan, M., and Swarth, C., 2024, Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland: BioRxiv, https://doi.org/10.1101/2024.08.28.610102.","productDescription":"22 p.","ipdsId":"IP-164958","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466948,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.08.28.610102","text":"External Repository"},{"id":465062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":920842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinlan, Mike","contributorId":347120,"corporation":false,"usgs":false,"family":"Quinlan","given":"Mike","email":"","affiliations":[{"id":83074,"text":"Jug Bay Wetlands Sanctuary","active":true,"usgs":false}],"preferred":false,"id":920843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarth, Christopher","contributorId":347121,"corporation":false,"usgs":false,"family":"Swarth","given":"Christopher","email":"","affiliations":[{"id":83075,"text":"no affiliations","active":true,"usgs":false}],"preferred":false,"id":920844,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259258,"text":"70259258 - 2024 - From field station to forecast: Managing data at the Alaska Volcano Observatory","interactions":[],"lastModifiedDate":"2024-10-02T14:06:15.606438","indexId":"70259258","displayToPublicDate":"2024-08-28T08:56:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"From field station to forecast: Managing data at the Alaska Volcano Observatory","docAbstract":"The Alaska Volcano Observatory (AVO) uses multidisciplinary data to monitor and study dozens of active and potentially active volcanoes. Here, we provide an overview of internally and externally generated data types, tools and resources used in their management, and challenges faced. Data sources include the following: (1) a multiparameter (seismic, infrasound, GNSS, web cameras) ground-based monitoring network that spans 3000 km and transmits data in real time; (2) a variety of satellite-borne sensors that provide information about surface change and volcanic emissions; (3) geologic and gas field campaigns; and (4) other external data products that provide situation awareness. Each data type requires distinct acquisition, processing, storage, visualization, and archiving approaches. AVO uses a variety of externally and internally developed tools to handle individual data types as well as multidisciplinary volcanological data. A primary tool is the Geologic Database of Information on Volcanoes in Alaska (GeoDIVA), which stores detailed, searchable information on more than 140 volcanoes and over 1000 eruptions and unrest events, including images, eruption descriptions, and geologic station and sample data, metadata, and analyses. It interacts with other internal tools that store monitoring reports and other operational records. Additional data management resources used by AVO assist with alarms and alerts, state-of-health monitoring, and multiparameter visualization. Requirements for 24/7 accessibility, the ever-expanding portfolio of data, and transitioning new tools from development to operations are all challenges faced by AVO and other volcano observatories. AVO strives to meet FAIR data practices and ensure that data are available to national and international community efforts using external repositories as well as those hosted by AVO and its parent institutions.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-024-01766-0","usgsCitation":"Coombs, M.L., Cameron, C., Dietterich, H., Boyce, E., Wech, A., Grapenthin, R., Wallace, K.L., Parker, T., Lopez, T., Crass, S., Fee, D., Haney, M.M., Ketner, D.M., Loewen, M.W., Lyons, J.J., Nakai, J.S., Power, J., Botnick, S.M., Brewster, I., Enders, M.L., Harmon, D., Kelly, P.J., and Randall, M., 2024, From field station to forecast: Managing data at the Alaska Volcano Observatory: Bulletin of Volcanology, v. 86, 79, 22 p., https://doi.org/10.1007/s00445-024-01766-0.","productDescription":"79, 22 p.","ipdsId":"IP-163867","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":914590,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914591,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Randall, Michael J. 0000-0001-7750-9612","orcid":"https://orcid.org/0000-0001-7750-9612","contributorId":44819,"corporation":false,"usgs":true,"family":"Randall","given":"Michael J.","affiliations":[],"preferred":false,"id":914592,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70258798,"text":"70258798 - 2024 - Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","interactions":[],"lastModifiedDate":"2024-09-26T13:48:12.795406","indexId":"70258798","displayToPublicDate":"2024-08-28T08:44:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","title":"Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","docAbstract":"Large mammals with general habitat needs can persist throughout mixed used landscapes, however, human-wildlife conflict frequently leads to their restriction to protected areas. Conservation efforts, especially for reducing conflicts with humans, can enhance tolerance of humans towards species like Asian elephants (Elephas maximus) in human-dominated landscapes. Here, we examine how elephant use in the Chure Terai Madhesh Landscape (CTML) covering the entire elephant range of Nepal changed between 2012 and 2020 in relationship to protection status and environmental conditions. We systematically surveyed ~ 42,000 km2 of potential habitat, by dividing the study area into 159 grid cells of 15 × 15 km2 and recorded elephant signs during the cool, dry season in three years (2012, 2018 and 2020). We analyzed the survey data in a single-species, multi-season (dynamic) occupancy modeling framework to test hypotheses regarding the influence of environmental conditions and protected area status on landscape use by elephants over time. The best-supported model included protected area effects on initial use, colonization, and detection probability as well as temporal variation in colonization and detection probability. Initial use and colonization rates were higher in protected areas, however elephants increasingly used cells located both inside and outside the protected areas, and the difference in use between protected areas and outside declined as elephants use became prevalent across most of the landscape. While elephant use was patchily distributed in the first year of surveys consistent with past descriptions of four sub-populations, elephant use consolidated into a western and eastern region in subsequent years with a gap in their distribution occurring between Chitwan and Bardiya National Parks. Our manuscript highlights the increasing landscape use by elephants in both protected areas and areas outside protected areas and suggests that management interventions that focus on reducing conflicts can promote greater use of both protected areas and areas outside of protected areas.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-70092-4","usgsCitation":"Ram, A.K., Lamichhane, B.R., Subedi, N., Yadav, N.K., Karki, A., Pandav, B., Brown, C., Khatri, T.B., and Yackulic, C., 2024, Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal: Scientific Reports, v. 14, 20023, 9 p., https://doi.org/10.1038/s41598-024-70092-4.","productDescription":"20023, 9 p.","ipdsId":"IP-160993","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":466949,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-70092-4","text":"Publisher Index Page"},{"id":462277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[88.12044,27.87654],[88.04313,27.44582],[88.1748,26.81041],[88.06024,26.41462],[87.22747,26.3979],[86.02439,26.63098],[85.25178,26.7262],[84.67502,27.2349],[83.30425,27.36451],[81.99999,27.92548],[81.0572,28.4161],[80.08842,28.79447],[80.47672,29.72987],[81.11126,30.18348],[81.5258,30.42272],[82.32751,30.11527],[83.33712,29.46373],[83.89899,29.32023],[84.23458,28.83989],[85.01164,28.64277],[85.82332,28.20358],[86.95452,27.97426],[88.12044,27.87654]]]},\"properties\":{\"name\":\"Nepal\"}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ram, Ashok Kumar","contributorId":344543,"corporation":false,"usgs":false,"family":"Ram","given":"Ashok","email":"","middleInitial":"Kumar","affiliations":[{"id":82383,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamichhane, Babu Ram","contributorId":201694,"corporation":false,"usgs":false,"family":"Lamichhane","given":"Babu","email":"","middleInitial":"Ram","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Subedi, Naresh","contributorId":201695,"corporation":false,"usgs":false,"family":"Subedi","given":"Naresh","email":"","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yadav, Nabin Kumar","contributorId":344544,"corporation":false,"usgs":false,"family":"Yadav","given":"Nabin","email":"","middleInitial":"Kumar","affiliations":[{"id":82385,"text":"Ministry of Forests and Environment, Madhesh Pradesh, Janakpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karki, Ajay","contributorId":344545,"corporation":false,"usgs":false,"family":"Karki","given":"Ajay","email":"","affiliations":[{"id":82383,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pandav, Bivash","contributorId":344546,"corporation":false,"usgs":false,"family":"Pandav","given":"Bivash","email":"","affiliations":[{"id":82387,"text":"Wildlife Institute of India, Dehradun","active":true,"usgs":false}],"preferred":false,"id":914077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Cory","contributorId":344547,"corporation":false,"usgs":false,"family":"Brown","given":"Cory","email":"","affiliations":[{"id":82388,"text":"US Fish and Wildlife Service, Washington D.C., USA","active":true,"usgs":false}],"preferred":false,"id":914078,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khatri, Top B.","contributorId":344548,"corporation":false,"usgs":false,"family":"Khatri","given":"Top","email":"","middleInitial":"B.","affiliations":[{"id":82389,"text":"Ecosystem Based Adaptation Program (EBA) II, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914079,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914080,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}