{"pageNumber":"136","pageRowStart":"3375","pageSize":"25","recordCount":46647,"records":[{"id":70237964,"text":"ofr20221096 - 2022 - Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","interactions":[],"lastModifiedDate":"2023-09-18T20:04:08.872815","indexId":"ofr20221096","displayToPublicDate":"2022-11-01T08:50:41","publicationYear":"2022","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":"2022-1096","displayTitle":"Assessing the Efficacy of Using a Parentage-Based Tagging Survival Model to Evaluate Two Sources of Mortality for Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","title":"Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","docAbstract":"

We conducted a study to assess the efficacy of using a parentage-based tagging survival model (PBT N-mixture model) to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon. The model was originally developed to evaluate reservoir mortality because of predation from piscivorous fish. However, recent studies have also found that juvenile Chinook salmon experience high infection rates from parasitic copepods (Salmincola californiensis), which are known to negatively affect performance and survival. Our study was conducted to determine if the PBT N-mixture model could separately estimate mortality because of predation from non-native fish and mortality resulting from copepod infection. This assessment was conducted in two parts: (1) data collected in Lookout Point Reservoir during 2018 were re-analyzed; and (2) a simulation was conducted to evaluate a multi-year study that included inter-annual variation in copepod infection rate and two subsampling strategies (10 fish per month, 30 fish per month) to characterize monthly copepod infection rate. Results from each of these efforts suggest that the survival model is unlikely to provide reliable survival estimates for the two mortality sources that we evaluated. The re-analysis of 2018 data showed that “predation only” and “copepod only” models estimated a negative coefficient for the respective covariate, but the model that included both covariates provided coefficient estimates that differed from the other models and were highly uncertain. Similarly, the simulation results showed that most models failed to correctly estimate the magnitude and direction of mortality due to predation and copepods. These results suggest that additional data will be required if a model is desired that can separately estimate mortality effects due to both predation and copepods in the future. The existing data are limited by factors including low detection probabilities from previous field studies, existing uncertainties about copepod effects on mortality in a natural setting and expected limitations in the number of years that a field study could realistically be expected to receive funding.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221096","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hance, D.J., Kock, T.J., Perry, R.W., and Pope, A.C., 2022, Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon: U.S. Geological Survey Open-File Report 2022–1096, 14 p., https://doi.org/10.3133/ofr20221096.","productDescription":"v, 14 p.","onlineOnly":"Y","ipdsId":"IP-141621","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":408997,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.XML"},{"id":408996,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1096/images"},{"id":408995,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221096/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1096"},{"id":408994,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1096"},{"id":408993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1096/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.84577497588536,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.952222617898286\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishedDate":"2022-11-01","noUsgsAuthors":false,"publicationDate":"2022-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton J. 0000-0002-4475-706X dhance@usgs.gov","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":206496,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","email":"dhance@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Adam C. 0000-0002-7253-2247 apope@usgs.gov","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":5664,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","email":"apope@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":856396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238799,"text":"70238799 - 2022 - New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications","interactions":[],"lastModifiedDate":"2022-12-13T14:27:49.816431","indexId":"70238799","displayToPublicDate":"2022-11-01T08:11:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications","docAbstract":"

Using new remote sensing technology to study agricultural crops will support advances in food and water security. The recently launched, new generation spaceborne hyperspectral sensors, German DLR Earth Sensing Imaging Spectrometer (DESIS) and Italian PRecursore IperSpettrale della Missione Applicativa (PRISMA), provide unprecedented data in hundreds of narrow spectral bands for the study of the Earth. Therefore, our overarching goal in this study was to use these data to explore advances that can be made in agricultural research. We selected PRISMA and DESIS images during the 2020 growing season in California's Central Valley to study seven major crops. PRISMA and DESIS images were highly correlated (R 2of 0.9–0.95). Out of the 235 DESIS bands (400–1000 nm) and 238 PRISMA bands (400–2500 nm), 26 (11%) and 45 (19%) bands, respectively, were optimal to study agricultural crops. These optimal bands provided crop type classification accuracies of 83–90%. Hyperspectral vegetation indices to estimate plant pigment content, stress, biomass, moisture, and cellulose/lignin content were also identified.

","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.22-00039R2","usgsCitation":"Aneece, I.P., and Thenkabail, P., 2022, New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications: Photogrammetric Engineering & Remote Sensing, v. 88, no. 11, p. 715-729, https://doi.org/10.14358/PERS.22-00039R2.","productDescription":"15 p.","startPage":"715","endPage":"729","ipdsId":"IP-137552","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":445966,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.22-00039r2","text":"Publisher Index Page"},{"id":435634,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98LO5D4","text":"USGS data release","linkHelpText":"DESIS and PRISMA spectral library of agricultural crops in California's Central Valley in the 2020 Growing Season"},{"id":410361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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,\n 37.15\n ],\n [\n -121,\n 36.75\n ],\n [\n -120.333,\n 36.75\n ],\n [\n -120.333,\n 37.15\n ],\n [\n -121,\n 37.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aneece, Itiya P. 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":208265,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","middleInitial":"P.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":858748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":858749,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238321,"text":"70238321 - 2022 - Gaining decision-maker confidence through community consensus: Developing environmental DNA standards for data display on the USGS Nonindigenous Aquatic Species database","interactions":[],"lastModifiedDate":"2022-11-16T12:50:55.92911","indexId":"70238321","displayToPublicDate":"2022-11-01T06:49:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Gaining decision-maker confidence through community consensus: Developing environmental DNA standards for data display on the USGS Nonindigenous Aquatic Species database","docAbstract":"

To advance national efforts for the detection and biosurveillance of aquatic invasive species (AIS), we employed a community consensus process to enable the incorporation of environmental DNA (eDNA) detection data into the U.S. Geological Survey’s (USGS) Nonindigenous Aquatic Species (NAS) database (https://nas.er.usgs.gov/eDNA/). Our goal was to identify minimum standards and best practices for the verification of eDNA data by working closely with AIS eDNA community practitioners and natural resource managers across government, private and academic sectors. To better inform management decisions, verified AIS eDNA data will be displayed on a separate mapping layer alongside visual sighting data with the inclusion of additional information on the eDNA methods employed to collect and produce the data. To allow for eDNA data display, we produced consensus derived online documents including a submission application and data submission template and are developing a guidance document for detailing the eDNA data submission process. We also developed a communication plan including a mechanism for reporting detections to appropriate managers for consideration prior to display. The products of these efforts are an application and data submission process that will be used in the new environmental DNA data layer on the Nonindigenous Aquatic Species (NAS) database. Herein, we detail how we engaged the eDNA community for consensus of our standards, share lessons learned from the process, and describe the benefits of such an approach at instilling confidence among the research and decision-maker community.

","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","usgsCitation":"Ferrante, J., Daniel, W., Freedman, J.A., Klymus, K.E., Neilson, M., Passamaneck, Y., Rees, C., Sepulveda, A.J., and Hunter, M., 2022, Gaining decision-maker confidence through community consensus: Developing environmental DNA standards for data display on the USGS Nonindigenous Aquatic Species database: Management of Biological Invasions, v. 13, no. 4, p. 809-832.","productDescription":"24 p.","startPage":"809","endPage":"832","ipdsId":"IP-137639","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":409381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409373,"type":{"id":15,"text":"Index Page"},"url":"https://www.reabic.net/journals/mbi/2022/Issue4.aspx"}],"volume":"13","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferrante, Jason 0000-0003-3453-4636","orcid":"https://orcid.org/0000-0003-3453-4636","contributorId":214738,"corporation":false,"usgs":true,"family":"Ferrante","given":"Jason","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219320,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freedman, Jonathan Adam 0000-0001-7140-8028","orcid":"https://orcid.org/0000-0001-7140-8028","contributorId":224222,"corporation":false,"usgs":true,"family":"Freedman","given":"Jonathan","email":"","middleInitial":"Adam","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":857089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":219310,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857090,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Passamaneck, Yale","contributorId":270026,"corporation":false,"usgs":false,"family":"Passamaneck","given":"Yale","affiliations":[],"preferred":false,"id":857091,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rees, Christopher B.","contributorId":196308,"corporation":false,"usgs":false,"family":"Rees","given":"Christopher B.","affiliations":[],"preferred":false,"id":857092,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":857093,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207584,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857094,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266792,"text":"70266792 - 2022 - A statistical framework for modelling migration corridors","interactions":[],"lastModifiedDate":"2025-05-13T15:19:21.848873","indexId":"70266792","displayToPublicDate":"2022-11-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework for modelling migration corridors","docAbstract":"

1. Management of animal populations requires spatially explicit knowledge of movement corridors, such as those used during seasonal migrations. GPS tracking data allows for mapping of corridors from directly observed movements, providing important insights, but tracking data is absent for many populations.

2. We developed a novel statistical corridor modeling approach that predicts movement corridors from cost-distance movement models fit directly to migration tracking data. Unlike existing predictive approaches, this does not require the ad-hoc transformation of habitat suitability surfaces into resistance surfaces. We tested the ability of the approach to recover parameters used to generate simulated movements. We then used GPS data from three migrating mule deer (Odocoileus hemionus) herds in Idaho and Wyoming to model corridors as a function of elevation, slope, aspect, percent shrub, date of peak green-up, snow-off date, and human footprint. We assessed the predictive ability of the fitted models using validation tracks from the same herd as well as from the other herds.

3. The approach reproduced parameters used to generate the simulated movements, predicted the corridors used by migratory populations, and described the direction, magnitude, and confidence levels of the effects of environmental variables on corridors. The effects environmental variables had on corridors differed depending on the herd. Within-herd validation indicated that fitted corridor models are more accurate at predicting migration corridors than null models, and cross-herd validation indicated that fitted models for some herds accurately predicted the observed migrations of other herds.

4. In addition to the practical benefit of mapping corridors for management, our statistical corridor modeling framework sets the stage for evaluating fundamental questions about the fitness tradeoffs, navigation, learning, fidelity, and movement constraints that influence migratory and other corridor-generating behavior. Models of predictive corridors can inform management and planning for the conservation of migrations across taxa, including the potential restoration of corridors. Our corridor modeling approach is also readily applied to non-migratory animal movements.

","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210x.13969","usgsCitation":"Nuñez, T., Hurley, M., Graves, T., Ortega, A., Sawyer, H., Fattebert, J., Merkle, J., and Kauffman, M., 2022, A statistical framework for modelling migration corridors: Methods in Ecology and Evolution, v. 13, no. 11, p. 2635-2648, https://doi.org/10.1111/2041-210x.13969.","productDescription":"14 p.","startPage":"2635","endPage":"2648","ipdsId":"IP-136728","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13969","text":"Publisher Index Page"},{"id":485818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.51571099773642,\n 45.9008891737889\n ],\n [\n -116.51571099773642,\n 42.05335013528642\n ],\n [\n -108.42991483721727,\n 42.05335013528642\n ],\n [\n -108.42991483721727,\n 45.9008891737889\n ],\n [\n -116.51571099773642,\n 45.9008891737889\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Nuñez, Tristan A.","contributorId":355041,"corporation":false,"usgs":false,"family":"Nuñez","given":"Tristan A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurley, Mark A.","contributorId":355042,"corporation":false,"usgs":false,"family":"Hurley","given":"Mark A.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":936790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ortega, Anna C.","contributorId":355044,"corporation":false,"usgs":false,"family":"Ortega","given":"Anna C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawyer, Hall","contributorId":355048,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[{"id":84702,"text":"Western EcoSystems Technology (WEST), Inc.,","active":true,"usgs":false}],"preferred":false,"id":936793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fattebert, Julien","contributorId":355051,"corporation":false,"usgs":false,"family":"Fattebert","given":"Julien","affiliations":[{"id":84703,"text":"University of Wyoming,","active":true,"usgs":false}],"preferred":false,"id":936794,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Merkle, Jerod A.","contributorId":355052,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936795,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936796,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70237675,"text":"dr1164 - 2022 - Materials flow in the United States—A global context, 1900–2020","interactions":[{"subject":{"id":70190027,"text":"fs20173062 - 2017 - Use of raw materials in the United States from 1900 through 2014","indexId":"fs20173062","publicationYear":"2017","noYear":false,"title":"Use of raw materials in the United States from 1900 through 2014"},"predicate":"SUPERSEDED_BY","object":{"id":70237675,"text":"dr1164 - 2022 - Materials flow in the United States—A global context, 1900–2020","indexId":"dr1164","publicationYear":"2022","noYear":false,"title":"Materials flow in the United States—A global context, 1900–2020"},"id":1}],"lastModifiedDate":"2026-03-18T19:37:01.949605","indexId":"dr1164","displayToPublicDate":"2022-10-31T08:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1164","displayTitle":"Materials Flow in the United States—A Global Context, 1900–2020","title":"Materials flow in the United States—A global context, 1900–2020","docAbstract":"

Introduction

During the last 12 decades (1900–2020), the amounts of raw materials used in the United States have increased significantly due to economic development, technological innovations, and population growth. Data on materials are presented here to provide an overview of the annual quantities (measured in physical terms) required for the standard of living in the United States and to provide insights into the consumption trajectory that developing countries may follow. The consumption patterns driving the use of raw materials were analyzed through the lens of economic disruptions and expansions during this period, illustrating the linkages between the selected materials and economic development. These annual material inputs to the U.S. economy (excluding food or fuel) were also analyzed in a global context. The data used were gathered by various agencies and compiled by the U.S. Geological Survey.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1164","collaboration":"National Minerals Information Center","usgsCitation":"Matos, G.R., 2022, Materials flow in the United States—A global context, 1900–2020: U.S. Geological Survey Data Report 1164, 23 p., https://doi.org/10.3133/dr1164. 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Center Director, National Minerals Information Center
U.S. Geological Survey
991 National Center
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-10-31","noUsgsAuthors":false,"publicationDate":"2022-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Matos, Grecia R. 0000-0002-3285-3070 gmatos@usgs.gov","orcid":"https://orcid.org/0000-0002-3285-3070","contributorId":2656,"corporation":false,"usgs":true,"family":"Matos","given":"Grecia","email":"gmatos@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":854946,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238109,"text":"70238109 - 2022 - Know what you don't know: Embracing state uncertainty in disease-structured multistate models","interactions":[],"lastModifiedDate":"2022-12-15T15:44:51.910487","indexId":"70238109","displayToPublicDate":"2022-10-31T07:27:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Know what you don't know: Embracing state uncertainty in disease-structured multistate models","docAbstract":"
  1. Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observed without ambiguity. However, state uncertainty is a pervasive feature of many ecological studies, and multievent models were developed to explicitly account for it.
  2. We developed a novel extended multievent mark–recapture model that incorporates state uncertainty at multiple levels of detection. Using a disease-structured example, both false negative and false positive state assignment errors are modelled at two levels of state assignment—the pathogen sampling process and the diagnostic process that samples are subjected to. We additionally describe methods to jointly model infection intensity to integrate heterogeneity in ecological parameters, such as mortality and infection dynamics, and the pathogen detection processes. We provide code to simulate and analyse datasets with various underlying ecological processes and fit our model to a mark–recapture dataset of Mixophyes fleayi (Fleay's barred frog) infected with the amphibian chytrid fungus (Batrachochytrium dendrobatidis, Bd).
  3. In our case study, we found evidence for various state assignment errors: the sampling protocol performed poorly in detecting Bd, pathogen detection was highly dependent on infection intensity and false positives were non-negligible. Incorporating state uncertainty yielded significantly higher estimates of infection prevalence and 4–5 times lower rates of infection state transitions compared to those obtained from a traditional multistate model.
  4. Our results highlight that incorporating state assignment errors improves inference on the ecological process, especially when sensitivity and specificity of the state assignment processes are low. The general model structure can be applied to other HMMs, providing a foundation for modelling state uncertainty in related models. For disease-structured multistate models, we recommend conducting robust design surveys and collecting samples during each capture event to facilitate incorporating pathogen detection errors.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13993","usgsCitation":"Hollanders, M., and Royle, A., 2022, Know what you don't know: Embracing state uncertainty in disease-structured multistate models: Methods in Ecology and Evolution, v. 13, no. 12, p. 2827-2837, https://doi.org/10.1111/2041-210X.13993.","productDescription":"11 p.","startPage":"2827","endPage":"2837","ipdsId":"IP-143355","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13993","text":"Publisher Index Page"},{"id":409291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Hollanders, Matthijs","contributorId":299029,"corporation":false,"usgs":false,"family":"Hollanders","given":"Matthijs","email":"","affiliations":[{"id":64751,"text":"Southern Cross University, Lismore, New South Wales","active":true,"usgs":false}],"preferred":false,"id":856901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":856902,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238396,"text":"70238396 - 2022 - A characterization of the deep-sea coral and sponge community along the California, Oregon, and Washington coasts using a remotely operated vehicle on the EXPRESS 2019 expedition","interactions":[],"lastModifiedDate":"2023-03-28T15:33:35.490838","indexId":"70238396","displayToPublicDate":"2022-10-31T07:13:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"A characterization of the deep-sea coral and sponge community along the California, Oregon, and Washington coasts using a remotely operated vehicle on the EXPRESS 2019 expedition","docAbstract":"

NOAA’s Deep-Sea Coral Research Technology Program (DSCRTP) began a 4-year funding initiative for the U.S. West Coast in 2018. The goals of the West Coast Deep-Sea Coral Initiative were to: 1) gather baseline information on DSCS in areas subject to fishing regulation changes prior to the implementation of Amendment 28; 2) improve our understanding of known DSCS bycatch “hot spots”; and 3) explore and assess DSCS resources within NOAA National Marine Sanctuaries with emphasis on areas of sanctuary resource protection and management concerns. Following the 2018 research expedition supported by NOAA Ship Bell M. Shimada (Laidig et al., 2021), a second research cruise was planned for 2019 to further survey seafloor communities in priority areas off the West Coast from Washington to California. The 2019 expedition spanned 35 days (4 Oct – 7 Nov) and was conducted from the NOAA Ship Reuben Lasker (hereafter referred to as “the ship”), beginning and ending in San Diego, CA. Surveys were conducted in deeper areas (generally 500-1200 m) in 2019 than in 2018 (limited to <650 m). These two expeditions provide data on seafloor communities and DSCS assemblages over a broad range of depths 50-1200 m.

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Lizzie","contributorId":270134,"corporation":false,"usgs":false,"family":"Duncan","given":"Lizzie","email":"","affiliations":[{"id":56094,"text":"NOAA, NOS, Channel Islands National Marine Sanctuary, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":857361,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clarke, Liz","contributorId":270135,"corporation":false,"usgs":false,"family":"Clarke","given":"Liz","email":"","affiliations":[{"id":56092,"text":"NOAA Fisheries, NWFSC, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":857362,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caldow, Chris","contributorId":66501,"corporation":false,"usgs":true,"family":"Caldow","given":"Chris","email":"","affiliations":[],"preferred":false,"id":857363,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857364,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClain Counts, Jennifer 0000-0002-3383-5472","orcid":"https://orcid.org/0000-0002-3383-5472","contributorId":219233,"corporation":false,"usgs":true,"family":"McClain Counts","given":"Jennifer","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857365,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857366,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70239143,"text":"70239143 - 2022 - On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations","interactions":[],"lastModifiedDate":"2022-12-29T13:12:05.588882","indexId":"70239143","displayToPublicDate":"2022-10-31T07:09:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12989,"text":"Journal of Geophysical Research--Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations","docAbstract":"

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments (\"urn:x-wiley:21699313:media:jgrb55931:jgrb55931-math-0001\"2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB025202","usgsCitation":"Mancini, S., Segou, M., Werner, M.J., Parsons, T.E., Beroza, G.C., and Chiaraluce, L., 2022, On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations: Journal of Geophysical Research--Solid Earth, v. 127, no. 11, e2022JB025202, 16 p., https://doi.org/10.1029/2022JB025202.","productDescription":"e2022JB025202, 16 p.","ipdsId":"IP-143668","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445979,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022jb025202","text":"External Repository"},{"id":411176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 12.153022380111537,\n 43.88263963722096\n ],\n [\n 12.153022380111537,\n 42.213562034839185\n ],\n [\n 14.568988554409458,\n 42.213562034839185\n ],\n [\n 14.568988554409458,\n 43.88263963722096\n ],\n [\n 12.153022380111537,\n 43.88263963722096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mancini, Simone 0000-0003-3415-2080","orcid":"https://orcid.org/0000-0003-3415-2080","contributorId":225525,"corporation":false,"usgs":false,"family":"Mancini","given":"Simone","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":860333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segou, Margarita","contributorId":199044,"corporation":false,"usgs":false,"family":"Segou","given":"Margarita","affiliations":[],"preferred":false,"id":860334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Werner, Maximillan J.","contributorId":194147,"corporation":false,"usgs":false,"family":"Werner","given":"Maximillan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":860335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":860336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":860337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chiaraluce, Lauro","contributorId":300501,"corporation":false,"usgs":false,"family":"Chiaraluce","given":"Lauro","email":"","affiliations":[{"id":35766,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":860338,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238017,"text":"70238017 - 2022 - An evaluation of transmitter effects on adult and juvenile Common Terns using leg-loop harness attachments","interactions":[],"lastModifiedDate":"2022-11-04T11:55:14.66042","indexId":"70238017","displayToPublicDate":"2022-10-31T06:53:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of transmitter effects on adult and juvenile Common Terns using leg-loop harness attachments","docAbstract":"

Marking birds with transmitters allows for the collection of data that are critical for fully understanding avian life history, but researchers must also be confident that performing such studies is as safe as possible for transmittered individuals. While much could be learned from tracking juveniles across dependency periods and first migration, doing so would require a harness-based attachment method which has not been evaluated on any species of juvenile tern. Therefore, we monitored the reproductive success and behavior of adult Common Terns (Sterna hirundo) and the growth and behavior of juvenile Common Terns after attaching transmitters to adults and juveniles with leg-loop harnesses made of elastic cord. We found that transmittered adults had similar reproductive success to untransmittered controls (hatching success for nests of transmittered adults = 0.553; nests of control adults = 0.665). Transmittered adults also expressed minimal behavioral differences from untransmittered controls when the groups were compared via paired treatment-control nest observations along with observations away from the nest. Transmittered juveniles had similar fledging success and growth rates to untransmittered control juveniles (fledging success for transmittered juveniles = 0.766; control juveniles = 0.817). Transmittered juveniles exhibited slight differences in behavior from controls, with increased rates of preening, although these differences did not appear to be detrimental. Finally, monitoring efforts during the breeding season following transmitter deployment found no difference in the return rate, nesting attempt rate, or hatching success rate based on treatment (P > 0.05). However, despite evidence of an individual retaining its transmitter into fall migration, no individuals retained their transmitters when resighted the following breeding season. While our results show that leg-loop harnesses made of elastic cord present a potential option for transmitter attachment to both adult and juvenile Common Terns, additional testing could provide further insight into potential long-term impacts.

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/JFO-00136-930403","usgsCitation":"Buck, E., Sullivan, J.D., Teitelbaum, C.S., Brinker, D.F., McGowan, P.C., and Prosser, D., 2022, An evaluation of transmitter effects on adult and juvenile Common Terns using leg-loop harness attachments: Journal of Field Ornithology, v. 93, no. 4, 3, 23 p., https://doi.org/10.5751/JFO-00136-930403.","productDescription":"3, 23 p.","ipdsId":"IP-141312","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445982,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/jfo-00136-930403","text":"Publisher Index Page"},{"id":435635,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IF16T5","text":"USGS data release","linkHelpText":"Data describing the effects of elastic leg-loop harnesses on adult and juvenile Common Terns"},{"id":409154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buck, Evan J","contributorId":265821,"corporation":false,"usgs":false,"family":"Buck","given":"Evan J","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":856580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":856581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teitelbaum, Claire S. 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":255382,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":856582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brinker, David F.","contributorId":207103,"corporation":false,"usgs":false,"family":"Brinker","given":"David","email":"","middleInitial":"F.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":856583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":856584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":856585,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237988,"text":"70237988 - 2022 - Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","interactions":[],"lastModifiedDate":"2022-11-16T17:25:45.53204","indexId":"70237988","displayToPublicDate":"2022-10-31T06:52:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","docAbstract":"

Monitoring changes in the distribution of large carnivores is important for managing human safety and supporting conservation. Throughout much of their range, polar bears (Ursus maritimus) are increasingly using terrestrial habitats in response to Arctic sea ice decline. Their increased presence in coastal areas has implications for bear-human conflict, inter-species interactions, and polar bear health and survival. We examined observed trends in land use over three decades by polar bears in the southern Beaufort Sea (SB) and Chukchi Sea (CS) where bears have traditionally spent most of the year on the sea ice. Using data from 408 adult females fitted with satellite radio-collars, we examined trends in the annual proportion of bears coming onshore (hereafter referred to as “percent of bears”) during the summer for ≥21 days, arrival and departure dates, duration spent onshore and relationships with sea ice metrics. We then estimated future land use through 2040 by extrapolating trends and by combining observed relationships between land use and sea ice with projections of future sea ice from an ensemble of earth system models. The observed percent of bears summering onshore and their duration onshore was correlated with the percent of open water that occurred within their population’s range between July and October. As sea ice declined, the percent of bears summering onshore increased from ~5 to 30% in the SB and ~10 to 50% in the CS and duration onshore increased by >30 days to 60–70 days in both populations. Using a range of greenhouse gas emission scenarios and adjustments for faster than forecasted sea ice loss we estimated that 50-62% of SB and 79-88% of CS bears will spend 90–108 and 110–126 days onshore during summer in the SB and CS, respectively, by 2040. Sea ice projections varied little between greenhouse gas emission scenarios prior to 2040 but diverged thereafter. Observed and forecasted increases in polar bear land occupancy puts more bears in proximity to human activities and settlements for longer durations while extending the lack of access to their primary prey. Because human conflict is one of the primary factors affecting the conservation of large carnivores worldwide, mitigation of bear-human interactions on land will be an increasingly important component of polar bear conservation.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02319","usgsCitation":"Rode, K.D., Douglas, D.C., Atwood, T.C., Durner, G.M., Wilson, R., and Pagano, A.M., 2022, Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040: Global Ecology and Conservation, v. 40, e02319, 21 p., https://doi.org/10.1016/j.gecco.2022.e02319.","productDescription":"e02319, 21 p.","ipdsId":"IP-144828","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445984,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02319","text":"Publisher Index Page"},{"id":435636,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XEOBWV","text":"USGS data release","linkHelpText":"Polar Bear Continuous Time-Correlated Random Walk (CTCRW) Location Data Derived from Satellite Location Data, Chukchi and Beaufort Seas, July-November 1985-2017"},{"id":409057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 179.9,\n 80\n ],\n [\n 158.6872334047083,\n 80\n ],\n [\n 158.6872334047083,\n 54\n ],\n [\n 179.9,\n 54\n ],\n [\n 179.9,\n 80\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.5651724337921,\n 80\n ],\n [\n -179.9,\n 80\n ],\n [\n -179.9,\n 65\n ],\n [\n -103.5651724337921,\n 65\n ],\n [\n -103.5651724337921,\n 80\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160,\n 65\n ],\n [\n -179.9,\n 65\n ],\n [\n -179.9,\n 54\n ],\n [\n -160,\n 54\n ],\n [\n -160,\n 65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":856441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":856442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":856443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":856444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Ryan R. ","contributorId":222456,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan R. ","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":856445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":856446,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237947,"text":"70237947 - 2022 - Modeling geomagnetic induction in submarine cables","interactions":[],"lastModifiedDate":"2022-11-01T11:54:23.10118","indexId":"70237947","displayToPublicDate":"2022-10-31T06:48:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12804,"text":"Frontiers in Physics","active":true,"publicationSubtype":{"id":10}},"title":"Modeling geomagnetic induction in submarine cables","docAbstract":"

Submarine cables have become a vital component of modern infrastructure, but past submarine cable natural hazard studies have mostly focused on potential cable damage from landslides and tsunamis. A handful of studies examine the possibility of space weather effects in submarine cables. The main purpose of this study is to develop a computational model, using Python, of geomagnetic induction on submarine cables. The model is used to estimate the induced voltage in the submarine cables in response to geomagnetic disturbances. It also utilizes newly acquired knowledge from magnetotelluric studies and associated investigations of geomagnetically induced currents in power systems. We describe the Python-based software, its working principle, inputs/outputs based on synthetic geomagnetic field data, and compare its operational capabilities against analytical solutions. We present the results for different model inputs, and find: 1) the seawater layer acts as a shield in the induction process: the greater the ocean depth, the smaller the seafloor geoelectric field; and 2) the model is sensitive to the Ocean-Earth layered conductivity structure.

","language":"English","publisher":"Frontiers","doi":"10.3389/fphy.2022.1022475","usgsCitation":"Chakraborty, S., Boteler, D.H., Shi, X., Murphy, B.S., Hartinger, M.D., Wang, X., Lucas, G., and Baker, J.B., 2022, Modeling geomagnetic induction in submarine cables: Frontiers in Physics, v. 10, 1022475, 14 p., https://doi.org/10.3389/fphy.2022.1022475.","productDescription":"1022475, 14 p.","ipdsId":"IP-145634","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":445987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fphy.2022.1022475","text":"Publisher Index Page"},{"id":408969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Chakraborty, Shibaji","contributorId":298710,"corporation":false,"usgs":false,"family":"Chakraborty","given":"Shibaji","email":"","affiliations":[{"id":64669,"text":"Center for Space Science and Engineering Research, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":856297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boteler, David H.","contributorId":298711,"corporation":false,"usgs":false,"family":"Boteler","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":856298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Xueling 0000-0001-8425-8241","orcid":"https://orcid.org/0000-0001-8425-8241","contributorId":296644,"corporation":false,"usgs":false,"family":"Shi","given":"Xueling","email":"","affiliations":[{"id":64114,"text":"Virginia Tech; NCAR High Altitude Observatory","active":true,"usgs":false}],"preferred":false,"id":856299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":856300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartinger, Michael D.","contributorId":298712,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":48422,"text":"Space Science Institute","active":true,"usgs":false}],"preferred":false,"id":856301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xuan","contributorId":298713,"corporation":false,"usgs":false,"family":"Wang","given":"Xuan","email":"","affiliations":[{"id":64670,"text":"Department of Electrical Engineering, Tsinghua University","active":true,"usgs":false}],"preferred":false,"id":856302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":856303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baker, Joseph B. H. 0000-0001-6255-3039","orcid":"https://orcid.org/0000-0001-6255-3039","contributorId":296646,"corporation":false,"usgs":false,"family":"Baker","given":"Joseph","email":"","middleInitial":"B. H.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":856304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70241063,"text":"70241063 - 2022 - Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis","interactions":[],"lastModifiedDate":"2023-03-08T15:37:45.932866","indexId":"70241063","displayToPublicDate":"2022-10-29T09:32:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis","docAbstract":"

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2022.103385","usgsCitation":"Wood, N.J., Pennaz, A., Marineau, J., Jones, J.M., Jones, J., Ng, P., and Henry, K., 2022, Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis: International Journal of Disaster Risk Reduction, v. 82, 103385, 15 p., https://doi.org/10.1016/j.ijdrr.2022.103385.","productDescription":"103385, 15 p.","ipdsId":"IP-142283","costCenters":[{"id":459,"text":"Natural Hazards Mission Area","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":445992,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2022.103385","text":"Publisher Index Page"},{"id":435637,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RKTXCT","text":"USGS data release","linkHelpText":"Threat prioritization framework and input data for a multi-hazard risk analysis for the U.S. Department of the Interior"},{"id":413865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413841,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/632254d1d34e71c6d67ab690"}],"volume":"82","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":865923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pennaz, Alice 0000-0002-7336-2761","orcid":"https://orcid.org/0000-0002-7336-2761","contributorId":205792,"corporation":false,"usgs":true,"family":"Pennaz","given":"Alice","email":"","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":865924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marineau, Jason","contributorId":213192,"corporation":false,"usgs":false,"family":"Marineau","given":"Jason","email":"","affiliations":[{"id":38714,"text":"Department of Interior Office of Emergency Management","active":true,"usgs":false}],"preferred":false,"id":865925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":865926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Jamie 0000-0002-9967-3314 jamiejones@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":204514,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie","email":"jamiejones@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":865927,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ng, Peter 0000-0001-8509-5544 png@usgs.gov","orcid":"https://orcid.org/0000-0001-8509-5544","contributorId":3317,"corporation":false,"usgs":true,"family":"Ng","given":"Peter","email":"png@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":865928,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Henry, Kevin 0000-0001-9314-2531 khenry@usgs.gov","orcid":"https://orcid.org/0000-0001-9314-2531","contributorId":176934,"corporation":false,"usgs":true,"family":"Henry","given":"Kevin","email":"khenry@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":865929,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237766,"text":"sim3491 - 2022 - Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont","interactions":[],"lastModifiedDate":"2026-04-01T15:22:38.069829","indexId":"sim3491","displayToPublicDate":"2022-10-28T11:30:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3491","displayTitle":"Bedrock Geologic Map of the Crown Point Quadrangle, Essex County, New York, and Addison County, Vermont","title":"Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont","docAbstract":"

The bedrock geology of the 7.5-minute Crown Point quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of granitic orthogneiss at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the host rocks. Subsequent D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into previously deformed lithologies. The LMG crystallized at approximately 1.15 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation during D3 produced F3 folds exhibited in regional domes and basins, such as the Keeney Mountain synform, local reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. Cambrian-Ordovician stratigraphy records an approximately 1-km-thick section and a transition from synrift clastics to passive margin peritidal carbonate buildups to gradually deeper water subtidal to shelf carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations and large areas of artificial fill.

This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Scientific Investigations Map of the Crown Point 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, three cross sections, and a simplified surficial geologic map that includes lidar percent slope. The explanatory pamphlet includes a discussion of the geology.

The bedrock geologic map on the map sheet is multi-layered and has been designed to enable the user to turn off the surficial map layer to view the concealed bedrock map units.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3491","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Orndorff, R.C., and McAleer, R.J., 2022, Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Scientific Investigations Map 3491, 1 sheet, scale 1:24,000, 44-p. pamphlet, https://doi.org/10.3133/sim3491.","productDescription":"Pamphlet: viii, 44 p.; Sheet: 62.00 x 41.00 inches; Base Map; Database; Metadata","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117525","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435638,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FHRNVU","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":410043,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_sheet1.pdf","size":"178 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408680,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_metadata.zip","size":"216 KB","linkFileType":{"id":6,"text":"zip"}},{"id":408682,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_basemap.zip","text":"Topographic Spatial Data","size":"119 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408679,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_database.zip","size":"4.40 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408674,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_pamphlet.pdf","text":"Pamphlet","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3491"},{"id":408673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3491/coverthb.jpg"},{"id":501933,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113783.htm","linkFileType":{"id":5,"text":"html"}},{"id":408681,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_openaccess.zip","text":"Open Access","size":"6.29 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Crown Point quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44\n ],\n [\n -73.5,\n 43.875\n ],\n [\n -73.375,\n 43.875\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.5,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-10-28","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":265307,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":855539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":855540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":855541,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237865,"text":"sir20225071 - 2022 - Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, using controlled-source audio-frequency magnetotelluric (CSAMT) surveys","interactions":[],"lastModifiedDate":"2022-10-31T11:37:48.874291","indexId":"sir20225071","displayToPublicDate":"2022-10-28T10:05:15","publicationYear":"2022","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":"2022-5071","displayTitle":"Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, Using Controlled-Source Audio-Frequency Magnetotelluric (CSAMT) Surveys","title":"Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, using controlled-source audio-frequency magnetotelluric (CSAMT) surveys","docAbstract":"

The Sevier/Toroweap Fault Zone is a major north-south-striking fault located in northern Arizona and southwestern Utah. In partnership with the National Park Service, the U.S. Geological Survey conducted two geophysical controlled-source audio-frequency magnetotelluric (CSAMT) surveys that transected the Sevier/Toroweap Fault Zone at Clay Flat, Utah, a potential pull-apart basin, west of a site of proposed groundwater pumping to evaluate the subsurface hydrogeology. The goal of the surveys was to enhance understanding of the interconnectedness of the Navajo aquifer, the region’s primary groundwater source, across two groundwater basins to the east and west of the fault zone, Water Rights Area (WRA) 81 and WRA 85.

In the Kane County, Utah, area, the Sevier/Toroweap Fault Zone consists of the Sevier section (to the north) and the northern Toroweap section (to the south). Two survey lines totaling 7 kilometers of CSAMT survey data were collected. The CSAMT survey line SV1 transected both the Sevier section and the northern Toroweap section of the fault zone; survey line SV2 transected only the Sevier section. Although offset of the Navajo Sandstone, the main component of the Navajo aquifer, by the Sevier/Toroweap Fault Zone is generally accepted as the geologic reason that the Navajo aquifer is disconnected in the study area, results of the CSAMT surveys suggest that vertical offset of the Navajo Sandstone of the Glen Canyon Group across the Sevier/Toroweap Fault Zone is insufficient to completely disconnect the aquifer in the study area. The effects of faulting on groundwater north and south of the study area, where offset of water-bearing layers may be greater, requires further study. A clearer understanding of groundwater movement across the Sevier /Toroweap Fault Zone will aid water-resource managers in making informed decisions concerning groundwater rights.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225071","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Jones, C.J.R., Robinson, M.J., and Macy, J.P., 2022, Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, using controlled-source audio-frequency magnetotelluric (CSAMT) surveys: U.S. Geological Survey Scientific Investigations Report 2022–5071, 14 p., https://doi.org/10.3133/sir20225071.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-133730","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":408827,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5071/covrthb.jpg"},{"id":408828,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5071/sir20225071.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408830,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF9PFR","text":"Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah (ver. 2.0, July 2022)","description":"Robinson, M.J., and Macy, J.P., 2022, Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah: U.S. Geological Survey data release, https://doi.org/10.5066/P9QF9PFR."}],"country":"United States","state":"Utah","county":"Kane County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.97309886757559,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.55221820418316\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director,
Arizona Water Science Center
U.S. Geological Survey
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To cope with complex environmental impacts in a changing climate, researchers are increasingly being asked to produce science that can directly support policy and decision making. To achieve such societal impact, scientists are using climate services to engage directly with stakeholders to better understand their needs and inform knowledge production. However, the wide variety of climate-services outcomes—ranging from establishing collegial relationships with stakeholders to obtaining specific information for inclusion into a pre-existing decision process—do not directly connect to traditional methods of measuring scientific impact (e.g., publication citations, journal impact factor). In this paper, we describe how concepts from the discipline of evaluation can be used to examine the societal impacts of climate services. We also present a case study from climate impacts and adaptation research to test a scalable evaluation approach. Those who conduct research for the purposes of climate services and those who fund applied climate research would benefit from evaluation from the beginning of project development. Doing so will help ensure that the approach, data collection, and data analysis are appropriately conceived and executed.

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mortality and mitigation at wind power facilities","interactions":[],"lastModifiedDate":"2022-10-28T14:24:08.947566","indexId":"70237878","displayToPublicDate":"2022-10-28T09:16:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Limited rigor in studies of raptor mortality and mitigation at wind power facilities","docAbstract":"

Wind power is an expanding source of renewable energy. However, there are ecological challenges related to wind energy generation, including collisions of wildlife with turbines. Lack of rigor, and variation in study design, together limit efforts to understand the broad-scale effects of wind power infrastructure on wildlife populations. It is not clear, however, whether these types of limitations apply to groups of birds such as raptors that are particularly vulnerable to negative effects of wind energy. We reviewed 672 peer-reviewed publications, unpublished reports, and citations from 321 wind facilities in 12 countries to evaluate methods used to monitor and mitigate for wind facility impacts on raptors. Most reports that included raptor monitoring (86 %, n = 461) only conducted post-construction monitoring for raptor fatalities, while few (12 %; n = 65) estimated pre-construction raptor use. Only 27 % of facilities (n = 62) provided estimates of fatalities or raptor use across multiple construction phases, and the percentage of facilities with data available from multiple construction periods has not changed over time. A formal experimental study design was incorporated into surveys at only 29 % of facilities. Finally, mitigation practices to reduce impacts on raptors were only reported at 23 % of facilities. Our results suggest that rigorous data collection on wind energy impacts to raptors is rare, and that mitigation of detrimental effects is seldom reported. Expanding the use of rigorous research approaches and increasing data availability would improve understanding of the regional and global effects of wind energy on raptor populations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109707","usgsCitation":"Conkling, T., McClure, C.J., Cuadros, S., Loss, S.R., and Katzner, T., 2022, Limited rigor in studies of raptor mortality and mitigation at wind power facilities: Biological Conservation, v. 275, 109707, 9 p., https://doi.org/10.1016/j.biocon.2022.109707.","productDescription":"109707, 9 p.","ipdsId":"IP-137776","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":446000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109707","text":"Publisher Index Page"},{"id":408856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Chile, Mexico, Peru, Spain, United States, 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W.","contributorId":296025,"corporation":false,"usgs":false,"family":"McClure","given":"Christopher","email":"","middleInitial":"J. W.","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":856062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cuadros, Sandra","contributorId":298625,"corporation":false,"usgs":false,"family":"Cuadros","given":"Sandra","email":"","affiliations":[{"id":36583,"text":"The Peregrine Fund","active":true,"usgs":false}],"preferred":false,"id":856063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loss, S. R. 0000-0002-8753-2995","orcid":"https://orcid.org/0000-0002-8753-2995","contributorId":257044,"corporation":false,"usgs":false,"family":"Loss","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":51965,"text":"Department of Natural Resource Ecology & Management, Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":856064,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856065,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237867,"text":"70237867 - 2022 - Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions","interactions":[],"lastModifiedDate":"2022-10-28T14:11:06.662086","indexId":"70237867","displayToPublicDate":"2022-10-28T09:05:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions","docAbstract":"

Many coastal ecosystems suffer from eutrophication, algal blooms, and dead zones due to excessive anthropogenic inputs of nitrogen (N) and phosphorus (P). This has led to regional restoration efforts that focus on managing watershed loads of N and P. In Chesapeake Bay, the largest estuary in the United States, dual nutrient reductions of N and P have been pursued since the 1980s. However, it remains unclear whether nutrient limitation – an indicator of restriction of algal growth by supplies of N and P – has changed in the tributaries of Chesapeake Bay following decades of reduction efforts. Toward that end, we analyzed historical data from nutrient-addition bioassay experiments and data from the Chesapeake Bay long-term water-quality monitoring program for six stations in three tidal tributaries (i.e., Patuxent, Potomac, and Choptank Rivers). Classification and regression tree (CART) models were developed using concurrent collections of water-quality parameters for each bioassay monitoring location during 1990-2003, which satisfactorily predicted the bioassay-based measures of nutrient limitation (classification accuracy = 96%). Predictions from the CART models using water-quality monitoring data showed enhanced nutrient limitation over the period of 1985-2020 at four of the six stations, including the downstream station in each of these three tributaries. These results indicate detectable, long-term water-quality improvements in the tidal tributaries. Overall, this research provides a new analytical tool for detecting signs of ecosystem recovery following nutrient reductions. More broadly, the approach can be adapted to other waterbodies with long-term bioassays and water-quality data sets to detect ecosystem recovery.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2022.119099","usgsCitation":"Zhang, Q., Fisher, T., Buchanan, C., Gustafson, A., Karrh, R., Murphy, R.R., Testa, J.M., Tian, R., and Tango, P.J., 2022, Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions: Water Research, v. 226, 119099, 13 p., https://doi.org/10.1016/j.watres.2022.119099.","productDescription":"119099, 13 p.","ipdsId":"IP-141495","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2022.119099","text":"Publisher Index Page"},{"id":408854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Pennsylvania, Virginia, West 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M.","contributorId":244524,"corporation":false,"usgs":false,"family":"Testa","given":"Jeremy","email":"","middleInitial":"M.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":856008,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tian, Richard 0000-0002-9416-8669","orcid":"https://orcid.org/0000-0002-9416-8669","contributorId":261309,"corporation":false,"usgs":false,"family":"Tian","given":"Richard","email":"","affiliations":[{"id":52807,"text":"U.S. Environmental Protection Agency Chesapeake Bay Program","active":true,"usgs":false}],"preferred":false,"id":856009,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tango, Peter J. 0000-0001-6669-6969","orcid":"https://orcid.org/0000-0001-6669-6969","contributorId":292845,"corporation":false,"usgs":true,"family":"Tango","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856010,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238040,"text":"70238040 - 2022 - Landsat 9 cross calibration under-fly of Landsat 8: Planning, and execution","interactions":[],"lastModifiedDate":"2022-11-04T12:18:22.038051","indexId":"70238040","displayToPublicDate":"2022-10-28T07:16:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Landsat 9 cross calibration under-fly of Landsat 8: Planning, and execution","docAbstract":"
During the early post-launch phase of the Landsat 9 mission, the Landsat 8 and 9 mission teams conducted a successful under-fly of Landsat 8 by Landsat 9, allowing for the near-simultaneous data collection of common Earth targets by the on-board sensors for cross-calibration. This effort, coordinated by the Landsat Calibration and Validation team, required contributions from various entities across National Aeronautics and Space Administration and U.S. Geological Survey such as Flight Dynamics, Systems, Mission Planning, and Flight Operations teams, beginning about 18 months prior to launch. Plans existed to allow this under-fly for any possible launch date of Landsat 9. This included 16 ascent plans and 16 data acquisition plans, one for every day of the Landsat orbital repeat period, with a minimum of 5 days of useful coverage overlap between the sensors. After the Landsat 9 launch, the plan executed, and led to the acquisition of over 2000 partial to full overlapping scene pairs. Although containing less than the expected number of scenes, this dataset was larger than previous Landsat mission under-fly efforts and more than sufficient for performing cross-calibration of the Landsat 8 and Landsat 9 sensors. The details of the planning process and execution of this under-fly are presented. 
","language":"English","publisher":"MDPI","doi":"10.3390/rs14215414","usgsCitation":"Kaita, E., Markham, B., Haque, M., Dichmann, D., Gerace, A., Leigh, L., Good, S., Schmidt, M., and Crawford, C., 2022, Landsat 9 cross calibration under-fly of Landsat 8: Planning, and execution: Remote Sensing, v. 14, no. 21, 5414, 15 p., https://doi.org/10.3390/rs14215414.","productDescription":"5414, 15 p.","ipdsId":"IP-144331","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":446006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14215414","text":"Publisher Index Page"},{"id":409159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"21","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Kaita, Edward","contributorId":298903,"corporation":false,"usgs":false,"family":"Kaita","given":"Edward","email":"","affiliations":[{"id":64728,"text":"Science Systems Applications Inc@NASA GSFC, Code 618, Greenbelt MD, 20771","active":true,"usgs":false}],"preferred":false,"id":856674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markham, Brian 0000-0002-9612-8169","orcid":"https://orcid.org/0000-0002-9612-8169","contributorId":139286,"corporation":false,"usgs":false,"family":"Markham","given":"Brian","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":856675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haque, Md Obaidul","contributorId":298904,"corporation":false,"usgs":false,"family":"Haque","given":"Md Obaidul","affiliations":[{"id":64729,"text":"KBR, Contractor to the U.S. Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD, 57198","active":true,"usgs":false}],"preferred":false,"id":856676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dichmann, Donald","contributorId":298905,"corporation":false,"usgs":false,"family":"Dichmann","given":"Donald","email":"","affiliations":[{"id":64730,"text":"NASA GSFC, Code 595, Greenbelt MD, 20771","active":true,"usgs":false}],"preferred":false,"id":856677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gerace, Aaron","contributorId":199173,"corporation":false,"usgs":false,"family":"Gerace","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":856678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leigh, Lawrence","contributorId":298906,"corporation":false,"usgs":false,"family":"Leigh","given":"Lawrence","email":"","affiliations":[{"id":64731,"text":"Office of Engineering Research, College of Engineering, South Dakota State University Brookings, SD 57007","active":true,"usgs":false}],"preferred":false,"id":856679,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Good, Susan","contributorId":298907,"corporation":false,"usgs":false,"family":"Good","given":"Susan","email":"","affiliations":[{"id":64732,"text":"A.I.Solutions@NASA GSFC, Code 595 Greenbelt, MD 20771","active":true,"usgs":false}],"preferred":false,"id":856680,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schmidt, Michael","contributorId":298908,"corporation":false,"usgs":false,"family":"Schmidt","given":"Michael","affiliations":[{"id":64734,"text":"A.I.Solutions@NASA GSFC, Code 595 Greenbelt, MD 20771.","active":true,"usgs":false}],"preferred":false,"id":856681,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":856682,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70242691,"text":"70242691 - 2022 - Underwater hearing in sea ducks with applications for reducing gillnet bycatch through acoustic deterrence","interactions":[],"lastModifiedDate":"2023-04-13T12:03:47.785757","indexId":"70242691","displayToPublicDate":"2022-10-28T07:00:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2275,"text":"Journal of Experimental Biology","active":true,"publicationSubtype":{"id":10}},"title":"Underwater hearing in sea ducks with applications for reducing gillnet bycatch through acoustic deterrence","docAbstract":"

As diving foragers, sea ducks are vulnerable to underwater anthropogenic activity, including ships, underwater construction, seismic surveys and gillnet fisheries. Bycatch in gillnets is a contributing source of mortality for sea ducks, killing hundreds of thousands of individuals annually. We researched underwater hearing in sea duck species to increase knowledge of underwater avian acoustic sensitivity and to assist with possible development of gillnet bycatch mitigation strategies that include auditory deterrent devices. We used both psychoacoustic and electrophysiological techniques to investigate underwater duck hearing in several species including the long-tailed duck (Clangula hyemalis), surf scoter (Melanitta perspicillata) and common eider (Somateria mollissima). Psychoacoustic results demonstrated that all species tested share a common range of maximum auditory sensitivity of 1.0–3.0 kHz, with the long-tailed ducks and common eiders at the high end of that range (2.96 kHz), and surf scoters at the low end (1.0 kHz). In addition, our electrophysiological results from 4 surf scoters and 2 long-tailed ducks, while only tested at 0.5, 1 and 2 kHz, generally agree with the audiogram shape from our psychoacoustic testing. The results from this study are applicable to the development of effective acoustic deterrent devices or pingers in the 2–3 kHz range to deter sea ducks from anthropogenic threats.

","language":"English","publisher":"The Company of Biologists","doi":"10.1242/jeb.243953","usgsCitation":"McGrew, K.A., Crowell, S.E., Fiely, J., Berlin, A., Olsen, G.H., James, J., Hopkins, H., and Williams , C., 2022, Underwater hearing in sea ducks with applications for reducing gillnet bycatch through acoustic deterrence: Journal of Experimental Biology, v. 225, no. 20, jeb243953, https://doi.org/10.1242/jeb.243953.","productDescription":"jeb243953","ipdsId":"IP-145975","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446008,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/jeb.243953","text":"Publisher Index Page"},{"id":415704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"225","issue":"20","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"McGrew, Kathleen A.","contributorId":265779,"corporation":false,"usgs":false,"family":"McGrew","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":869380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowell, Sara E.","contributorId":146550,"corporation":false,"usgs":false,"family":"Crowell","given":"Sara","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":869381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fiely, Jonathan","contributorId":200905,"corporation":false,"usgs":false,"family":"Fiely","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":869382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berlin, Alicia 0000-0002-5275-3077","orcid":"https://orcid.org/0000-0002-5275-3077","contributorId":216023,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869383,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869384,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, Jennifer","contributorId":304133,"corporation":false,"usgs":false,"family":"James","given":"Jennifer","email":"","affiliations":[{"id":65980,"text":"Naval Undersea Warfare Center","active":true,"usgs":false}],"preferred":false,"id":869385,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hopkins, Heather","contributorId":304134,"corporation":false,"usgs":false,"family":"Hopkins","given":"Heather","email":"","affiliations":[{"id":65980,"text":"Naval Undersea Warfare Center","active":true,"usgs":false}],"preferred":false,"id":869386,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams , Christopher J. ","contributorId":223677,"corporation":false,"usgs":false,"family":"Williams ","given":"Christopher J. ","affiliations":[],"preferred":false,"id":869387,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238167,"text":"70238167 - 2022 - Spatial models of jaguar energy expenditure in response to border wall construction and remediation","interactions":[],"lastModifiedDate":"2022-11-15T12:50:52.470023","indexId":"70238167","displayToPublicDate":"2022-10-28T06:47:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Spatial models of jaguar energy expenditure in response to border wall construction and remediation","docAbstract":"

The construction of a wall at the United States-Mexico border is known to impede and deter movement of terrestrial wildlife between the two countries. One such species is the jaguar, in its northernmost range in the borderlands of Arizona and Sonora. We developed an anisotropic cost distance model for jaguar in a binational crossing area of the Madrean Sky Islands at the United States-Mexico border in Southern Arizona as a case study by using previously collected GPS tracking data for jaguars, bioenergetic calculations for pumas, and a digital elevation model. This model describes projected energy expenditure for jaguar to reach key water sources north of the international border. These desert springs and the broader study region provide vital habitat for jaguar conservation and reintroduction efforts in the United States. An emerging impediment to jaguar conservation and reintroduction is border infrastructure including border wall. By comparing walled and un-walled border sections, and three remediation scenarios, we demonstrate that existing border infrastructure significantly increases energy expenditure by jaguars and that some partial remediation scenarios are more beneficial than others. Our results demonstrate opportunities for remediation. Improved understanding of how border infrastructure impacts physiological requirements and resulting impacts to jaguar and other terrestrial wildlife in the United States-Mexico borderlands may inform conservation management.

","language":"English","publisher":"Frontiers","doi":"10.3389/fcosc.2022.1012010","usgsCitation":"Chambers, S.N., Villarreal, M.L., Norman, L., Bravo, J.C., and Traphagen, M.B., 2022, Spatial models of jaguar energy expenditure in response to border wall construction and remediation: Frontiers in Conservation Science, v. 3, 1012010, 9 p., https://doi.org/10.3389/fcosc.2022.1012010.","productDescription":"1012010, 9 p.","ipdsId":"IP-143998","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":446012,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.1012010","text":"Publisher Index Page"},{"id":435642,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DSSV2Q","text":"USGS data release","linkHelpText":"Maps of cumulative energy expenditure models for jaguar in southern Arizona"},{"id":409349,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Tumacacori Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.7240776436901,\n 32.20918805856094\n ],\n [\n -111.7240776436901,\n 31.199752402944327\n ],\n [\n -110.41670459681502,\n 31.199752402944327\n ],\n [\n -110.41670459681502,\n 32.20918805856094\n ],\n [\n -111.7240776436901,\n 32.20918805856094\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambers, Samuel Norton 0000-0002-9840-7989","orcid":"https://orcid.org/0000-0002-9840-7989","contributorId":297110,"corporation":false,"usgs":true,"family":"Chambers","given":"Samuel","email":"","middleInitial":"Norton","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bravo, Juan Carlos","contributorId":299075,"corporation":false,"usgs":false,"family":"Bravo","given":"Juan","email":"","middleInitial":"Carlos","affiliations":[{"id":64759,"text":"Wildlands Network","active":true,"usgs":false}],"preferred":false,"id":857034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Traphagen, Myles B.","contributorId":299076,"corporation":false,"usgs":false,"family":"Traphagen","given":"Myles","email":"","middleInitial":"B.","affiliations":[{"id":64759,"text":"Wildlands Network","active":true,"usgs":false}],"preferred":false,"id":857035,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237271,"text":"gip216 - 2022 - Water-quality monitoring of the Merrimack River watershed in Massachusetts","interactions":[],"lastModifiedDate":"2026-03-25T16:46:48.547391","indexId":"gip216","displayToPublicDate":"2022-10-27T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"216","displayTitle":"Water-Quality Monitoring of the Merrimack River Watershed in Massachusetts","title":"Water-quality monitoring of the Merrimack River watershed in Massachusetts","docAbstract":"

The U.S. Geological Survey has been working in collaboration with the Massachusetts Department of Environmental Protection on a project to collect water-quality data from the Merrimack River watershed since April 2020. Twelve locations in the Merrimack River watershed are being sampled for nutrients (such as nitrogen), metals (such as aluminum), Escherichia coli bacteria, and other measures.

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Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532

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A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 60th annual report of the River Master of the Delaware River. It covers the 2013 River Master report year, the period from December 1, 2012 to November 30, 2013.

During the report year, precipitation in the upper Delaware River Basin was 44.50 inches or 100 percent of the long-term average. Combined storage in the Pepacton, Cannonsville, and Neversink Reservoirs remained high until October 2013 when it decreased below 80 percent combined capacity. The lowest combined storage of the report year was 70.2 percent of combined capacity on November 26, 2013. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.

Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the Montague flow objective for the Delaware River at the Montague, New Jersey streamgage on 71 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year. An agreement was signed on July 16, 2013 to temporarily increase releases to provide thermal protection below Cannonsville Reservoir.

The quality of water in the Delaware River estuary between streamgages at Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at several locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.

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Delaware River Master
Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337

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","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-10-27","noUsgsAuthors":false,"publicationDate":"2022-10-27","publicationStatus":"PW","contributors":{"authors":[{"text":"DiFrenna, Vincent J. 0000-0002-1336-7288","orcid":"https://orcid.org/0000-0002-1336-7288","contributorId":298307,"corporation":false,"usgs":true,"family":"DiFrenna","given":"Vincent","email":"","middleInitial":"J.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":855354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, William J. 0000-0003-4780-8835","orcid":"https://orcid.org/0000-0003-4780-8835","contributorId":216006,"corporation":false,"usgs":true,"family":"Andrews","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Kendra L. 0000-0002-3046-7440","orcid":"https://orcid.org/0000-0002-3046-7440","contributorId":218135,"corporation":false,"usgs":true,"family":"Russell","given":"Kendra","email":"","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":855356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norris, J. Michael 0000-0002-7480-0161","orcid":"https://orcid.org/0000-0002-7480-0161","contributorId":222849,"corporation":false,"usgs":true,"family":"Norris","given":"J. Michael","affiliations":[{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true}],"preferred":true,"id":855357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mason, Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":2090,"corporation":false,"usgs":true,"family":"Mason","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":855358,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237854,"text":"70237854 - 2022 - Review of harmful algal blooms effects on birds with implications for avian wildlife in the Chesapeake Bay region","interactions":[],"lastModifiedDate":"2023-06-23T13:17:32.903846","indexId":"70237854","displayToPublicDate":"2022-10-27T10:29:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Review of harmful algal blooms effects on birds with implications for avian wildlife in the Chesapeake Bay region","docAbstract":"

The Chesapeake Bay, along the mid-Atlantic coast of North America, is the largest estuary in the United States and provides critical habitat for wildlife. In contrast to point and non-point source release of pesticides, metals, and industrial, personal care and household use chemicals on biota in this watershed, there has only been scant attention to potential exposure and effects of algal toxins on wildlife in the Chesapeake Bay region. As background, we first review the scientific literature on algal toxins and harmful algal bloom (HAB) events in various regions of the world that principally affected birds, and to a lesser degree other wildlife. To examine the situation for the Chesapeake, we compiled information from government reports and databases summarizing wildlife mortality events for 2000 through 2020 that were associated with potentially toxic algae and HAB events. Summary findings indicate that there have been few wildlife mortality incidents definitively linked to HABs, other mortality events that were suspected to be related to HABs, and more instances in which HABs may have indirectly contributed to or occurred coincident with wildlife mortality. The dominant toxins found in the Chesapeake Bay drainage that could potentially affect wildlife are microcystins, with concentrations in water approaching or exceeding human-based thresholds for ceasing recreational use and drinking water at a number of locations. As an increasing trend in HAB events in the U.S. and in the Chesapeake Bay have been reported, additional information on HAB toxin exposure routes, comparative sensitivity among species, consequences of sublethal exposure, and better diagnostic and risk criteria would greatly assist in predicting algal toxin hazard and risks to wildlife.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2022.102319","usgsCitation":"Rattner, B., Wazniak, C.E., Lankton, J.S., McGowan, P.C., Drovetski, S.V., and Egerton, T.A., 2022, Review of harmful algal blooms effects on birds with implications for avian wildlife in the Chesapeake Bay region: Harmful Algae, v. 120, 102319, 20 p.; Data Release, https://doi.org/10.1016/j.hal.2022.102319.","productDescription":"102319, 20 p.; Data Release","ipdsId":"IP-138638","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446019,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2022.102319","text":"Publisher Index Page"},{"id":408805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418367,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ULAM7G","text":"Wildlife mortality events in counties surrounding the Chesapeake Bay recorded in the Wildlife Health Information Sharing Partnership Event Reporting System (WHISPers) from 2000-2020"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.18954322170708,\n 37.53524166994633\n ],\n [\n -77.44783397911205,\n 37.364931581898986\n ],\n [\n -76.73341273522277,\n 36.72453067388703\n ],\n [\n -76.21133567238093,\n 36.76416355102856\n ],\n [\n -75.98601820315514,\n 37.06311061060744\n ],\n [\n -75.93655827088573,\n 37.308289271077044\n ],\n [\n -75.41997675607354,\n 37.95675381093146\n ],\n [\n -75.69475415756958,\n 38.48348716740804\n ],\n [\n -75.77718737801817,\n 39.59326365864615\n ],\n [\n -76.0464692314839,\n 39.66521791944069\n ],\n [\n -77.45332952714315,\n 38.82253108298832\n ],\n [\n -77.40386959487374,\n 38.276702908455235\n ],\n [\n -77.18954322170708,\n 37.53524166994633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":298580,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett A.","email":"brattner@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":855925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wazniak, Catherine E.","contributorId":298582,"corporation":false,"usgs":false,"family":"Wazniak","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":855989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":855990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":855991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":855992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Egerton, Todd A.","contributorId":298583,"corporation":false,"usgs":false,"family":"Egerton","given":"Todd","email":"","middleInitial":"A.","affiliations":[{"id":64620,"text":"Virginia Department of Health","active":true,"usgs":false}],"preferred":false,"id":855993,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238751,"text":"70238751 - 2022 - Using active source seismology to image the Palos Verdes Fault damage zone as a function of distance, depth, and geology","interactions":[],"lastModifiedDate":"2022-12-07T12:43:06.769149","indexId":"70238751","displayToPublicDate":"2022-10-26T06:40:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Using active source seismology to image the Palos Verdes Fault damage zone as a function of distance, depth, and geology","docAbstract":"

Fault damage zones provide a window into the non-elastic processes of an earthquake. Geological and seismic tomography methods have been unable to measure damage zones at depth with sufficient spatial sampling to evaluate the relative influence of depth, distance, and lithological variations. Here, we identify and analyze the damage zone of the Palos Verdes Fault offshore southern California using two 3D seismic reflection datasets. We apply a novel algorithm to identify discontinuities attributed to faults and fractures in large seismic volumes and examine the spatial distribution of fault damage in sedimentary rock surrounding the Palos Verdes Fault. Our results show that damage through fracturing is most concentrated around mapped faults and decays exponentially to a distance of ∼2 km, where fracturing reaches a clearly defined and relatively undamaged background for all examined depths and lithologies (450 m to 2.2 km). This decrease in fracturing with distance from the central fault strand exhibits similar functional form to outcrop studies. However, here we extend analysis to distances seldom accessible (∼10 km lateral distance). Separating the data by geologic units we find that the damage decay and background level differs for each unit, with the older and deeper units having higher levels of background fracturing and shallower exponential decays of fracturing with distance from the fault. Surprisingly, these differences in damage decay and background level trade-off result in a consistent damage zone width regardless of lithology or depth. We find that the damage zone has similar decay trends on both sides of the fault. When examining the damage zone at shorter (4 km vs 17 km) along strike distances, the damage zone has a more complex decay trend and at least two strands are resolvable.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2022.117871","usgsCitation":"Alongi, T., Brodsky, E., Kluesner, J., and Brothers, D., 2022, Using active source seismology to image the Palos Verdes Fault damage zone as a function of distance, depth, and geology: Earth and Planetary Science Letters, v. 600, 117871, 14 p., https://doi.org/10.1016/j.epsl.2022.117871.","productDescription":"117871, 14 p.","ipdsId":"IP-142040","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2022.117871","text":"Publisher Index Page"},{"id":410151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.38209178303092,\n 34.82996235145717\n ],\n [\n -120.38209178303092,\n 31.97009660355488\n ],\n [\n -114.14450638757215,\n 31.97009660355488\n ],\n [\n -114.14450638757215,\n 34.82996235145717\n ],\n [\n -120.38209178303092,\n 34.82996235145717\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"600","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Alongi, Travis","contributorId":299734,"corporation":false,"usgs":false,"family":"Alongi","given":"Travis","email":"","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":858474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodsky, Emily","contributorId":299735,"corporation":false,"usgs":false,"family":"Brodsky","given":"Emily","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":858475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262041,"text":"70262041 - 2022 - Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus)","interactions":[],"lastModifiedDate":"2025-01-10T15:07:46.307314","indexId":"70262041","displayToPublicDate":"2022-10-26T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus)","docAbstract":"

Background

Dispersal is a fundamental process to animal population dynamics and gene flow. In white-tailed deer (WTD; Odocoileus virginianus), dispersal also presents an increasingly relevant risk for the spread of infectious diseases. Across their wide range, WTD dispersal is believed to be driven by a suite of landscape and host behavioral factors, but these can vary by region, season, and sex. Our objectives were to (1) identify dispersal events in Wisconsin WTD and determine drivers of dispersal rates and distances, and (2) determine how landscape features (e.g., rivers, roads) structure deer dispersal paths.

Methods

We developed an algorithmic approach to detect dispersal events from GPS collar data for 590 juvenile, yearling, and adult WTD. We used statistical models to identify host and landscape drivers of dispersal rates and distances, including the role of agricultural land use, the traversability of the landscape, and potential interactions between deer. We then performed a step selection analysis to determine how landscape features such as agricultural land use, elevation, rivers, and roads affected deer dispersal paths.

Results

Dispersal predominantly occurred in juvenile males, of which 64.2% dispersed, with dispersal events uncommon in other sex and age classes. Juvenile male dispersal probability was positively associated with the proportion of the natal range that was classified as agricultural land use, but only during the spring. Dispersal distances were typically short (median 5.77 km, range: 1.3–68.3 km), especially in the fall. Further, dispersal distances were positively associated with agricultural land use in potential dispersal paths but negatively associated with the number of proximate deer in the natal range. Lastly, we found that, during dispersal, juvenile males typically avoided agricultural land use but selected for areas near rivers and streams.

Conclusion

Land use—particularly agricultural—was a key driver of dispersal rates, distances, and paths in Wisconsin WTD. In addition, our results support the importance of deer social environments in shaping dispersal behavior. Our findings reinforce knowledge of dispersal ecology in WTD and how landscape factors—including major rivers, roads, and land-use patterns—structure host gene flow and potential pathogen transmission.

","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-022-00342-5","usgsCitation":"Gilbertson, M., Ketz, A., Hunsaker, M., Jarosinski, D., Ellarson, W., Walsh, D.P., Storm, D., and Turner, W.C., 2022, Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus): Movement Ecology, v. 10, 43, 18 p., https://doi.org/10.1186/s40462-022-00342-5.","productDescription":"43, 18 p.","ipdsId":"IP-139079","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467154,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-022-00342-5","text":"Publisher Index Page"},{"id":465983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"southwestern Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.9914420863848,\n 43.07956941638602\n ],\n [\n -90.9914420863848,\n 42.580032684433775\n ],\n [\n -89.45335614888498,\n 42.580032684433775\n ],\n [\n -89.45335614888498,\n 43.07956941638602\n ],\n [\n -90.9914420863848,\n 43.07956941638602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gilbertson, Marie L. J.","contributorId":347968,"corporation":false,"usgs":false,"family":"Gilbertson","given":"Marie L. J.","affiliations":[{"id":83274,"text":"University of Wisconsin–Madison","active":true,"usgs":false}],"preferred":false,"id":922783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ketz, Alison","contributorId":347969,"corporation":false,"usgs":false,"family":"Ketz","given":"Alison","affiliations":[{"id":83274,"text":"University of Wisconsin–Madison","active":true,"usgs":false}],"preferred":false,"id":922784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunsaker, Matthew","contributorId":347970,"corporation":false,"usgs":false,"family":"Hunsaker","given":"Matthew","affiliations":[{"id":83274,"text":"University of Wisconsin–Madison","active":true,"usgs":false}],"preferred":false,"id":922785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarosinski, Dana","contributorId":347971,"corporation":false,"usgs":false,"family":"Jarosinski","given":"Dana","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":922786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ellarson, Wesley","contributorId":347972,"corporation":false,"usgs":false,"family":"Ellarson","given":"Wesley","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":922787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922788,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Storm, Daniel J.","contributorId":347976,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":922789,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922790,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}