{"pageNumber":"77","pageRowStart":"1900","pageSize":"25","recordCount":40754,"records":[{"id":70263625,"text":"70263625 - 2024 - Why do seismic hazard models worldwide appear to overpredict historical intensity observations?","interactions":[],"lastModifiedDate":"2025-02-18T15:27:18.152919","indexId":"70263625","displayToPublicDate":"2024-05-01T08:19:49","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Why do seismic hazard models worldwide appear to overpredict historical intensity observations?","docAbstract":"<p><span>Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models—which forecast shaking as peak ground acceleration or velocity—and observations—parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes.</span></p>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.adj9291","usgsCitation":"Salditch, L.M., Gallahue, M.M., Stein, S., Neely, J.S., Abrahamson, N., and Hough, S.E., 2024, Why do seismic hazard models worldwide appear to overpredict historical intensity observations?: Science Advances, v. 10, no. 18, eadj9291, 6 p., https://doi.org/10.1126/sciadv.adj9291.","productDescription":"eadj9291, 6 p.","ipdsId":"IP-155475","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":489938,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adj9291","text":"Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":927601,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":927603,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927604,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70257438,"text":"70257438 - 2024 - Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology","interactions":[],"lastModifiedDate":"2024-08-16T12:24:55.911749","indexId":"70257438","displayToPublicDate":"2024-05-01T07:23:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology","docAbstract":"<div id=\"143376043\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><div id=\"143376043\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>The Atlantic and Gulf Coastal Plains (CPs) are characterized by widespread accumulations of low-velocity sediments and sedimentary rock that overlay high-velocity bedrock. Geology and sediment thickness greatly influence seismic wave propagation, but current regional ground motion amplification and seismic hazard models include limited characterization of these site conditions. In this study, a new regional seismic velocity model for the CPs is created by integrating shear wave velocity (V<sub>S</sub>) measurements, surface geology, and a sediment thickness model recently developed for the CPs. A reference rock V<sub>S</sub><span>&nbsp;</span>of 3000 m/s has been assumed at the bottom of the sedimentary columns, which corresponds to the base of Cretaceous and Mesozoic sediments underlying the Atlantic CP and the Gulf CP, respectively. Measured V<sub>S</sub><span>&nbsp;</span>profiles located throughout the CPs are sorted into five geologic groups of varying age, and median V<sub>S</sub><span>&nbsp;</span>profiles are developed for each group by combining measured V<sub>S</sub><span>&nbsp;</span>values within layer thicknesses defined by an assumed layering ratio. Statistical analyses are also conducted to test the appropriateness of the selected groups. A power law model with geology-informed coefficients is used to extend the median velocity models beyond the depths where measured data were available. The median V<sub>S</sub><span>&nbsp;</span>profiles provide reasonable agreement with other generic models applicable for the region, but they also incorporate new information that enables more advanced characterizations of site response at regional scales and their effective incorporation into seismic hazard models and building codes. The proposed median velocity profiles can be assigned within a grid-based model of the CPs according to the spatial distribution of geologic units at the surface.</p></div><div id=\"articlefulltext_figshare\" class=\"figshare-wrapper\" data-widgetname=\"filesViewerGeneric\" data-showstats=\"True\" data-showpageinfo=\"False\" data-showsharebutton=\"True\" data-showfiledetails=\"False\" data-loaddoisbycollection=\"False\"><br></div></div><div id=\"articlefulltext_figshare\" class=\"figshare-wrapper\" data-widgetname=\"filesViewerGeneric\" data-showstats=\"True\" data-showpageinfo=\"False\" data-showsharebutton=\"True\" data-showfiledetails=\"False\" data-loaddoisbycollection=\"False\"><br></div>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930231222960","usgsCitation":"Gann-Phillips, C., Cabas, A., Ji, C., Cramer, C.H., Kaklamanos, J., and Boyd, O.S., 2024, Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology: Earthquake Spectra, v. 40, no. 2, p. 1269-1300, https://doi.org/10.1177/87552930231222960.","productDescription":"32 p.","startPage":"1269","endPage":"1300","ipdsId":"IP-154152","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":432854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Gann-Phillips, Cassie","contributorId":342803,"corporation":false,"usgs":false,"family":"Gann-Phillips","given":"Cassie","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":910403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cabas, Ashly 0000-0002-1039-4053","orcid":"https://orcid.org/0000-0002-1039-4053","contributorId":342804,"corporation":false,"usgs":false,"family":"Cabas","given":"Ashly","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":910404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ji, Chunyang","contributorId":342806,"corporation":false,"usgs":false,"family":"Ji","given":"Chunyang","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":910405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cramer, Chris H.","contributorId":194851,"corporation":false,"usgs":false,"family":"Cramer","given":"Chris","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":910406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaklamanos, James 0000-0001-7480-0391","orcid":"https://orcid.org/0000-0001-7480-0391","contributorId":342809,"corporation":false,"usgs":false,"family":"Kaklamanos","given":"James","email":"","affiliations":[{"id":81933,"text":"Merrimack College","active":true,"usgs":false}],"preferred":false,"id":910407,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":910408,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70254150,"text":"70254150 - 2024 - Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models","interactions":[],"lastModifiedDate":"2024-05-09T11:51:29.615368","indexId":"70254150","displayToPublicDate":"2024-05-01T06:47:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models","docAbstract":"<div class=\"JournalAbstract\"><p>The Statewide (formerly Southern) California Earthquake Center (SCEC) conducts multidisciplinary earthquake system science research that aims to develop predictive models of earthquake processes, and to produce accurate seismic hazard information that can improve societal preparedness and resiliency to earthquake hazards. As part of this program, SCEC has developed the CyberShake platform, which calculates physics-based probabilistic seismic hazard analysis (PSHA) models for regions with high-quality seismic velocity and fault models. The CyberShake platform implements a sophisticated computational workflow that includes over 15 individual codes written by 6 developers. These codes are heterogeneous, ranging from short-running high-throughput serial CPU codes to large, long-running, parallel GPU codes. Additionally, CyberShake simulation campaigns are computationally extensive, typically producing tens of terabytes of meaningful scientific data and metadata over several months of around-the-clock execution on leadership-class supercomputers. To meet the needs of the CyberShake platform, we have developed an extreme-scale workflow stack, including the Pegasus Workflow Management System, HTCondor, Globus, and custom tools. We present this workflow software stack and identify how the CyberShake platform and supporting tools enable us to meet a variety of challenges that come with large-scale simulations, such as automated remote job submission, data management, and verification and validation. This platform enabled us to perform our most recent simulation campaign, CyberShake Study 22.12, from December 2022 to April 2023. During this time, our workflow tools executed approximately 32,000 jobs, and used up to 73% of the<span>&nbsp;</span><i>Summit</i><span>&nbsp;</span>system at Oak Ridge Leadership Computing Facility. Our workflow tools managed about 2.5 PB of total temporary and output data, and automatically staged 19 million output files totaling 74 TB back to archival storage on the University of Southern California's Center for Advanced Research Computing systems, including file-based relational data and large binary files to efficiently store millions of simulated seismograms. CyberShake extreme-scale workflows have generated simulation-based probabilistic seismic hazard models that are being used by seismological, engineering, and governmental communities.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fhpcp.2024.1360720","usgsCitation":"Callaghan, S., Maechling, P.J., Silva, F., Su, M., Milner, K.R., Graves, R., Olsen, K., Cui, Y., Vahi, K., Kottke, A., Goulet, C.A., Deelman, E., Jordan, T., and Ben-Zion, Y., 2024, Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models: Frontiers Earth Science Journal, v. 2, 1360720, 21 p., https://doi.org/10.3389/fhpcp.2024.1360720.","productDescription":"1360720, 21 p.","ipdsId":"IP-161963","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":439691,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fhpcp.2024.1360720","text":"Publisher Index Page"},{"id":428582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","noUsgsAuthors":false,"publicationDate":"2024-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Callaghan, Scott","contributorId":195136,"corporation":false,"usgs":false,"family":"Callaghan","given":"Scott","email":"","affiliations":[],"preferred":false,"id":900434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maechling, Phillip J.","contributorId":117072,"corporation":false,"usgs":false,"family":"Maechling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":900435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silva, Fabio","contributorId":264130,"corporation":false,"usgs":false,"family":"Silva","given":"Fabio","email":"","affiliations":[{"id":54387,"text":"SCEC","active":true,"usgs":false}],"preferred":false,"id":900436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Su, Mei-Hui","contributorId":336583,"corporation":false,"usgs":false,"family":"Su","given":"Mei-Hui","email":"","affiliations":[{"id":54387,"text":"SCEC","active":true,"usgs":false}],"preferred":false,"id":900437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":900438,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":900439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Olsen, Kim","contributorId":117549,"corporation":false,"usgs":false,"family":"Olsen","given":"Kim","email":"","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":900440,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cui, Yifeng","contributorId":336585,"corporation":false,"usgs":false,"family":"Cui","given":"Yifeng","email":"","affiliations":[{"id":80793,"text":"SDSC","active":true,"usgs":false}],"preferred":false,"id":900441,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vahi, Karan","contributorId":336586,"corporation":false,"usgs":false,"family":"Vahi","given":"Karan","email":"","affiliations":[{"id":80794,"text":"ISI","active":true,"usgs":false}],"preferred":false,"id":900442,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kottke, Albert","contributorId":140539,"corporation":false,"usgs":false,"family":"Kottke","given":"Albert","affiliations":[],"preferred":false,"id":900443,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Goulet, Christine A 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":336587,"corporation":false,"usgs":true,"family":"Goulet","given":"Christine","email":"","middleInitial":"A","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":900444,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Deelman, Ewa","contributorId":336588,"corporation":false,"usgs":false,"family":"Deelman","given":"Ewa","email":"","affiliations":[{"id":80794,"text":"ISI","active":true,"usgs":false}],"preferred":false,"id":900445,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jordan, Tom","contributorId":336589,"corporation":false,"usgs":false,"family":"Jordan","given":"Tom","affiliations":[{"id":47795,"text":"USC","active":true,"usgs":false}],"preferred":false,"id":900446,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ben-Zion, Yehuda","contributorId":195741,"corporation":false,"usgs":false,"family":"Ben-Zion","given":"Yehuda","email":"","affiliations":[{"id":16177,"text":"University of Southern California, Los Angeles, Ca.","active":true,"usgs":false}],"preferred":false,"id":900447,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70267274,"text":"70267274 - 2024 - Integration of rupture directivity models for the US National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2025-05-19T17:35:40.050468","indexId":"70267274","displayToPublicDate":"2024-05-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Integration of rupture directivity models for the US National Seismic Hazard Model","docAbstract":"<p>Several rupture directivity models (DMs) have been developed in recent years to describe the near-source spatial variations in ground motion amplitudes related to propagation of rupture along the fault. We recently organized an effort towards incorporating these directivity effects into the USGS National Seismic Hazard Model (NSHM), by first evaluating the community's work and potential methods to implement directivity adjustments into probabilistic seismic hazard analysis (PSHA). Guided by this evaluation and comparison among the considered DMs, we selected an approach that can be readily implemented into the USGS hazard software, that provides an azimuthally varying adjustment to the median ground motion and its aleatory variability. This method allows assessment of the impact on hazard levels and provides a platform to test the DM amplification predictions using a generalized coordinate system, necessary for consistent calculation of source-to-site distance terms for complex ruptures. We give examples of the directivity-related impact on hazard, progressing from a simple, hypothetical rupture, to more complex fault systems, composed of multiple rupture segments and sources. The directivity adjustments were constrained to strike-slip faulting, where DMs have good agreement. We find that rupture directivity adjustments using a simple median and aleatory adjustment approach can impact hazard both from a site perspective and on a regional scale, increasing shaking off the end of the fault trace up to 30--40\\% and potentially reducing it for sites along strike. Statewide hazard maps of California show that the change in shaking along major faults can be a factor to consider for assessing long-period (&gt;ls)&nbsp;near-source effects within the USGS NSHM going forward, reaching up to 10--20\\%. Finally, we suggest consideration of minimum parameter ranges and baseline requirements as future DMs are developed to minimize single approach adaptations, to enable more consistent application within both ground motion and hazard studies.</p>","language":"English","publisher":"Sage","doi":"10.1177/87552930241232708","usgsCitation":"Withers, K., Moschetti, M.P., Powers, P.M., Petersen, M.D., Graves, R., Aagaard, B.T., Baltay Sundstrom, A.S., Luco, N., Wirth, E.A., Rezaeian, S., and Thompson, E.M., 2024, Integration of rupture directivity models for the US National Seismic Hazard Model: Earthquake Spectra, v. 40, no. 2, p. 1066-1098, https://doi.org/10.1177/87552930241232708.","productDescription":"33 p.","startPage":"1066","endPage":"1098","ipdsId":"IP-153605","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":490134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70253244,"text":"tm7A3 - 2024 - Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities","interactions":[],"lastModifiedDate":"2024-12-03T19:57:00.75842","indexId":"tm7A3","displayToPublicDate":"2024-04-30T16:58:47","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-A3","displayTitle":"Accounting for the Fraction of Carcasses Outside the Searched Area in the Estimation of Bird and Bat Fatalities at Wind Energy Facilities","title":"Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities","docAbstract":"<p>Accurate estimation of bird and bat mortality at wind energy facilities requires accounting for carcasses that lie outside the search plots because they lie beyond the search radius or in areas within the search radius that remain unsearched due to sub-optimal search conditions such as thick vegetation, rough or dangerous ground, water, or restricted access to the land. However, carcass density is not constant around a turbine and the fraction of carcasses within the unsearched area can vary greatly depending on where the area lies relative to the turbine. The density-weighted proportion approach takes into account the changing density of carcasses around turbines to estimate the fraction of carcasses lying in unsearched areas (dwp). It involves tallying the carcasses found in concentric rings centered at the turbine, fitting a curve to the carcass densities in the rings, and dividing the integral of the curve over the area searched by the integral over the total area. Accounting for unsearched area presents special difficulties such as extrapolation beyond the search radius, spatial prediction, and model selection, which are frequently ignored or under-appreciated, potentially resulting in substantial estimation errors.</p><p>A powerful new R software package (dwp) is available to perform the calculations, given the distances at which carcasses were found from turbines and a map of the searched area used to discern the fraction of the ground searched at each distance. If all ground within a given search radius has been searched, the map is simply the search radius. For more complicated search plots, other kinds of maps may be used: R polygons for plots that can be readily delineated into searched and not-searched areas (for example, searches restricted to access roads and turbine pads), GIS shape files for complicated search patterns (for example, non-uniform vegetation or ground texture resulting in spatially varying search conditions), or raster files for complicated search patterns coupled with carcass spatial distribution that depends on both distance and direction from turbines.</p><p>This study discusses estimation and interpretation of dwp in the context of several realistic examples; provides guidance for use of the dwp software for doing the analyses; and addresses questions of extrapolation, spatial prediction, and model selection.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7A3","usgsCitation":"Dalthorp, D., Huso, M., Dalthorp, M., and Mintz, J., 2024, Accounting for the fraction of carcasses outside the searched area in the estimation of bird and bat fatalities at wind energy facilities: U.S. Geological Survey Techniques and Methods, book 7, chap. A3, 104 p., https://doi.org/10.3133/tm7A3.","productDescription":"vii, 104 p.","onlineOnly":"Y","ipdsId":"IP-135475","costCenters":[],"links":[{"id":428248,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.XML"},{"id":428246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.jpg"},{"id":428247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/7a3/tm7A3.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7A3"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/forest-and-rangeland-ecosystem-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/forest-and-rangeland-ecosystem-science-center\">Forest and Rangeland Ecosystem Science Center</a><br>U.S. Geological Survey<br>777 NW 9th Street, Suite 400<br>Corvallis, Oregon 97330</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Overview</li><li>General Principles</li><li>The dwp Package</li><li>Examples</li><li>References Cited</li><li>Appendixes 1–5</li></ul>","publishedDate":"2024-04-30","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":899843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":899844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalthorp, Mark","contributorId":335937,"corporation":false,"usgs":false,"family":"Dalthorp","given":"Mark","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":899845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mintz, Jeffrey 0000-0003-4345-366X","orcid":"https://orcid.org/0000-0003-4345-366X","contributorId":210452,"corporation":false,"usgs":false,"family":"Mintz","given":"Jeffrey","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":899846,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70257360,"text":"70257360 - 2024 - Quantifying the relative importance of biotic and abiotic factors in landscape-based models of stream fish distributions","interactions":[],"lastModifiedDate":"2024-09-05T16:34:13.810348","indexId":"70257360","displayToPublicDate":"2024-04-30T11:27:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18519,"text":"Community Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the relative importance of biotic and abiotic factors in landscape-based models of stream fish distributions","docAbstract":"<p><span>Lotic fish species distributions are frequently predicted using remotely sensed habitat variables that characterize the adjacent landscape and serve as proxies for instream habitat. Recent advancements in statistical methodology, however, allow for leveraging fish assemblage data when predicting distributions. This is important because assemblage composition likely provides better information about instream habitat compared to landscape-derived metrics and therefore may improve predictions. To better understand the value of using multi-species fish data in species distribution modeling, we fit two conditional random fields (CRF) models to quantify the relative importance of fish assemblage co-occurrence, landscape-derived habitat variables, and interactions between these two predictor groups (i.e., effects of co-occurrence could be context-dependent) at over 1200 stream catchments in Pennsylvania, USA. We first compared predictive performance of CRF models against traditionally used single-species logistic regressions (generalized linear models; GLMs) and found that inclusion of fish assemblage data often improved predictive performance. The multi-species CRF models performed significantly better at predicting occurrence for 63% of species with an average percent increase in AUC of 25% compared to GLMs. Furthermore, the CRF identified species co-occurrences as more informative, and thus relatively more important, at predicting occurrence than the other effect types. The CRF also suggested that allowing these biotic effects to be context-dependent was important for predicting occurrence of many species. These findings illustrate the value of fish assemblage data for landscape-scale species distribution modeling and leveraging this information can improve predictions and inferences to help inform the management and conservation of freshwater fishes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s42974-024-00183-9","usgsCitation":"Custer, C., Fischer, D., Smith, G., Henning, A., Kepler Schall, M., Shank, M.K., Wertz, T.A., and Isermann, D.A., 2024, Quantifying the relative importance of biotic and abiotic factors in landscape-based models of stream fish distributions: Community Ecology, v. 25, p. 145-196, https://doi.org/10.1007/s42974-024-00183-9.","productDescription":"52 p.","startPage":"145","endPage":"196","ipdsId":"IP-147148","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s42974-024-00183-9","text":"Publisher Index Page"},{"id":433512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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A.","contributorId":342455,"corporation":false,"usgs":false,"family":"Wertz","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":910114,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910115,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70257781,"text":"70257781 - 2024 - Ancient permafrost and past permafrost in the Northern Hemisphere","interactions":[],"lastModifiedDate":"2024-08-27T14:13:01.25462","indexId":"70257781","displayToPublicDate":"2024-04-30T09:10:16","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Ancient permafrost and past permafrost in the Northern Hemisphere","docAbstract":"The existence and dynamics of permafrost depend on the prevailing climate conditions. Therefore, the study of ancient permafrost (existing since the Pleistocene or earlier) and past permafrost (Late Pleistocene or older permafrost that no longer exists) and their dynamics may inform about climate and environmental changes in the past. In this chapter, we provide a brief overview of characteristics, detection and dating methods of ancient and past permafrost, before presenting a spatial and temporal history of permafrost in the middle and high northern latitudes. While the first permafrost may have formed about 3 million years ago, the late Pliocene and Early Pleistocene were characterized by frequent thawing and new formation of permafrost. It was not until the Middle and Late Pleistocene that permafrost became more persistent and widespread due to prolonged cooling. The most ancient dated permafrost formed between 800 and 600 ka in Yukon/Canada and East Siberia. Interglacial warming after the last ice age has led to massive thawing of permafrost and large areas in Europe, Asia and America are now characterized by traces of past permafrost.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in Earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-99931-1.00258-0","usgsCitation":"Opel, T., Bertran, P., Grosse, G., Jones, M.C., Luetscher, M., Schirrmeister, L., Stadelmeier, K., and Veremeeva, A., 2024, Ancient permafrost and past permafrost in the Northern Hemisphere, chap. <i>of</i> Reference module in Earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-323-99931-1.00258-0.","productDescription":"HTML Document","ipdsId":"IP-164376","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":439707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-04581090","text":"External Repository"},{"id":433194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Hemisphere","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              89\n            ],\n            [\n              -179.9,\n              1\n            ],\n            [\n              179.9,\n              1\n            ],\n            [\n              179.9,\n              89\n            ],\n            [\n              -179.9,\n              89\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Opel, Thomas","contributorId":195054,"corporation":false,"usgs":false,"family":"Opel","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":911664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bertran, Pascal","contributorId":343679,"corporation":false,"usgs":false,"family":"Bertran","given":"Pascal","email":"","affiliations":[{"id":82154,"text":"Institut National de Recherches Archéologiques Préventives","active":true,"usgs":false}],"preferred":false,"id":911665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":911666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":911667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luetscher, Marc","contributorId":343680,"corporation":false,"usgs":false,"family":"Luetscher","given":"Marc","email":"","affiliations":[{"id":82157,"text":"Swiss Institute for Speleology and Karst Studies","active":true,"usgs":false}],"preferred":false,"id":911668,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schirrmeister, Lutz","contributorId":200976,"corporation":false,"usgs":false,"family":"Schirrmeister","given":"Lutz","email":"","affiliations":[],"preferred":false,"id":911669,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stadelmeier, Kim","contributorId":343681,"corporation":false,"usgs":false,"family":"Stadelmeier","given":"Kim","email":"","affiliations":[{"id":82158,"text":"Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research Troposphere Research (IMKTRO","active":true,"usgs":false}],"preferred":false,"id":911670,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veremeeva, Alexandra","contributorId":194028,"corporation":false,"usgs":false,"family":"Veremeeva","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":911671,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70253582,"text":"70253582 - 2024 - NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","interactions":[],"lastModifiedDate":"2024-05-02T13:42:54.186655","indexId":"70253582","displayToPublicDate":"2024-04-30T08:41:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps","docAbstract":"<p><span>Models of rocky-coast erosion help us understand the physical phenomena that control coastal morphology and evolution, infer the processes shaping coasts in remote environments, and evaluate risk from natural hazards and future climate change. Existing models, however, are highly complex, are computationally expensive, and depend on many input parameters; this limits our ability to explore planform erosion of rocky coasts over long timescales (thousands to millions of years) and over a range of conditions. In this paper, we present a simplified cellular model of coastline evolution in closed basins through uniform erosion and wave-driven erosion. Uniform erosion is modeled as a constant rate of retreat. Wave erosion is modeled as a function of fetch, the distance over which the wind blows to generate waves, and the angle between the incident wave and the shoreline. This reduced-complexity model can be used to evaluate how a detachment-limited coastal landscape reflects climate, sea-level history, material properties, and the relative influence of different erosional processes.</span></p>","language":"English","publisher":"Copernicus","doi":"10.5194/gmd-17-3433-2024","usgsCitation":"Palermo, R.E., Perron, J.T., Soderblom, J.M., Birch, S.P., Hayes, A.G., and Ashton, A.D., 2024, NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps: Geoscientific Model Development, v. 17, no. 8, p. 3433-3445, https://doi.org/10.5194/gmd-17-3433-2024.","productDescription":"13 p.","startPage":"3433","endPage":"3445","ipdsId":"IP-157241","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-17-3433-2024","text":"Publisher Index Page"},{"id":428321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Palermo, Rose Elizabeth 0000-0002-7438-361X","orcid":"https://orcid.org/0000-0002-7438-361X","contributorId":300046,"corporation":false,"usgs":true,"family":"Palermo","given":"Rose","email":"","middleInitial":"Elizabeth","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":899974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perron, J. Taylor","contributorId":184100,"corporation":false,"usgs":false,"family":"Perron","given":"J.","email":"","middleInitial":"Taylor","affiliations":[],"preferred":false,"id":899975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soderblom, Jason M.","contributorId":193866,"corporation":false,"usgs":false,"family":"Soderblom","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":899976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birch, Samuel P. D.","contributorId":202322,"corporation":false,"usgs":false,"family":"Birch","given":"Samuel","email":"","middleInitial":"P. D.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":899977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Alexander G.","contributorId":211180,"corporation":false,"usgs":false,"family":"Hayes","given":"Alexander","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":899978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ashton, Andrew D.","contributorId":300047,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":899979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70253227,"text":"sir20245025 - 2024 - Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","interactions":[],"lastModifiedDate":"2026-02-03T18:10:33.629761","indexId":"sir20245025","displayToPublicDate":"2024-04-30T07:15:01","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5025","displayTitle":"Simulation of Hydrodynamics and Water Temperature in a 21-Mile Reach of the Upper Illinois River, Illinois, 2020–22","title":"Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22","docAbstract":"<p>This report describes the development of a CE-QUAL-W2 river hydrodynamics and temperature model of a 21-mile reach of the Illinois River including a 3-mile reach of a major tributary, the Fox River. Model outputs consist of streamflow, water velocity, water-surface elevation, and water-temperature time series that can be used to simulate summer conditions in years with and without extensive development of harmful algal blooms (HABs). These analyses may provide a better understanding of some complex factors contributing to HAB development along the Illinois River. Such an understanding may provide more accurate HAB timing and location predictions and may help determine potential mitigating activities to prevent or limit the size and duration of HABs.</p><p>Using the observed and simulated hydrodynamic conditions in the Illinois River study reach, it was possible to compare and contrast streamflow, velocity, and temperature conditions in years with varying HAB distributions. Occurrences of extensive HABs were documented in the study reach in June 2020 and June 2021, but only a small HAB restricted to the Marseilles Lock and Dam pool occurred in the summer of 2022. The objective then was to find similarities in site conditions between 2020 and 2021 that may contrast with the conditions in 2022. Among the 3 years included in the study, the variability in simulated water temperature exceeded variability in observed streamflow and simulated velocities. The longest period of water temperatures greater than 27 degrees Celsius (°C) in the selected locations in June of the three analysis years was in the second half of June 2022, yet no study-area wide HAB was documented in 2022. Simulations indicated that after warm water temperatures were established in the reach in June 2022, a cooling period broke up the warming period. This period of cooling was greater in magnitude and duration downstream from the location of a localized HAB perhaps limiting the spread of the bloom.</p><p>Residence times differed substantially in segments representing different channel features; values ranged from 0.28 to 17.3 (days per 500 meters of channel) between the main stem and backwater areas, respectively. Variation in average June residence times was also greater among different channel features than among different years in the study period. The HABs in 2020 and 2021 at Starved Rock Dam were documented when water temperatures were about 26 °C. River backwater areas at some locations did attain these temperatures 2 to 3 days before the conditions in the main stem. Residence times in the backwater areas, however, generally exceeded 9 days, thus limiting the exchange of water carrying algal biomass into the main channel.</p><p>Hydrodynamic model calibration involved adjusting model parameters until observed and simulated daily water-surface elevations, daily streamflows, discrete velocities, and channel areas were similar. Temperature calibration was done with near-surface continuous time-series data and discrete vertical profile temperatures. Observed and simulated water temperatures generally were within 1 °C at all monitoring locations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245025","usgsCitation":"Ament, M.R., and Heimann, D.C., 2024, Simulation of hydrodynamics and water temperature in a 21-mile reach of the upper Illinois River, Illinois, 2020–22 (ver. 1.1, October 2024): U.S. Geological Survey Scientific Investigations Report 2024–5025, 35 p., https://doi.org/10.3133/sir20245025.","productDescription":"Report: viii, 35 p.; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-147887","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497947,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116400.htm","linkFileType":{"id":5,"text":"html"}},{"id":462442,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5025/versionHist.txt","size":"2.7 KB","linkFileType":{"id":2,"text":"txt"}},{"id":428192,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245025/full"},{"id":428191,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":428190,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BV9EG2","text":"USGS data release","linkHelpText":"Hydrodynamic and water-temperature model of a 21-mile reach of the upper Illinois River, Illinois (ver. 1.1, October 2024)"},{"id":428189,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5025/images/"},{"id":428186,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5025/coverthb2.jpg"},{"id":428187,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5025/sir20245025.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5025"},{"id":428188,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5025/sir20245025.XML"}],"country":"United States","state":"Illinois","otherGeospatial":"Upper Illinois River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.09651850759147,\n              41.39468681338917\n            ],\n            [\n              -89.09651850759147,\n              41.27302034876615\n            ],\n            [\n              -88.30008450383568,\n              41.27302034876615\n            ],\n            [\n              -88.30008450383568,\n              41.39468681338917\n            ],\n            [\n              -89.09651850759147,\n              41.39468681338917\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Version 1.0: April 30, 2024; Version 1.1: October 1, 2024","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>1400 Independence Road<br>Rolla, MO 65401</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Model Development and Calibration</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-04-30","revisedDate":"2024-10-01","noUsgsAuthors":false,"publicationDate":"2024-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ament, Michael R. 0000-0003-2715-6147","orcid":"https://orcid.org/0000-0003-2715-6147","contributorId":335922,"corporation":false,"usgs":true,"family":"Ament","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70254291,"text":"70254291 - 2024 - Challenges creating monarch butterfly management strategies for electric power companies in the United States","interactions":[],"lastModifiedDate":"2024-05-17T14:22:11.936823","indexId":"70254291","displayToPublicDate":"2024-04-29T09:15:29","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Challenges creating monarch butterfly management strategies for electric power companies in the United States","docAbstract":"<p><span>Returning monarch butterflies (</span><i>Danaus plexippus</i><span>) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2024.1360325","usgsCitation":"Fox, J., Allen, K., Diffendorfer, J., Lukens, L., Thogmartin, W.E., and Newman, C., 2024, Challenges creating monarch butterfly management strategies for electric power companies in the United States: Frontiers in Ecology and Evolution, v. 12, 1360325, 9 p., https://doi.org/10.3389/fevo.2024.1360325.","productDescription":"1360325, 9 p.","ipdsId":"IP-161359","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":439716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/fevo.2024.1360325","text":"Publisher Index 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]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fox, Jessica","contributorId":336721,"corporation":false,"usgs":false,"family":"Fox","given":"Jessica","email":"","affiliations":[{"id":80850,"text":"Electric Power Research Institute","active":true,"usgs":false}],"preferred":false,"id":900887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Kasey","contributorId":336722,"corporation":false,"usgs":false,"family":"Allen","given":"Kasey","email":"","affiliations":[{"id":80851,"text":"ICF Jones & Stokes, Inc","active":true,"usgs":false}],"preferred":false,"id":900888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":900889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lukens, Laura","contributorId":336723,"corporation":false,"usgs":false,"family":"Lukens","given":"Laura","affiliations":[{"id":80852,"text":"Monarch Joint Venture","active":true,"usgs":false}],"preferred":false,"id":900890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":900891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newman, Christian","contributorId":336724,"corporation":false,"usgs":false,"family":"Newman","given":"Christian","email":"","affiliations":[{"id":80850,"text":"Electric Power Research Institute","active":true,"usgs":false}],"preferred":false,"id":900892,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70253576,"text":"70253576 - 2024 - Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","interactions":[],"lastModifiedDate":"2024-07-01T14:41:54.77567","indexId":"70253576","displayToPublicDate":"2024-04-29T08:28:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework","docAbstract":"<p><span>An important provision of the Minamata Convention on Mercury is to monitor and evaluate the effectiveness of the adopted measures and its implementation. Here, we describe for the first time currently available biotic mercury (Hg) data on a global scale to improve the understanding of global efforts to reduce the impact of Hg pollution on people and the environment. Data from the peer-reviewed literature were compiled in the Global Biotic Mercury Synthesis (GBMS) database (&gt;550,000 data points). These data provide a foundation for establishing a biomonitoring framework needed to track Hg concentrations in biota globally. We describe Hg exposure in the taxa identified by the Minamata Convention: fish, sea turtles, birds, and marine mammals. Based on the GBMS database, Hg concentrations are presented at relevant geographic scales for continents and oceanic basins. We identify some effective regional templates for monitoring methylmercury (MeHg) availability in the environment, but overall illustrate that there is a general lack of regional biomonitoring initiatives around the world, especially in Africa, Australia, Indo-Pacific, Middle East, and South Atlantic and Pacific Oceans. Temporal trend data for Hg in biota are generally limited. Ecologically sensitive sites (where biota have above average MeHg tissue concentrations) have been identified throughout the world. Efforts to model and quantify ecosystem sensitivity locally, regionally, and globally could help establish effective and efficient biomonitoring programs. We present a framework for a global Hg biomonitoring network that includes a three-step continental and oceanic approach to integrate existing biomonitoring efforts and prioritize filling regional data gaps linked with key Hg sources. We describe a standardized approach that builds on an evidence-based evaluation to assess the Minamata Convention’s progress to reduce the impact of global Hg pollution on people and the environment.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10646-024-02747-x","usgsCitation":"Evers, D.C., Ackerman, J.T., Akerblom, S., Bally, D., Basu, N., Bishop, K., Bodin, N., Veitberg Braaten, H.F., Burton, M., Bustamante, P., Chen, C.Y., Chetelat, J., Christian, L., Dietz, R., Drevnick, P., Eagles-Smith, C., Fernandez, L., Hammerschlag, N., Harmelin-Vivien, M., Harte, A., Kruemmel, E., Lailson-Brito, J., Medina, G., Rodriguez, C., Stenhouse, I., Sunderland, E.M., Takeuchi, A., Tear, T., Vega, C., Wilson, S., and Wu, P., 2024, Global mercury concentrations in biota: Their use as a basis for a global biomonitoring framework: Ecotoxicology, v. 33, p. 325-396, https://doi.org/10.1007/s10646-024-02747-x.","productDescription":"72 p.","startPage":"325","endPage":"396","ipdsId":"IP-159055","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439720,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10646-024-02747-x","text":"Publisher Index Page"},{"id":428320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","noUsgsAuthors":false,"publicationDate":"2024-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Evers, David C.","contributorId":96160,"corporation":false,"usgs":false,"family":"Evers","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":899935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":899936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akerblom, Staffan 0000-0001-7607-9518","orcid":"https://orcid.org/0000-0001-7607-9518","contributorId":335950,"corporation":false,"usgs":false,"family":"Akerblom","given":"Staffan","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":899937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bally, Dominique","contributorId":335951,"corporation":false,"usgs":false,"family":"Bally","given":"Dominique","email":"","affiliations":[{"id":80590,"text":"African Center for Environmental Health","active":true,"usgs":false}],"preferred":false,"id":899938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Basu, Niladri","contributorId":60085,"corporation":false,"usgs":false,"family":"Basu","given":"Niladri","email":"","affiliations":[],"preferred":false,"id":899939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bishop, Kevin","contributorId":147940,"corporation":false,"usgs":false,"family":"Bishop","given":"Kevin","affiliations":[],"preferred":false,"id":899940,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bodin, Nathalie 0000-0001-8464-0213","orcid":"https://orcid.org/0000-0001-8464-0213","contributorId":335953,"corporation":false,"usgs":false,"family":"Bodin","given":"Nathalie","email":"","affiliations":[{"id":80591,"text":"Research Institute for Sustainable Development Seychelles Fishing Authority","active":true,"usgs":false}],"preferred":false,"id":899941,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veitberg Braaten, Hans Fredrik","contributorId":335954,"corporation":false,"usgs":false,"family":"Veitberg Braaten","given":"Hans","email":"","middleInitial":"Fredrik","affiliations":[{"id":13695,"text":"Norwegian Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":899942,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burton, Mark","contributorId":224999,"corporation":false,"usgs":false,"family":"Burton","given":"Mark","email":"","affiliations":[{"id":37436,"text":"Biodiversity Research Institute","active":true,"usgs":false}],"preferred":false,"id":899943,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bustamante, Paco","contributorId":201551,"corporation":false,"usgs":false,"family":"Bustamante","given":"Paco","email":"","affiliations":[{"id":36199,"text":"La Rochelle University","active":true,"usgs":false}],"preferred":false,"id":899944,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Chen, Celia Y.","contributorId":145630,"corporation":false,"usgs":false,"family":"Chen","given":"Celia","email":"","middleInitial":"Y.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":899945,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chetelat, John","contributorId":221830,"corporation":false,"usgs":false,"family":"Chetelat","given":"John","email":"","affiliations":[{"id":40438,"text":"Environment and Climate Change Canada, National Wildlife Research Centre","active":true,"usgs":false}],"preferred":false,"id":899946,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Christian, Linroy","contributorId":335955,"corporation":false,"usgs":false,"family":"Christian","given":"Linroy","email":"","affiliations":[{"id":80593,"text":"Antigua and Barbados Department of Analytical Services","active":true,"usgs":false}],"preferred":false,"id":899947,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dietz, Rune","contributorId":191799,"corporation":false,"usgs":false,"family":"Dietz","given":"Rune","email":"","affiliations":[],"preferred":false,"id":899948,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Drevnick, Paul","contributorId":168738,"corporation":false,"usgs":false,"family":"Drevnick","given":"Paul","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":899949,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":899950,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Fernandez, Luis","contributorId":335957,"corporation":false,"usgs":false,"family":"Fernandez","given":"Luis","email":"","affiliations":[{"id":36744,"text":"Wake Forest University","active":true,"usgs":false}],"preferred":false,"id":899951,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Hammerschlag, Neil","contributorId":213059,"corporation":false,"usgs":false,"family":"Hammerschlag","given":"Neil","email":"","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":899952,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Harmelin-Vivien, Mireille 0000-0003-3085-2899","orcid":"https://orcid.org/0000-0003-3085-2899","contributorId":335958,"corporation":false,"usgs":false,"family":"Harmelin-Vivien","given":"Mireille","email":"","affiliations":[{"id":80595,"text":"Université de Toulon","active":true,"usgs":false}],"preferred":false,"id":899953,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Harte, Agustin 0000-0002-3042-0474","orcid":"https://orcid.org/0000-0002-3042-0474","contributorId":335959,"corporation":false,"usgs":false,"family":"Harte","given":"Agustin","email":"","affiliations":[{"id":80596,"text":"United Nations Environment Programme","active":true,"usgs":false}],"preferred":false,"id":899954,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Kruemmel, Eva 0000-0001-6834-7738","orcid":"https://orcid.org/0000-0001-6834-7738","contributorId":335960,"corporation":false,"usgs":false,"family":"Kruemmel","given":"Eva","email":"","affiliations":[{"id":80597,"text":"ScienTissiME","active":true,"usgs":false}],"preferred":false,"id":899955,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Lailson-Brito, Jose 0000-0001-8366-458X","orcid":"https://orcid.org/0000-0001-8366-458X","contributorId":335961,"corporation":false,"usgs":false,"family":"Lailson-Brito","given":"Jose","email":"","affiliations":[{"id":80598,"text":"Universidade do Estado do Rio de Janeiro","active":true,"usgs":false}],"preferred":false,"id":899956,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Medina, Gabriella 0000-0002-4924-8539","orcid":"https://orcid.org/0000-0002-4924-8539","contributorId":335962,"corporation":false,"usgs":false,"family":"Medina","given":"Gabriella","email":"","affiliations":[{"id":80599,"text":"Basel Convention Coordinating Centre","active":true,"usgs":false}],"preferred":false,"id":899957,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Rodriguez, Cesar","contributorId":335964,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Cesar","email":"","affiliations":[{"id":80600,"text":"University of Panamá","active":true,"usgs":false}],"preferred":false,"id":899959,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Stenhouse, Iain","contributorId":194567,"corporation":false,"usgs":false,"family":"Stenhouse","given":"Iain","affiliations":[],"preferred":false,"id":899960,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Sunderland, Elsie M.","contributorId":151016,"corporation":false,"usgs":false,"family":"Sunderland","given":"Elsie","email":"","middleInitial":"M.","affiliations":[{"id":18166,"text":"Harvard University, Cambridge, M","active":true,"usgs":false}],"preferred":false,"id":899961,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Takeuchi, Akinori","contributorId":335965,"corporation":false,"usgs":false,"family":"Takeuchi","given":"Akinori","email":"","affiliations":[{"id":80601,"text":"Japanese National Institute for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":899962,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Tear, Timothy","contributorId":139999,"corporation":false,"usgs":false,"family":"Tear","given":"Timothy","email":"","affiliations":[{"id":13347,"text":"Grumeti Fund","active":true,"usgs":false}],"preferred":false,"id":899963,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Vega, Claudia","contributorId":335966,"corporation":false,"usgs":false,"family":"Vega","given":"Claudia","email":"","affiliations":[{"id":80602,"text":"Centro de Innovaccion Cientifica Amazonica","active":true,"usgs":false}],"preferred":false,"id":899964,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Wilson, Simon","contributorId":218345,"corporation":false,"usgs":false,"family":"Wilson","given":"Simon","email":"","affiliations":[{"id":39809,"text":"Arctic Monitoring and Assessment Programme (AMAP) Secretariat","active":true,"usgs":false}],"preferred":false,"id":899965,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Wu, Pianpian 0000-0002-2037-9164","orcid":"https://orcid.org/0000-0002-2037-9164","contributorId":335963,"corporation":false,"usgs":false,"family":"Wu","given":"Pianpian","email":"","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":899958,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}}
,{"id":70253230,"text":"70253230 - 2024 - Evaluation of debris-flow building damage forecasts","interactions":[],"lastModifiedDate":"2024-04-30T11:54:07.819325","indexId":"70253230","displayToPublicDate":"2024-04-29T06:50:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of debris-flow building damage forecasts","docAbstract":"<div id=\"abstract\" class=\"abstract sec\"><div class=\"abstract-content show-no-js\"><p id=\"d1e113\">Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9&nbsp;January&nbsp;2018 Montecito postfire debris-flow runout event, in which over 500&nbsp;buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models&nbsp;(RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.</p></div></div>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-24-1459-2024","usgsCitation":"Barnhart, K.R., Miller, C.R., Rengers, F.K., and Kean, J.W., 2024, Evaluation of debris-flow building damage forecasts: Natural Hazards and Earth System Sciences, v. 24, no. 4, p. 1459-1483, https://doi.org/10.5194/nhess-24-1459-2024.","productDescription":"25 p.","startPage":"1459","endPage":"1483","ipdsId":"IP-152213","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":439730,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-24-1459-2024","text":"Publisher Index Page"},{"id":428242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":899763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Christopher R.","contributorId":335923,"corporation":false,"usgs":false,"family":"Miller","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":7197,"text":"Unaffiliated","active":true,"usgs":false}],"preferred":false,"id":899764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":899765,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":899766,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70254267,"text":"70254267 - 2024 - Methylmercury effects on birds: A review, meta-analysis, and development of toxicity reference values for injury assessment based on tissue residues and diet","interactions":[],"lastModifiedDate":"2024-06-03T15:11:50.580162","indexId":"70254267","displayToPublicDate":"2024-04-29T06:45:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Methylmercury effects on birds: A review, meta-analysis, and development of toxicity reference values for injury assessment based on tissue residues and diet","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Birds are used as bioindicators of environmental mercury (Hg) contamination, and toxicity reference values are needed for injury assessments. We conducted a comprehensive review, summarized data from 168 studies, performed a series of Bayesian hierarchical meta-analyses, and developed new toxicity reference values for the effects of methylmercury (MeHg) on birds using a benchmark dose analysis framework. Lethal and sublethal effects of MeHg on birds were categorized into nine biologically relevant endpoint categories and three age classes. Effective Hg concentrations where there was a 10% reduction (EC10) in the production of juvenile offspring (0.55 µg/g wet wt adult blood-equivalent Hg concentrations, 80% credible interval: [0.33, 0.85]), histology endpoints (0.49 [0.15, 0.96] and 0.61 [0.09, 2.48]), and biochemical markers (0.77 [&lt;0.25, 2.12] and 0.57 [0.35, 0.92]) were substantially lower than those for survival (2.97 [2.10, 4.73] and 5.24 [3.30, 9.55]) and behavior (6.23 [1.84, &gt;13.42] and 3.11 [2.10, 4.64]) of juveniles and adults, respectively. Within the egg age class, survival was the most sensitive endpoint (EC10 = 2.02 µg/g wet wt adult blood-equivalent Hg concentrations [1.39, 2.94] or 1.17 µg/g fresh wet wt egg-equivalent Hg concentrations [0.80, 1.70]). Body morphology was not particularly sensitive to Hg. We developed toxicity reference values using a combined survival and reproduction endpoints category for juveniles, because juveniles were more sensitive to Hg toxicity than eggs or adults. Adult blood-equivalent Hg concentrations (µg/g wet wt) and egg-equivalent Hg concentrations (µg/g fresh wet wt) caused low injury to birds (EC1) at 0.09 [0.04, 0.17] and 0.04 [0.01, 0.08], moderate injury (EC5) at 0.6 [0.37, 0.84] and 0.3 [0.17, 0.44], high injury (EC10) at 1.3 [0.94, 1.89] and 0.7 [0.49, 1.02], and severe injury (EC20) at 3.2 [2.24, 4.78] and 1.8 [1.28, 2.79], respectively. Maternal dietary Hg (µg/g dry wt) caused low injury to juveniles at 0.16 [0.05, 0.38], moderate injury at 0.6 [0.29, 1.03], high injury at 1.1 [0.63, 1.87], and severe injury at 2.4 [1.42, 4.13]. We found few substantial differences in Hg toxicity among avian taxonomic orders, including for controlled laboratory studies that injected Hg into eggs. Our results can be used to quantify injury to birds caused by Hg pollution.<span>&nbsp;</span></p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/etc.5858","usgsCitation":"Ackerman, J.T., Peterson, S.H., Herzog, M.P., and Yee, J.L., 2024, Methylmercury effects on birds: A review, meta-analysis, and development of toxicity reference values for injury assessment based on tissue residues and diet: Environmental Toxicology and Chemistry, v. 43, no. 6, p. 1195-1241, https://doi.org/10.1002/etc.5858.","productDescription":"48 p.","startPage":"1195","endPage":"1241","ipdsId":"IP-152154","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439733,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5858","text":"Publisher Index Page"},{"id":434974,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MSD8X0","text":"USGS data release","linkHelpText":"Methylmercury Effects on Birds: Percent Injury Tool"},{"id":434973,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8UPGF","text":"USGS data release","linkHelpText":"Methylmercury Effects on Birds: Bibliography and Dataset for the Development of Toxicity Reference Values for Injury Assessment"},{"id":428728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":900817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70253906,"text":"70253906 - 2024 - Influence of organic matter thermal maturity on rare earth element distribution: A study of Middle Devonian black shales from the Appalachian Basin, USA","interactions":[],"lastModifiedDate":"2024-06-04T10:46:21.394306","indexId":"70253906","displayToPublicDate":"2024-04-28T09:47:48","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":"Influence of organic matter thermal maturity on rare earth element distribution: A study of Middle Devonian black shales from the Appalachian Basin, USA","docAbstract":"<p><span>This study focuses on understanding the association of rare earth elements (REE; lanthanides + yttrium + scandium) with organic matter from the Middle Devonian black shales of the Appalachian Basin. Developing a better understanding of the role of organic matter (OM) and thermal maturity in REE partitioning may help improve current geochemical models of REE enrichment in a wide range of black shales. We studied relationships between whole rock REE content and total organic carbon (TOC) and compared the correlations with a suite of global oil shales that contain TOC as high as 60 wt.%. The sequential leaching of the Appalachian shale samples was conducted to evaluate the REE content associated with carbonates, Fe–Mn oxyhydroxides, sulfides, and organics. Finally, the residue from the leaching experiment was analyzed to assess the mineralogical changes and REE extraction efficiency. Our results show that heavier REE (HREE) have a positive correlation with TOC in our Appalachian core samples. However, data from the global oil shales display an opposite trend. We propose that although TOC controls REE enrichment, thermal maturation likely plays a critical role in HREE partitioning into refractory organic phases, such as pyrobitumen. The REE inventory from a core in the Appalachian Basin shows that (1) the total REE ranges between 180 and 270 ppm and the OM-rich samples tend to contain more REE than the calcareous shales; (2) there is a relatively higher abundance of middle REE (MREE) to HREE than lighter REE (LREE); (3) there is a disproportionate increase in Y and Tb with TOC likely due to the rocks being over-mature; and (4) the REE extraction demonstrates that although the OM has higher HREE concentration, the organic leachates contain more LREE, suggesting it is more challenging to extract HREE from OM than using traditional leaching techniques.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/en17092107","usgsCitation":"Bhattacharya, S., Sharma, S., Agrawal, V., Dix, M.C., Zanoni, G., Birdwell, J.E., Wylie, A.S., and Wagner, T., 2024, Influence of organic matter thermal maturity on rare earth element distribution: A study of Middle Devonian black shales from the Appalachian Basin, USA: Energies, v. 17, no. 9, 2107, 23 p., https://doi.org/10.3390/en17092107.","productDescription":"2107, 23 p.","ipdsId":"IP-160281","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":439736,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/en17092107","text":"Publisher Index Page"},{"id":428357,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Middle Devonian Appalachian Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.019722212101,\n              35.09354117626262\n            ],\n            [\n              -80.0893868493873,\n              35.83616426236574\n            ],\n            [\n              -75.48876301910367,\n              41.23650512855389\n            ],\n            [\n              -74.6944038739024,\n              43.48785346597265\n            ],\n            [\n              -79.3043542917768,\n              42.997887934674736\n            ],\n            [\n              -83.72355980871455,\n              37.83971543304291\n            ],\n            [\n              -85.019722212101,\n              35.09354117626262\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bhattacharya, Shailee","contributorId":336153,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Shailee","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharma, Shikha","contributorId":336154,"corporation":false,"usgs":false,"family":"Sharma","given":"Shikha","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agrawal, Vikas","contributorId":336156,"corporation":false,"usgs":false,"family":"Agrawal","given":"Vikas","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":900059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dix, Michael C.","contributorId":336159,"corporation":false,"usgs":false,"family":"Dix","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":80761,"text":"Consultant (formerly with PremierCorex)","active":true,"usgs":false}],"preferred":false,"id":900060,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zanoni, Giovanni","contributorId":336160,"corporation":false,"usgs":false,"family":"Zanoni","given":"Giovanni","email":"","affiliations":[{"id":80763,"text":"RohmTek, Houston, TX","active":true,"usgs":false}],"preferred":false,"id":900061,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":900062,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wylie, Albert S. Jr.","contributorId":336282,"corporation":false,"usgs":false,"family":"Wylie","given":"Albert","suffix":"Jr.","email":"","middleInitial":"S.","affiliations":[{"id":80764,"text":"Independent researcher, Mohawk, MI","active":true,"usgs":false}],"preferred":false,"id":900063,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Tom","contributorId":336283,"corporation":false,"usgs":false,"family":"Wagner","given":"Tom","email":"","affiliations":[],"preferred":false,"id":900064,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70253052,"text":"ofr20241021 - 2024 - Special Contributing Area Loading Program user’s manual","interactions":[],"lastModifiedDate":"2024-04-26T16:36:34.348917","indexId":"ofr20241021","displayToPublicDate":"2024-04-26T11:23:22","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":"2024-1021","displayTitle":"Special Contributing Area Loading Program User’s Manual","title":"Special Contributing Area Loading Program user’s manual","docAbstract":"<p>The Special Contributing Area Loading Program (SCALP) is a hydrologic routing program that simulates reservoir routing through a linear-reservoir-in-series method. The Java version of SCALP was developed to replicate and replace the functionality of an older version of the program written in Fortran. SCALP models flow through three reservoirs in series using an input runoff depth time series and information describing the hydrologic characteristics and sanitary flow for one or more land areas within a basin, supplied by the user. Each basin is herein referred to as a “Special Contributing Area” (SCA); the SCAs are a central concept in SCALP. Although flow through each SCA is routed separately, the user may simulate multiple SCAs in a batch simulation. The outputs of SCALP include information about flows through and overflows from the three reservoirs in the series.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241021","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Doyle, H.F., and Domanski, M.M., 2024, Special Contributing Area Loading Program user’s manual: U.S. Geological Survey Open-File Report 2024–1021, 15 p., https://doi.org/10.3133/ofr20241021.","productDescription":"Report: vi, 15 p.; Software Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-137188","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":427858,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9EE0614","text":"USGS software release","linkHelpText":"—SCALP (Special Contributing Area Loading Program, ver. 1.0.0)"},{"id":427857,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241021/full"},{"id":427856,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1021/images/"},{"id":427855,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1021/ofr20241021.XML"},{"id":427854,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1021/ofr20241021.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1021"},{"id":427853,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1021/coverthb.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 North Goodwin<br>Urbana, IL 61801</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Introduction</li><li>Reservoir Routing</li><li>Usage</li><li>Model Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-04-26","noUsgsAuthors":false,"publicationDate":"2024-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Doyle, Henry F. 0000-0001-9942-8602 hfdoyle@usgs.gov","orcid":"https://orcid.org/0000-0001-9942-8602","contributorId":243432,"corporation":false,"usgs":true,"family":"Doyle","given":"Henry","email":"hfdoyle@usgs.gov","middleInitial":"F.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70254148,"text":"70254148 - 2024 - Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: The hotspot learning and identification network","interactions":[],"lastModifiedDate":"2024-05-09T11:59:38.152536","indexId":"70254148","displayToPublicDate":"2024-04-26T06:55:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: The hotspot learning and identification network","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2024.1345104","usgsCitation":"Saunders-Shultz, P., Lopez, T., Dietterich, H., and Girona, T., 2024, Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: The hotspot learning and identification network: Frontiers in Earth Science, v. 12, 1345104, 20 p., https://doi.org/10.3389/feart.2024.1345104.","productDescription":"1345104, 20 p.","ipdsId":"IP-157801","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":439740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2024.1345104","text":"Publisher Index Page"},{"id":428583,"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\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -145.34913503064,\n              62.169615932234194\n            ],\n            [\n              -171.18897878064004,\n              62.169615932234194\n            ],\n            [\n              -171.18897878064004,\n              52.13889648467486\n            ],\n            [\n              -145.34913503064,\n              52.13889648467486\n            ],\n            [\n              -145.34913503064,\n              62.169615932234194\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders-Shultz, Pablo","contributorId":336581,"corporation":false,"usgs":false,"family":"Saunders-Shultz","given":"Pablo","email":"","affiliations":[{"id":80792,"text":"University of Alaska Fairbanks Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":900429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, Taryn","contributorId":237830,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":900430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Girona, Tarsilo","contributorId":336582,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","affiliations":[{"id":80792,"text":"University of Alaska Fairbanks Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":900432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70253191,"text":"sir20245009 - 2024 - Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2025-08-07T20:31:29.798566","indexId":"sir20245009","displayToPublicDate":"2024-04-25T13:17:53","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5009","displayTitle":"Status of Water Quality in Groundwater Resources Used for Drinking-Water Supply in the Southeastern San Joaquin Valley, 2013–15: California GAMA Priority Basin Project","title":"Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project","docAbstract":"<p>The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) investigated water quality of groundwater resources used for drinking-water supplies in the Madera-Chowchilla, Kings, Kaweah, Tule, and Tulare Lake groundwater subbasins of the southeastern San Joaquin Valley during 2013–15. The study focused primarily on groundwater resources used for domestic-supply wells in the southeastern San Joaquin Valley (SESJV-D), which correspond mostly to shallower parts of aquifer systems, compared to the groundwater resources used for public-supply wells in the southeastern San Joaquin Valley (SESJV-P). The investigation had three components: (1) characterization of the status of water quality in the SESJV-D, (2) comparison between water quality in the SESJV-D and SESJV-P, and (3) identification of natural and anthropogenic factors that potentially could affect water quality in these resources.</p><p>The characterization of water quality in the SESJV-D was based on data collected from 198 domestic wells sampled during 2013–15 by the U.S. Geological Survey (USGS); characterization of water quality in the SESJV-P was based on data collected from 124 wells sampled by the USGS during 2005–18 and an additional 1,577 wells with publicly available data reported to the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW). Measured concentrations were compared to regulatory and non-regulatory drinking-water quality benchmarks. A grid-based method was used to estimate the areal proportions of each study area and the whole southeastern San Joaquin Valley with high (greater than benchmark concentration), moderate (greater than half of the benchmark for inorganic and one-tenth of the benchmark for organic), and low concentrations relative to those benchmarks.</p><p>Natural and anthropogenic factors that could affect groundwater quality for the SESJV-D were identified in the context of the hydrogeologic setting of the southeastern San Joaquin Valley. The considered factors represented hydrologic conditions and position in the groundwater flow system (well depth, lateral position, presence of hydric soils, percentage of coarse-grained sediment, and aridity index), land-use characteristics (percentages of agricultural, urban, and natural land use, percentage of orchard or vineyard land use, and densities of septic tanks and underground storage tanks near the wells), and geochemical conditions (groundwater age class, oxidation-reduction class, pH, and dissolved oxygen and bicarbonate concentrations). Factors are compared between SESJV-D and SESJV-P at the scale of the five study areas.</p><p>One or more inorganic constituents with U.S. Environmental Protection Agency (EPA) or California maximum contaminant levels (MCLs) were detected at high concentrations in 47 percent of the SESJV-D and in 32 percent of the SESJV-P. The inorganic constituents most commonly present at high concentrations in the SESJV-D were nitrate, uranium, and arsenic. Within the SESJV-D, the proportion of the study area with high concentrations of inorganic constituents ranged from 19 percent in Madera-Chowchilla to 60 percent in Kings and Tulare Lake. One or more inorganic constituents with California State Water Resources Control Board Division of Drinking Water secondary maximum contaminant levels (SMCL-CAs) were detected at high concentrations in 14 percent of the SESJV-D and in 19 percent of the SESJV-P. The constituents most commonly present at high concentrations were manganese, iron, and total dissolved solids (TDS). Although the proportion of SESJV-D and SESJV-P with high concentrations of TDS greater than the upper SMCL were similar at 4 percent, the proportion of the SESJV-D with moderate concentrations (between the recommended and upper SMCL-CA), 30 percent, was greater than the proportion of the SESJV-P with moderate concentrations, 12 percent.</p><p>One or more organic constituents with MCLs were present at high concentrations in 19 percent of the SESJV-D and in 12 percent of the SESJV-P. All the constituents detected at high concentrations in the SESJV-D were fumigants, primarily 1,2,3-trichloropropane (1,2,3-TCP) and 1,2-dibromo-3-chloropropane (DBCP). Fumigants also were the constituents most commonly detected at high concentrations in the SESJV-P, although high concentrations of solvents also were detected. The SESJV-D dataset included analysis of many organic constituents without MCL benchmarks and with detection levels far below drinking water benchmark concentrations; detections at these low concentrations can be used as tracers of anthropogenic influence on groundwater. Pesticides and degradates of pesticides were detected in 60 percent of the SESJV-D; the most frequently detected pesticides were the herbicides simazine, didealkylatrazine (CAAT, a degradate of simazine and atrazine), diuron, and bromacil.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245009","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Burow, K.R., Shelton, J.L., and Fram, M.S., 2024, Status of water quality in groundwater resources used for drinking-water supply in the southeastern San Joaquin Valley, 2013–15—California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2024–5009, 135 p., https://doi.org/10.3133/sir20245009.","productDescription":"Report: xiii, 135 p.; Data Release","numberOfPages":"136","onlineOnly":"Y","ipdsId":"IP-094434","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":428122,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245009/full"},{"id":493742,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116370.htm","linkFileType":{"id":5,"text":"html"}},{"id":428123,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DCTLXV","text":"USGS Data Release","description":"Balkan, M., Burow, K.R., and Shelton, J.L., and Fram, M.S., 2024, Data sets for: Status of water quality in groundwater resources used for drinking water supply in the southeast San Joaquin Valley, 2013–2015—California GAMA Priority Basin Project: U.S. Geological Survey data release, accessed January, 22, 2024, at https://doi.org/10.5066/P9DCTLXV","linkHelpText":"Data sets for: Status of water quality in groundwater resources used for drinking water supply in the southeast San Joaquin Valley, 2013–2015—California GAMA Priority Basin Project"},{"id":428120,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5009/sir20245009.xml"},{"id":428118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5009/covrthb.jpg"},{"id":428121,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5009/images"},{"id":428119,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5009/sir20245009.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.36728753741212,\n              37.719936264455484\n            ],\n            [\n              -121.36728753741212,\n              35.78355104851377\n            ],\n            [\n              -118.20322503741215,\n              35.78355104851377\n            ],\n            [\n              -118.20322503741215,\n              37.719936264455484\n            ],\n            [\n              -121.36728753741212,\n              37.719936264455484\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Hydrogeologic Setting</li><li>Methods</li><li>Hydrogeologic, Land-Use, and Geochemical Characteristics</li><li>Status of Groundwater Quality</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Additional Information About Well Selection</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2024-04-25","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Burow, Karen R. 0000-0001-6006-6667 krburow@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-6667","contributorId":1504,"corporation":false,"usgs":true,"family":"Burow","given":"Karen","email":"krburow@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":899465,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263482,"text":"70263482 - 2024 - Cytology in cnidaria using Exaiptasia as a model","interactions":[],"lastModifiedDate":"2025-02-12T14:24:23.745139","indexId":"70263482","displayToPublicDate":"2024-04-25T08:21:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Cytology in cnidaria using <i>Exaiptasia</i> as a model","title":"Cytology in cnidaria using Exaiptasia as a model","docAbstract":"<p><span>A need exists for additional methods to examine cnidaria at the cellular level to aid our understanding of health, anatomy, and physiology of this important group of organisms. This need is particularly acute given that disease is emerging as a major factor in declines of ecologically important functional groups such as corals. Here we describe a simple method to process cnidarian cells for microscopic examination using the model organism&nbsp;</span><i>Exaiptasia</i><span>. We show that this organism has at least 18 cell types or structures that can be readily distinguished based on defined morphological features. Some of these cells can be related back to anatomic features of the animal both at the light microscope and ultrastructural level. The cnidome of&nbsp;</span><i>Exaiptasia</i><span>&nbsp;may be more complex than what is currently understood. Moreover, cnidarian cells, including some types of cnidocytes, phagocytize cells other than endosymbionts. Finally, our findings shed light on morphologic complexity of cell-associated microbial aggregates and their intimate intracellular associations. The tools described here could be useful for other cnidaria.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/dao03781","usgsCitation":"Work, T.M., Singarkhan, C., and Weatherby, T., 2024, Cytology in cnidaria using Exaiptasia as a model: Diseases of Aquatic Organisms, v. 158, p. 37-53, https://doi.org/10.3354/dao03781.","productDescription":"17 p.","startPage":"37","endPage":"53","ipdsId":"IP-159594","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":487639,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/dao03781","text":"Publisher Index Page"},{"id":481970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":927130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singarkhan, Chutimon","contributorId":335063,"corporation":false,"usgs":false,"family":"Singarkhan","given":"Chutimon","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":927131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weatherby, Tina","contributorId":193516,"corporation":false,"usgs":false,"family":"Weatherby","given":"Tina","affiliations":[],"preferred":false,"id":927132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70253192,"text":"70253192 - 2024 - Atmospheric river activity during the late Holocene exceeds modern range of variability in California","interactions":[],"lastModifiedDate":"2024-04-26T12:03:49.92142","indexId":"70253192","displayToPublicDate":"2024-04-25T06:59:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13795,"text":"Nature Communications Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric river activity during the late Holocene exceeds modern range of variability in California","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Atmospheric rivers are associated with some of the largest flood-producing precipitation events in western North America, particularly California. Insight into past extreme precipitation can be reconstructed from sedimentary archives on millennial timescales. Here we document atmospheric river activity near Leonard Lake, California, over 3,200 years, using a key metric of atmospheric river intensity, that is silicon/aluminum enriched layers that are highly correlated with modern records of integrated vapor transport. The late twentieth century had the highest median integrated vapor transport since the onset of the Medieval Climate Anomaly, with integrated vapor transport increasing during the Little Ice Age. The reconstruction suggests California has experienced pluvial episodes that exceeded any in the meteorologic instrumental era, with the largest episodes occurring two and three millennia ago. These results provide critical data to help avoid underestimation of potential risks and aid future planning scenarios.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s43247-024-01357-z","usgsCitation":"Knight, C.A., Anderson, L., Presnetsova, L.S., Champagne, M.R., and Wahl, D., 2024, Atmospheric river activity during the late Holocene exceeds modern range of variability in California: Nature Communications Earth and Environment, v. 5, 216, 8 p., https://doi.org/10.1038/s43247-024-01357-z.","productDescription":"216, 8 p.","ipdsId":"IP-159306","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":439749,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01357-z","text":"Publisher Index Page"},{"id":434976,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1ECT7AM","text":"USGS data release","linkHelpText":"Geochemical, grain size, lithological, bathymetric, reconstructed integrated vapor transport, and age model data for Leonard Lake, Mendocino County"},{"id":428129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Leonard Lake","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Clarke Alexandra 0000-0003-0002-6959","orcid":"https://orcid.org/0000-0003-0002-6959","contributorId":288487,"corporation":false,"usgs":true,"family":"Knight","given":"Clarke","email":"","middleInitial":"Alexandra","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":899466,"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":899467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Presnetsova, Liubov S. 0000-0002-1351-8541 lpresnetsova@usgs.gov","orcid":"https://orcid.org/0000-0002-1351-8541","contributorId":296053,"corporation":false,"usgs":true,"family":"Presnetsova","given":"Liubov","email":"lpresnetsova@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":899468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champagne, Marie Rhondelle 0000-0001-8236-3910","orcid":"https://orcid.org/0000-0001-8236-3910","contributorId":248214,"corporation":false,"usgs":true,"family":"Champagne","given":"Marie","email":"","middleInitial":"Rhondelle","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":899469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":899470,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70254071,"text":"70254071 - 2024 - Flexible migration and habitat use strategies of an endangered waterbird during hydrological drought","interactions":[],"lastModifiedDate":"2024-05-20T15:45:14.936342","indexId":"70254071","displayToPublicDate":"2024-04-25T06:44:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Flexible migration and habitat use strategies of an endangered waterbird during hydrological drought","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Wildlife species confront threats from climate and land use change, exacerbating the influence of extreme climatic events on populations and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes (<i>Grus americana</i>) modified habitat use and migration strategies during drought to evaluate their resilience to changing conditions and adaptive capacity. We categorized &gt;8000 night-roost sites used by 146 cranes from 2010 to 2022 and examined relative use during non-drought, moderate drought, and extreme drought conditions. We found cultivated and uncultivated palustrine and lacustrine wetlands were generally used less during droughts than non-drought conditions. Conversely, impounded palustrine and lacustrine systems and rivers served more frequently as drought refugia (i.e., used more during drought than non-drought conditions). Night roosts occurred primarily on private lands (86% overall); public land use decreased with latitude and increased with drought severity, with greatest use (56%) occurring during severe autumn drought in the southern Great Plains. Quantifying use of identified critical habitats in the United States indicated that Cheyenne Bottoms State Waterfowl Management Area and Quivira National Wildlife Refuge were used less during drought, and the Central Platte River and Salt Plains National Wildlife Refuge received similar use during drought compared to non-drought conditions. Our findings provide insights into compensatory use of habitats, where impounded surface water may function in a complementary fashion with natural wetlands. Collectively, these and other types of wetlands distributed across the migration corridor provided a reliable network of habitat available across the Great Plains. A diversity of wetlands available during variable environmental conditions would be useful in supporting continued recovery of whooping cranes and likely have benefits for a wide array of migratory birds.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/csp2.13120","usgsCitation":"Pearse, A.T., Caven, A.J., Baasch, D.M., Bidwell, M., Conkin, J.A., and Brandt, D.A., 2024, Flexible migration and habitat use strategies of an endangered waterbird during hydrological drought: Conservation Science and Practice, v. 6, e13120, 18 p., https://doi.org/10.1111/csp2.13120.","productDescription":"e13120, 18 p.","ipdsId":"IP-157091","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":439753,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.13120","text":"Publisher Index Page"},{"id":428429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.0014028418284,\n              59.16981020528931\n            ],\n            [\n              -117.0014028418284,\n              27.51717050445781\n            ],\n            [\n              -88.78851221682842,\n              27.51717050445781\n            ],\n            [\n              -88.78851221682842,\n              59.16981020528931\n            ],\n            [\n              -117.0014028418284,\n              59.16981020528931\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":900134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caven, Andrew J.","contributorId":177586,"corporation":false,"usgs":false,"family":"Caven","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":900135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":900136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":139204,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark T.","affiliations":[{"id":12696,"text":"Environmental Canada","active":true,"usgs":false}],"preferred":false,"id":900137,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conkin, John A","contributorId":236845,"corporation":false,"usgs":false,"family":"Conkin","given":"John","email":"","middleInitial":"A","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":900138,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":900139,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70253217,"text":"70253217 - 2024 - Ecological inferences on invasive carp survival using hydrodynamics and egg drift models","interactions":[],"lastModifiedDate":"2024-04-29T11:04:35.731469","indexId":"70253217","displayToPublicDate":"2024-04-25T06:02:17","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}},"title":"Ecological inferences on invasive carp survival using hydrodynamics and egg drift models","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Bighead carp (<i>Hypophthalmichthys nobilis</i>), silver carp (<i>H. molitrix</i>), black carp (<i>Mylopharyngodon piceus</i>), and grass carp (<i>Ctenopharyngodon idella</i>), are invasive species in North America. However, they hold significant economic importance as food sources in China. The drifting stage of carp eggs has received great attention because egg survival rate is strongly affected by river hydrodynamics. In this study, we explored egg-drift dynamics using computational fluid dynamics (CFD) models to infer potential egg settling zones based on mechanistic criteria from simulated turbulence in the Lower Missouri River. Using an 8-km reach, we simulated flow characteristics with four different discharges, representing 45–3% daily flow exceedance. The CFD results elucidate the highly heterogeneous spatial distribution of flow velocity, flow depth, turbulence kinetic energy (TKE), and the dissipation rate of TKE. The river hydrodynamics were used to determine potential egg settling zones using criteria based on shear velocity, vertical turbulence intensity, and Rouse number. Importantly, we examined the difference between hydrodynamic-inferred settling zones and settling zones predicted using an egg-drift transport model. The results indicate that hydrodynamic inference is useful in determining the ‘potential’ of egg settling, however, egg drifting paths should be taken into account to improve prediction. Our simulation results also indicate that the river turbulence does not surpass the laboratory-identified threshold to pose a threat to carp eggs.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-024-60189-1","usgsCitation":"Xu, R., Chapman, D., Elliott, C.M., Call, B., Jacobson, R.B., and Yang, B., 2024, Ecological inferences on invasive carp survival using hydrodynamics and egg drift models: Scientific Reports, v. 14, no. 1, 9556, 15 p., https://doi.org/10.1038/s41598-024-60189-1.","productDescription":"9556, 15 p.","ipdsId":"IP-164134","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":439755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-60189-1","text":"Publisher Index Page"},{"id":428173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Ruichen","contributorId":335913,"corporation":false,"usgs":false,"family":"Xu","given":"Ruichen","email":"","affiliations":[{"id":80580,"text":"University of Missouri - Columbia","active":true,"usgs":false}],"preferred":false,"id":899709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":899710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":899711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Call, Bruce 0000-0001-9064-2231","orcid":"https://orcid.org/0000-0001-9064-2231","contributorId":217707,"corporation":false,"usgs":true,"family":"Call","given":"Bruce","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":899712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobson, Robert B.","contributorId":335914,"corporation":false,"usgs":false,"family":"Jacobson","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":80580,"text":"University of Missouri - Columbia","active":true,"usgs":false}],"preferred":false,"id":899713,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Binbin","contributorId":335915,"corporation":false,"usgs":false,"family":"Yang","given":"Binbin","email":"","affiliations":[{"id":80580,"text":"University of Missouri - Columbia","active":true,"usgs":false}],"preferred":false,"id":899714,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70258184,"text":"70258184 - 2024 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","interactions":[{"subject":{"id":70258184,"text":"70258184 - 2024 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","indexId":"70258184","publicationYear":"2024","noYear":false,"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples"},"predicate":"SUPERSEDED_BY","object":{"id":70261709,"text":"70261709 - 2025 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","indexId":"70261709","publicationYear":"2025","noYear":false,"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples"},"id":1}],"supersededBy":{"id":70261709,"text":"70261709 - 2025 - A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","indexId":"70261709","publicationYear":"2025","noYear":false,"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples"},"lastModifiedDate":"2024-12-27T15:54:35.881315","indexId":"70258184","displayToPublicDate":"2024-04-24T09:49:38","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples","docAbstract":"<p><span>Environmental DNA (eDNA) sampling is an increasingly important tool for answering ecological questions and informing aquatic species management; however, several factors currently limit the reliability of ecological inference from eDNA sampling. Two particular challenges are 1) determining species source location(s) and 2) accurately and precisely measuring low concentration eDNA samples in the presence of multiple sources of ecological and measurement variability. The recently introduced eDNA Integrating Transport and Hydrology (eDITH) model provides a framework for relating eDNA measurements to source locations in riverine networks, but little empirical work has been done to test and refine model assumptions or accommodate low concentration samples, that can be systematically undermeasured. To better understand eDNA fate and transport dynamics and our ability to reliably quantify low concentration samples, we developed a hierarchical model and used it to evaluate a fate and transport experiment. Our model addresses several low concentration challenges by modeling the number of copies in each PCR replicate as a latent variable with a count distribution and conditioning detection and quantification on replicate copy number. We provide evidence that the eDNA removal rate declined through time, estimating that over 80% of eDNA was removed over the first 10 meters, traversed in 41 seconds. After this initial period of rapid decay, eDNA decayed slowly with consistent detection through our farthest site 1km from the release location, traversed in 250 seconds. Our model further allowed us to detect extra-Poisson variation in the allocation of copies to replicates. We extended our hierarchical model to accommodate a continuous effect of inhibitors and used our model to provide evidence for the inhibitor hypothesis and explore the potential implications. While our model is not a panacea for all challenges faced when quantifying low-concentration eDNA samples, it provides a framework for a more complete accounting of uncertainty.</span></p>","language":"English","publisher":"BiorXiv","doi":"10.1101/2024.03.27.586987","usgsCitation":"Augustine, B., Hutchins, P., Jones-Slobodian, D.N., Williams, J., Leinonen, E., and Sepulveda, A., 2024, A hierarchical model for eDNA fate and transport dynamics accommodating low concentration samples: BioRxiv, https://doi.org/10.1101/2024.03.27.586987.","productDescription":"61 p.","ipdsId":"IP-161502","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":459969,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.03.27.586987","text":"External Repository"},{"id":465483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Augustine, Ben 0000-0001-6935-6361","orcid":"https://orcid.org/0000-0001-6935-6361","contributorId":245736,"corporation":false,"usgs":true,"family":"Augustine","given":"Ben","email":"","affiliations":[{"id":49304,"text":"Department of Natural Resources, Cornell University","active":true,"usgs":false}],"preferred":false,"id":912510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchins, Patrick Ross 0000-0001-5232-0821","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":256658,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick Ross","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones-Slobodian, Devin Nicole 0000-0001-9215-2930","orcid":"https://orcid.org/0000-0001-9215-2930","contributorId":305357,"corporation":false,"usgs":true,"family":"Jones-Slobodian","given":"Devin","middleInitial":"Nicole","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Jacob R.","contributorId":343977,"corporation":false,"usgs":false,"family":"Williams","given":"Jacob R.","affiliations":[{"id":82269,"text":"Turner Institute of Ecoagriculture","active":true,"usgs":false}],"preferred":false,"id":912513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leinonen, Eric","contributorId":343978,"corporation":false,"usgs":false,"family":"Leinonen","given":"Eric","affiliations":[{"id":82269,"text":"Turner Institute of Ecoagriculture","active":true,"usgs":false}],"preferred":false,"id":912514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":912515,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70253898,"text":"70253898 - 2024 - Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions","interactions":[],"lastModifiedDate":"2024-07-15T15:03:38.550959","indexId":"70253898","displayToPublicDate":"2024-04-24T08:48:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions","docAbstract":"<p><span>Wildlife reintroduction is an important conservation tool for threatened species, yet identifying appropriate source populations poses a challenge. In particular, the possibility of outbreeding depression is cited as a constraint limiting the range of candidate source populations for translocation. When multiple source lineages are mixed during reintroduction, genetic monitoring is necessary to evaluate whether sources contribute equally to subsequent generations and whether they are interbreeding as expected. Moreover, statistical analysis of genetic data should account for complex life histories that might affect the timescale of admixture and genetic drift. Here, we use samples collected over a 23-year period and a stochastic age-structured model to analyze the genetic mixing process in reintroduced Brook Trout (</span><i>Salvelinus fontinalis</i><span>) populations in the Southern Appalachians. Each restored population was seeded with two to three source populations. Previous research inferred reproductive isolation between source populations leading to a proposal of splitting the species into multiple taxa. In contrast, we found patterns of ancestry that were consistent with random mating and no advantage for one source lineage over any other. Brook Trout from different source streams are mixing as expected in the restoration sites. This result does not support the hypothesis that Brook Trout in the Southern Appalachian Mountains includes several distinct species. Mixing different sources from the same watershed seems to be an effective way to increase genetic diversity of reintroduced populations while minimizing risk to source populations.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-024-01620-y","usgsCitation":"Smith, R.J., Kazyak, D.C., Kulp, M.A., Lubinski, B.A., and Fitzpatrick, B.M., 2024, Genetic structure of restored Brook Trout populations in the Southern Appalachian Mountains indicates successful reintroductions: Conservation Genetics, v. 25, p. 1007-1020, https://doi.org/10.1007/s10592-024-01620-y.","productDescription":"14 p.","startPage":"1007","endPage":"1020","ipdsId":"IP-158952","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":428350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.90629478474587,\n              35.85116809750147\n            ],\n            [\n              -84.21639200734252,\n              35.85116809750147\n            ],\n            [\n              -84.21639200734252,\n              35.2665417042201\n            ],\n            [\n              -82.90629478474587,\n              35.2665417042201\n            ],\n            [\n              -82.90629478474587,\n              35.85116809750147\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2024-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Rebecca J.","contributorId":229064,"corporation":false,"usgs":false,"family":"Smith","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":41574,"text":"National Park Service, Yellowstone National Park, PO Box 168, 22 Stable Street, Yellowstone National Park, WY, 82190, USA","active":true,"usgs":false}],"preferred":false,"id":900031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":900032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kulp, Matt A.","contributorId":196801,"corporation":false,"usgs":false,"family":"Kulp","given":"Matt","email":"","middleInitial":"A.","affiliations":[{"id":35484,"text":"National Park Service, Great Smoky Mountains National Park","active":true,"usgs":false}],"preferred":false,"id":900033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":900034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzpatrick, Benjamin M.","contributorId":336140,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[{"id":80760,"text":"1. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee","active":true,"usgs":false}],"preferred":false,"id":900035,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264784,"text":"70264784 - 2024 - Environmental DNA dynamics of three species of unionid freshwater mussels","interactions":[],"lastModifiedDate":"2025-03-24T15:21:21.274494","indexId":"70264784","displayToPublicDate":"2024-04-24T08:17:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Environmental DNA dynamics of three species of unionid freshwater mussels","docAbstract":"<p><span>North American freshwater mussels are of special conservation concern due to their high endemism and the multiple anthropogenic stressors affecting them. Of the over 300 species in North America, nearly one third of these species are federally listed as threatened or endangered. Environmental DNA (eDNA) analysis has been successful in detecting freshwater mussels and could aid in monitoring their populations. Production and degradation rates of eDNA for the species of interest are needed to inform interpretation of eDNA detections, allow possible modeling of relative abundance and population location, and aid in mussel conservation through population identification. Here, we designed and tested qPCR assays for three freshwater mussel species, mucket (</span><i>Ortmanniana ligamentina</i><span>), fatmucket (</span><i>Lampsilis siliquoidea</i><span>), and the federally endangered spectaclecase (</span><i>Cumberlandia monodonta</i><span>). We performed laboratory experiments under controlled conditions to measure eDNA shedding and degradation rates for each species. Different biomasses, temperatures, and food regimens were tested independently to determine if these factors influence the amount of DNA produced by the mussels. Degradation rates of eDNA were measured from experimental tank water after mussels were removed. Overall, we observed low eDNA shedding rates for freshwater mussels compared to previous studies of fish eDNA shedding rates. Furthermore, temperature and feeding showed limited or no significant effects in the species studied. Environmental DNA degradation rates were consistent with those reported in the literature for other taxa. Collectively, our results will be useful for designing eDNA monitoring studies, modeling eDNA dispersal, and interpreting eDNA results to help inform freshwater mussel conservation efforts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/edn3.543","usgsCitation":"Ruiz-Ramos, D., Thompson, N., Richter, C.A., Voshage, M., Schreier, T.M., Merkes, C.M., and Klymus, K.E., 2024, Environmental DNA dynamics of three species of unionid freshwater mussels: Environmental DNA, v. 6, no. 2, e543, 15 p., https://doi.org/10.1002/edn3.543.","productDescription":"e543, 15 p.","ipdsId":"IP-157659","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.543","text":"Publisher Index Page"},{"id":483719,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruiz-Ramos, Dannise","contributorId":332474,"corporation":false,"usgs":false,"family":"Ruiz-Ramos","given":"Dannise","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":931669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voshage, Megan C.","contributorId":332475,"corporation":false,"usgs":false,"family":"Voshage","given":"Megan C.","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":931672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":931673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":931674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931675,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70257757,"text":"70257757 - 2024 - Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA","interactions":[],"lastModifiedDate":"2024-09-09T16:49:25.320965","indexId":"70257757","displayToPublicDate":"2024-04-24T07:02:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA","docAbstract":"<div id=\"abstract\" class=\"abstract sec\"><div class=\"abstract-content show-no-js\"><p id=\"d1e157\"><span>Moderate- or high-severity fires promote increases in runoff and erosion, leading to a greater likelihood of extreme geomorphic responses, including debris flows. In the first several years following fire, the majority of debris flows initiate when runoff rapidly entrains sediment on steep slopes. From a hazard perspective, it is important to be able to anticipate when and where watershed responses will be dominated by debris flows rather than flood flows. Rainfall intensity averaged over a 15 </span><span class=\"inline-formula\">min</span><span>&nbsp;duration,&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span><span>, in particular, has been identified as a key predictor of debris flow likelihood. Developing effective warning systems and predictive models for post-fire debris flow hazards therefore relies on high-temporal resolution rainfall data at the time debris flows initiate. In this study, we documented the geomorphic response of a series of watersheds following a wildfire in western New Mexico, USA, with an emphasis on constraining debris flow timing within rainstorms to better characterize debris-flow-triggering rainfall intensities. We estimated temporal changes in soil hydraulic properties and ground cover in areas burned at different severities over&nbsp;</span><span class=\"inline-formula\">&gt;2</span><span>&nbsp;years to offer explanations for observed differences in spatial and temporal patterns in debris flow activity. We observed 16 debris flows, all of which initiated during the first several months following the fire. The average recurrence interval of the debris-flow-triggering&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span><span>&nbsp;is 1.3&nbsp;years, which highlights the susceptibility of recently burned watersheds to runoff-generated debris flows in this region. All but one of the debris flows initiated in watersheds burned primarily at moderate or high soil burn severity. Since soil hydraulic properties appeared to be relatively resilient to burning, we attribute reduced debris flow activity at later times to decreases in the fraction of bare ground. Results provide additional constraints on the rainfall characteristics that promote post-fire debris flow initiation in a region where fire size and severity have been increasing.</span></p></div></div><div id=\"citation-footer\" class=\"sec\"><br></div>","language":"English","publisher":"European Geophysical Union","doi":"10.5194/nhess-24-1357-2024","usgsCitation":"McGuire, L.A., Rengers, F.K., Youberg, A., Gorr, A., Hoch, O.J., Beers, R., and Porter, R., 2024, Characteristics of debris-flow-prone watersheds and debris-flow-triggering rainstorms following the Tadpole Fire, New Mexico, USA: Natural Hazards and Earth System Sciences, v. 24, no. 4, p. 1357-1379, https://doi.org/10.5194/nhess-24-1357-2024.","productDescription":"23 p.","startPage":"1357","endPage":"1379","ipdsId":"IP-151760","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":439764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-24-1357-2024","text":"Publisher Index Page"},{"id":433634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Gila National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -108.483061459492,\n              33.02319886221093\n            ],\n            [\n              -108.483061459492,\n              32.67705656895561\n            ],\n            [\n              -107.94463669183348,\n              32.67705656895561\n            ],\n            [\n              -107.94463669183348,\n              33.02319886221093\n            ],\n            [\n              -108.483061459492,\n              33.02319886221093\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"24","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":911615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172400,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":911616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorr, Alexander 0000-0002-3239-7773","orcid":"https://orcid.org/0000-0002-3239-7773","contributorId":294389,"corporation":false,"usgs":false,"family":"Gorr","given":"Alexander","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoch, Olivia J. 0000-0002-1327-7100","orcid":"https://orcid.org/0000-0002-1327-7100","contributorId":306177,"corporation":false,"usgs":true,"family":"Hoch","given":"Olivia","email":"","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":911618,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beers, Rebecca 0000-0001-5649-6525","orcid":"https://orcid.org/0000-0001-5649-6525","contributorId":306179,"corporation":false,"usgs":false,"family":"Beers","given":"Rebecca","email":"","affiliations":[{"id":34160,"text":"Arizona Geological Survey","active":true,"usgs":false}],"preferred":false,"id":911619,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Porter, Ryan 0000-0002-6734-3257","orcid":"https://orcid.org/0000-0002-6734-3257","contributorId":343663,"corporation":false,"usgs":false,"family":"Porter","given":"Ryan","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":911620,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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