{"pageNumber":"28","pageRowStart":"675","pageSize":"25","recordCount":4111,"records":[{"id":70219056,"text":"ofr20211017 - 2021 - Distribution, abundance, and genomic diversity of the endangered antioch dunes evening primrose (Oenothera deltoides subsp. howellii) surveyed in 2019","interactions":[],"lastModifiedDate":"2021-04-08T21:27:20.542124","indexId":"ofr20211017","displayToPublicDate":"2021-03-22T12:28:10","publicationYear":"2021","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":"2021-1017","displayTitle":"Distribution, Abundance, and Genomic Diversity of the Endangered Antioch Dunes Evening Primrose (Oenothera deltoides subsp. howellii) Surveyed in 2019","title":"Distribution, abundance, and genomic diversity of the endangered antioch dunes evening primrose (Oenothera deltoides subsp. howellii) surveyed in 2019","docAbstract":"

Sand dune ecosystems are highly dynamic landforms found along coastlines and riverine deltas where a supply of sand-sized material is available to be delivered by aquatic and wind environments. These unique ecosystems provide habitat for a variety of endemic and rare plant and animal species. Sand dunes have been affected by human development, sand mining, and shoreline stabilization from invasive weeds. This report provides a summary of a comprehensive literature review, field survey, and genomic analysis for the Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii, hereafter howellii), an endemic species to the San Francisco Bay-Delta, California, which was listed as a federally endangered subspecies in 1978. Howellii is found on a historic dune sheet (the Antioch sand sheet) near the confluence of the Sacramento and San Joaquin Rivers. The Antioch sand sheet has been greatly altered by sand mining and land conversion into agriculture and urban development. In chapter A, we describe results of the literature review and field survey. We found howellii at eight locations with over 90 percent of the adult population and nearly 99 percent of juveniles observed on the Antioch Dunes National Wildlife Refuge. We measured a negative relationship between howellii numbers and invasive weed cover, illustrating the importance of mobilized open sand for this species. In chapter B, we describe the genomic study results. We surveyed genomic diversity by using double-digest restriction-site associated sequencing to estimate population genetic structure and levels of diversity across all surveyed occurrences. The genomic analyses included outgroup samples of the closely related Oenothera deltoides subsp. cognata and three occurrences of an unknown taxon with intermediate morphology to cognata and howellii, which also occurs on the Antioch sand sheet, east of the Antioch Dunes National Wildlife Refuge. These three morphologically distinctive groups formed genetically distinctive clusters and well-supported monophyletic clades in clustering and phylogenetic analyses, respectively. There was no indication of recent hybridization among any of the groups. Among howellii occurrences, the Antioch Dunes National Wildlife Refuge contained the greatest genetic diversity. Our approach, which combined field surveys, habitat assessments, and genetic analyses, can provide useful information for the conservation and management of rare and at-risk plant species and highlights the uniqueness of the Antioch sand sheet floral diversity through the discovery of a putative new taxon within the bird-cage evening primrose species complex.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211017","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Friends of San Pablo Bay National Wildlife Refuge","usgsCitation":"Thorne, K.M., and Vandergast, A.G., 2021, Distribution, abundance, and genomic diversity of the endangered Antioch Dunes evening-primrose (Oenothera deltoides subsp. howellii) surveyed in 2019: U.S. Geological Survey Open-File Report 2021–1017, 40 p., https://doi.org/10.3133/ofr20211017.","productDescription":"vi, 40 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-124754","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436447,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93VYTF5","text":"USGS data release","linkHelpText":"Oenothera deltoides Genotype Data from Contra Costa County, California in 2019"},{"id":384604,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017_chB_app2.csv","text":"Chapter B Appendix 2","size":"4 KB","linkFileType":{"id":7,"text":"csv"}},{"id":384550,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017.xml"},{"id":384549,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1017/images"},{"id":384548,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384547,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1017/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.89605712890624,\n 37.97018468810549\n ],\n [\n -121.6241455078125,\n 37.97018468810549\n ],\n [\n -121.6241455078125,\n 38.11727165830543\n ],\n [\n -121.89605712890624,\n 38.11727165830543\n ],\n [\n -121.89605712890624,\n 37.97018468810549\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-03-22","noUsgsAuthors":false,"publicationDate":"2021-03-22","publicationStatus":"PW","contributors":{"editors":[{"text":"Thorne, Karen M. 0000-0002-1381-0657 kthorne@usgs.gov","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":4191,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen","email":"kthorne@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":812617,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":812618,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":70223227,"text":"70223227 - 2021 - Coflowering invasive plants and a congener have neutral effects on fitness components of a rare endemic plant","interactions":[],"lastModifiedDate":"2021-08-18T12:40:16.346666","indexId":"70223227","displayToPublicDate":"2021-03-20T07:37:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Coflowering invasive plants and a congener have neutral effects on fitness components of a rare endemic plant","docAbstract":"

Network analyses rarely include fitness components, such as germination, to tie invasive plants to population-level effects on the natives. We address this limitation in a previously studied network of flower visitors around a suite of native and invasive plants that includes an endemic plant at Badlands National Park, South Dakota, USA. Eriogonum visheri coflowers with two abundant invasive plants, Salsola tragus and Melilotus officinalis, as well as a common congener, E. pauciflorum. Network analyses had suggested strong linkages between E. visheri and S. tragus and E. pauciflorum, with a weaker link to M. officinalis. We measured visitation, pollen deposited on stigmas, achene weight and germination over three field seasons (two for germination) in four populations (two in the final season) of E. visheri and applied in situ pollen treatments to E. visheri, adding pollen from other flowers on the same plant; flowers on other E. visheri plants; S. tragus, M. officinalis, or E. pauciflorum; open pollination; or excluding pollinators. Insect visitation to E. visheri was not affected by floral abundance of any of the focal species. Most visitors were halictid bees; one of these (Lasioglossum packeri) was the only identified species to visit E. visheri all three years. Ninety-seven percent of pollen on collected E. visheri stigmas was conspecific, but 22% of flowers had >1 grain of E. pauciflorum pollen on stigmas and 7% had >1 grain of S. tragus pollen; <1% of flowers had M. officinalis pollen on stigmas. None of the pollen treatments produced significant differences in weight or germination of E. visheri achenes. We conclude that, in contrast to the results of the network analysis, neither of the invasive species poses a threat, via heterospecific pollen deposition, to pollination of the endemic E. visheri, and that its congener provides alternative pollen resources to its pollinators.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7375","usgsCitation":"Larson, D.L., Larson, J.L., Symstad, A., Buhl, D.A., and Portman, Z.M., 2021, Coflowering invasive plants and a congener have neutral effects on fitness components of a rare endemic plant: Ecology and Evolution, v. 11, no. 9, p. 4750-4762, https://doi.org/10.1002/ece3.7375.","productDescription":"13 p.","startPage":"4750","endPage":"4762","ipdsId":"IP-122779","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":453005,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7375","text":"External Repository"},{"id":436451,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MNIVB3","text":"USGS data release","linkHelpText":"Eriogonum visheri (Visher's buckwheat) seed, pollen, and insects at Badlands National Park, South Dakota, USA, 2014-2015, 2017"},{"id":388088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.29345703125,\n 43.229195113965005\n ],\n [\n -101.337890625,\n 43.229195113965005\n ],\n [\n -101.337890625,\n 44.18220395771566\n ],\n [\n -103.29345703125,\n 44.18220395771566\n ],\n [\n -103.29345703125,\n 43.229195113965005\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":821453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Jennifer L 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":257024,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":821454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":821455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":821456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Portman, Zachary M.","contributorId":264397,"corporation":false,"usgs":false,"family":"Portman","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":54455,"text":"Dept. of Entomology, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":821457,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219188,"text":"70219188 - 2021 - Post-fire management targeting invasive annual grasses may have inadvertently released the exotic perennial forb Chondrilla juncea and suppressed its biocontrol agent","interactions":[],"lastModifiedDate":"2021-06-01T17:30:45.351733","indexId":"70219188","displayToPublicDate":"2021-03-20T07:21:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Post-fire management targeting invasive annual grasses may have inadvertently released the exotic perennial forb Chondrilla juncea and suppressed its biocontrol agent","title":"Post-fire management targeting invasive annual grasses may have inadvertently released the exotic perennial forb Chondrilla juncea and suppressed its biocontrol agent","docAbstract":"

Top-down and bottom-up factors affecting invasive populations are rarely considered simultaneously, yet their interactive responses to disturbances and management interventions can be essential to understanding invasion patterns. We evaluated post-fire responses of the exotic perennial forb Chondrilla juncea (rush skeletonweed) and its biocontrol agents to landscape factors and a post-fire combined herbicide (imazapic) and bacteria (Pseudomonas fluorescens strain MB906) treatment that targeted invasive annual grasses in a sagebrush steppe ecosystem. Biocontrol agents released against C. juncea in previous decades included Cystiphora schmidti (gall midge), Aceria chondrillae (gall mite), and Puccinia chondrillina (rust fungus). C. juncea abundance was greater in sprayed than unsprayed plots, and where soils were coarser, slopes faced southwest, solar heat loads and topographic water accumulation were greater, and cover of deep-rooted native perennials was lower. Mite infestation was greater in unsprayed plots, midge infestation was greater at higher elevations on steeper slopes, and midges were more abundant while rust was less abundant on gravelly soils. Biocontrol infestation levels varied considerably between years and could not be predicted in 2019 from 2018 infestation levels. Multiple biocontrol species were often present at the same plots but were rarely present on the same C. juncea individuals. These results suggest that spatial patterns of invasion by C. juncea are related to deep-soil water availability, warmer conditions, and alleviation of competition. Treatments designed to reduce invasive annual grasses may inadvertently release C. juncea by both reducing plant competition for soil resources and affecting biocontrol agent (mite) abundance.

","language":"English","publisher":"Springer","doi":"10.1007/s10530-021-02481-z","usgsCitation":"Lazarus, B., and Germino, M., 2021, Post-fire management targeting invasive annual grasses may have inadvertently released the exotic perennial forb Chondrilla juncea and suppressed its biocontrol agent: Biological Invasions, v. 23, p. 1915-1932, https://doi.org/10.1007/s10530-021-02481-z.","productDescription":"18 p.","startPage":"1915","endPage":"1932","onlineOnly":"N","ipdsId":"IP-120244","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":436452,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QFBHZ3","text":"USGS data release","linkHelpText":"Post-fire Chondrilla juncea and biocontrol at Boise River Wildlife Management Area 2018-2019"},{"id":384752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.54296874999999,\n 43.51668853502906\n ],\n [\n -115.48828125000001,\n 43.51668853502906\n ],\n [\n -115.48828125000001,\n 43.96119063892024\n ],\n [\n -116.54296874999999,\n 43.96119063892024\n ],\n [\n -116.54296874999999,\n 43.51668853502906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813150,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219120,"text":"70219120 - 2021 - Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","interactions":[],"lastModifiedDate":"2021-05-28T14:11:19.896547","indexId":"70219120","displayToPublicDate":"2021-03-19T06:49:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7788,"text":"Environmental International","active":true,"publicationSubtype":{"id":10}},"title":"Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","docAbstract":"

Background

Humans are primary drivers of environmental contamination worldwide, including in drinking-water resources. In the United States (US), federal and state agencies regulate and monitor public-supply drinking water while private-supply monitoring is rare; the current lack of directly comparable information on contaminant-mixture exposures and risks between private- and public-supplies undermines tapwater (TW) consumer decision-making.

Methods

We compared private- and public-supply residential point-of-use TW at Cape Cod, Massachusetts, where both supplies share the same groundwater source. TW from 10 private- and 10 public-supply homes was analyzed for 487 organic, 38 inorganic, 8 microbial indicators, and 3 in vitro bioactivities. Concentrations were compared to existing protective health-based benchmarks, and aggregated Hazard Indices (HI) of regulated and unregulated TW contaminants were calculated along with ratios of in vitro exposure-activity cutoffs.

Results

Seventy organic and 28 inorganic constituents were detected in TW. Median detections were comparable, but median cumulative concentrations were substantially higher in public supply due to 6 chlorine–disinfected samples characterized by disinfection byproducts and corresponding lower heterotrophic plate counts. Public-supply applicable maximum contaminant (nitrate) and treatment action (lead and copper) levels were exceeded in private-supply TW samples only. Exceedances of health-based HI screening levels of concern were common to both TW supplies.

Discussion

These Cape Cod results indicate comparable cumulative human-health concerns from contaminant exposures in private- and public-supply TW in a shared source-water setting. Importantly, although this study’s analytical coverage exceeds that currently feasible for water purveyors or homeowners, it nevertheless is a substantial underestimation of the full breadth of contaminant mixtures documented in the environment and potentially present in drinking water.

Conclusion

Regardless of the supply, increased public engagement in source-water protection and drinking-water treatment, including consumer point-of-use treatment, is warranted to reduce risks associated with long-term TW contaminant exposures, especially in vulnerable populations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2021.106487","usgsCitation":"Bradley, P., LeBlanc, D.R., Romanok, K., Smalling, K., Focazio, M.J., Cardon, M.C., Clark, J., Conley, J.M., Evans, N., Givens, C.E., Gray, J.L., Gray, L.E., Hartig, P.C., Higgins, C.P., Hladik, M.L., Iwanowicz, L., Loftin, K.A., McCleskey, R., McDonough, C.A., Medlock-Kakaley, E., Weis, C.P., and Wilson, V.S., 2021, Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA: Environmental International, v. 152, 106487, 14 p., https://doi.org/10.1016/j.envint.2021.106487.","productDescription":"106487, 14 p.","ipdsId":"IP-110487","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":453024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envint.2021.106487","text":"Publisher Index Page"},{"id":384622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.6805419921875,\n 41.50034959128928\n ],\n [\n -69.80712890625,\n 41.50034959128928\n ],\n [\n -69.80712890625,\n 42.24478535602799\n ],\n [\n -70.6805419921875,\n 42.24478535602799\n ],\n [\n -70.6805419921875,\n 41.50034959128928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"152","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Focazio, Michael J. 0000-0003-0967-5576 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Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

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mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":812548,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Silverman, Debra T.","contributorId":255547,"corporation":false,"usgs":false,"family":"Silverman","given":"Debra","email":"","middleInitial":"T.","affiliations":[{"id":29855,"text":"National Cancer Institute","active":true,"usgs":false}],"preferred":false,"id":812549,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Toccalino, Patricia 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":213727,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia","email":"","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":812550,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Argos, Maria 0000-0003-4234-252X","orcid":"https://orcid.org/0000-0003-4234-252X","contributorId":204352,"corporation":false,"usgs":false,"family":"Argos","given":"Maria","email":"","affiliations":[{"id":18125,"text":"University of Illinois, Chicago","active":true,"usgs":false}],"preferred":false,"id":812551,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gribble, Matthew O.","contributorId":255548,"corporation":false,"usgs":false,"family":"Gribble","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":812552,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812553,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70219123,"text":"70219123 - 2021 - Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health","interactions":[],"lastModifiedDate":"2021-03-24T11:41:22.219976","indexId":"70219123","displayToPublicDate":"2021-03-16T06:33:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health","docAbstract":"

Autonomous, robotic environmental (e)DNA samplers now make it possible for biological observations to match the scale and quality of abiotic measurements collected by automated sensor networks. Merging these automated data streams may allow for improved insight into biotic responses to environmental change and stressors. Here, we merged eDNA data collected by robotic samplers installed at three U.S. Geological Survey (USGS) streamgages with gridded daily weather data, and daily water quality and quantity data into a cloud-hosted database. The eDNA targets were a rare fish parasite and a more common salmonid fish. We then used computationally expedient Bayesian hierarchical occupancy models to evaluate associations between abiotic conditions and eDNA detections and to simulate how uncertainty in result interpretation changes with the frequency of autonomous robotic eDNA sample collection. We developed scripts to automate data merging, cleaning and analysis steps into a chained-step, workflow. We found that inclusion of abiotic covariates only provided improved insight for the more common salmonid fish since its DNA was more frequently detected. Rare fish parasite DNA was infrequently detected, which caused occupancy parameter estimates and covariate associations to have high uncertainty. Our simulations found that collecting samples at least once per day resulted in more detections and less parameter uncertainty than less frequent sampling. Our occupancy and simulation results together demonstrate the advantages of robotic eDNA samplers and how these samples can be combined with easy to acquire, publicly available data to foster real-time biosurveillance and forecasting.

","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2021.620715","usgsCitation":"Sepulveda, A., Hoegh, A.B., Gage, J.A., Caldwell Eldridge, S.L., Birch, J.M., Stratton, C., Hutchins, P.R., and Barnhart, E.P., 2021, Integrating environmental DNA results with diverse data sets to improve biosurveillance of river health: Frontiers in Ecology and Evolution, v. 9, 13 p., https://doi.org/10.3389/fevo.2021.620715.","productDescription":"13 p.","ipdsId":"IP-123750","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2021.620715","text":"Publisher Index Page"},{"id":384620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming, Montana","otherGeospatial":"Yellowstone River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.400390625,\n 43.89789239125797\n ],\n [\n -107.666015625,\n 43.89789239125797\n ],\n [\n -107.666015625,\n 46.49839225859763\n ],\n [\n -115.400390625,\n 46.49839225859763\n ],\n [\n -115.400390625,\n 43.89789239125797\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoegh, Andrew B.","contributorId":166684,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":812862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gage, Joshua A.","contributorId":255726,"corporation":false,"usgs":false,"family":"Gage","given":"Joshua","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":812863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell Eldridge, Sara L. 0000-0001-8838-8940 seldridge@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-8940","contributorId":4981,"corporation":false,"usgs":true,"family":"Caldwell Eldridge","given":"Sara","email":"seldridge@usgs.gov","middleInitial":"L.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":812864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birch, James M.","contributorId":255728,"corporation":false,"usgs":false,"family":"Birch","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":812865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stratton, Christian","contributorId":217711,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":812866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hutchins, Patrick R. 0000-0001-5232-0821 phutchins@usgs.gov","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":198337,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick","email":"phutchins@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812867,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812868,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70219168,"text":"70219168 - 2021 - Submarine lava deltas of the 2018 eruption of Kilauea volcano","interactions":[],"lastModifiedDate":"2021-04-08T15:27:07.976909","indexId":"70219168","displayToPublicDate":"2021-03-11T07:54:07","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Submarine lava deltas of the 2018 eruption of Kīlauea volcano","title":"Submarine lava deltas of the 2018 eruption of Kilauea volcano","docAbstract":"

Hawaiian and other ocean island lava flows that reach the coastline can deposit significant volumes of lava in submarine deltas. The catastrophic collapse of these deltas represents one of the most significant, but least predictable, volcanic hazards at ocean islands. The volume of lava deposited below sea level in delta-forming eruptions and the mechanisms of delta construction and destruction are rarely documented. Here, we report on bathymetric surveys and ROV observations following the Kīlauea 2018 eruption that, along with a comparison to the deltas formed at Pu‘u ‘Ō‘ō over the past decade, provide new insight into delta formation. Bathymetric differencing reveals that the 2018 deltas contain more than half of the total volume of lava erupted. In addition, we find that the 2018 deltas are comprised largely of coarse-grained volcanic breccias and intact lava flows, which contrast with those at Pu‘u ‘Ō‘ō that contain a large fraction of fine-grained hyaloclastite. We attribute this difference to less efficient fragmentation of the 2018 ‘a‘ā flows leading to fragmentation by collapse rather than hydrovolcanic explosion. We suggest a mechanistic model where the characteristic grain size influences the form and stability of the delta with fine grain size deltas (Pu‘u ‘Ō‘ō) experiencing larger landslides with greater run-out supported by increased pore pressure and with coarse grain size deltas (Kīlauea 2018) experiencing smaller landslides that quickly stop as the pore pressure rapidly dissipates. This difference, if validated for other lava deltas, would provide a means to assess potential delta stability in future eruptions.


","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01424-1","usgsCitation":"Soule, S.A., Zoeller, M.H., and Parcheta, C., 2021, Submarine lava deltas of the 2018 eruption of Kilauea volcano: Bulletin of Volcanology, v. 83, 23, 16 p., https://doi.org/10.1007/s00445-020-01424-1.","productDescription":"23, 16 p.","ipdsId":"IP-119021","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-020-01424-1","text":"Publisher Index Page"},{"id":384715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3089141845703,\n 19.237901559805035\n ],\n [\n -155.02532958984375,\n 19.237901559805035\n ],\n [\n -155.02532958984375,\n 19.449759112405612\n ],\n [\n -155.3089141845703,\n 19.449759112405612\n ],\n [\n -155.3089141845703,\n 19.237901559805035\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":813097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zoeller, Michael H. 0000-0003-4716-8567","orcid":"https://orcid.org/0000-0003-4716-8567","contributorId":214557,"corporation":false,"usgs":true,"family":"Zoeller","given":"Michael","email":"","middleInitial":"H.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":813099,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217783,"text":"70217783 - 2021 - Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators","interactions":[],"lastModifiedDate":"2021-04-19T15:43:33.892853","indexId":"70217783","displayToPublicDate":"2021-03-10T10:41:13","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":8561,"text":"AWWI Technical Report","active":true,"publicationSubtype":{"id":4}},"title":"Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators","docAbstract":"

The impacts of wind power development on bat and bird populations are commonly assessed by estimating the number of fatalities at wind power facilities through post-construction monitoring (PCM) studies. Standard methodology involves periodic carcass searches on plots beneath turbines (Strickland et al. 2011, US Fish and Wildlife Service 2012). The resulting counts are adjusted to compensate for bias due to imperfect carcass detection by searchers, removal of carcasses by scavengers or other processes (Korner-Nievergelt et al. 2011), and carcasses that may have fallen outside of searched areas. To account for the bias in counts due to imperfect detection and carcass removal, investigators typically conduct bias trial experiments to inform models of carcass detection probability. Many different estimators have been proposed that combine information about the bias trial experiments to estimate a detection probability for carcasses (g) and ultimately obtain an estimate of total mortality (M). The two estimators that have seen the most widespread use in North America recently are the Huso (Huso 2011, Huso et al. 2012) and Shoenfeld (Shoenfeld 2004; also called the Erickson estimator) estimators. GenEst (Dalthorp et al. 2018a, 2018b, 2018c) is the newest statistical estimator to become available and was designed to improve upon the Huso and Shoenfeld estimators by generalizing the key assumptions in both, and to improve comparability among new PCM studies. In addition to relaxing some of the assumptions inherent to the Huso and Shoenfeld estimators, GenEst uses a parametric bootstrap applied to a novel approach to variance estimation (Madsen et al. 2019).

The current study was undertaken to document the performance of GenEst relative to the Huso and Shoenfeld estimators. We took a simulation approach to the study because simulation data provides the basis to compare mortality estimators under conditions where the “truth” is known. The estimators were compared on three metrics: 1) bias—the tendency of an estimator to over- or under-estimate actual mortality, 2) precision—the ability of an estimator to constrain an estimate to a narrow range (measured here as the width of a 90% confidence interval [CI] around the point estimate divided by the true, known mortality), and 3) CI coverage—the probability a CI with a specified level of confidence actually includes the true level of mortality.

Although our simulations were conceived and designed—and are discussed—with respect to wind power facilities, it is important to note that the estimators and results discussed here are relevant to any post-construction fatality monitoring study that may occur (such as at solar facilities) where detection is imperfect. Although our study treats the problem of mortality estimation when detection is imperfect, it is also important to note that all of the estimators considered here are Horvitz-Thompson (Horvitz and Thompson 1952) style estimators, that is, none are designed to estimate the mortality of rare species as might be necessary under an Incidental Take Permit. The Evidence of Absence estimator (Dalthorp et al. 2017) is still the most appropriate statistical tool for rare event estimation.

The simulations cover a broad range of conditions that may occur in field studies and complete results are presented without commentary in the appendix. The main body of this report does not provide a comprehensive treatment of our results; rather, we try to identify some of the more important differences among the estimators and some conditions under which reliable mortality estimates are especially challenging.

","language":"English","publisher":"American Wind Wildlife Institute","usgsCitation":"Rabie, P., Riser-Espinoza, D., Studyvin, J., Dalthorp, D., and Huso, M., 2021, Performance of the GenEst Mortality Estimator Compared to The Huso and Shoenfeld Estimators: AWWI Technical Report, 29 p.","productDescription":"29 p.","ipdsId":"IP-119710","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":385197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385196,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://awwi.org/resources/genest/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rabie, Paul","contributorId":248699,"corporation":false,"usgs":false,"family":"Rabie","given":"Paul","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riser-Espinoza, Daniel","contributorId":248700,"corporation":false,"usgs":false,"family":"Riser-Espinoza","given":"Daniel","email":"","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Studyvin, Jared","contributorId":248701,"corporation":false,"usgs":false,"family":"Studyvin","given":"Jared","affiliations":[{"id":49982,"text":"WEST, Inc.","active":true,"usgs":false}],"preferred":false,"id":809637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":809638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":809639,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218813,"text":"70218813 - 2021 - The making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)","interactions":[],"lastModifiedDate":"2021-03-15T13:59:10.529639","indexId":"70218813","displayToPublicDate":"2021-03-05T07:53:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"The making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)","docAbstract":"

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.

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Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.

","language":"English","publisher":"Hindawi","doi":"10.1155/2021/6650821","usgsCitation":"Odom, R.H., and Ford, W., 2021, Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model: International Journal of Forestry Research, v. 2021, 6650821, 16 p., https://doi.org/10.1155/2021/6650821.","productDescription":"6650821, 16 p.","ipdsId":"IP-111053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2021/6650821","text":"Publisher Index Page"},{"id":393572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0089111328125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 43.95921358836687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, Richard H.","contributorId":171659,"corporation":false,"usgs":false,"family":"Odom","given":"Richard","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":829633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829632,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224614,"text":"70224614 - 2021 - Beach placer mineral deposits along localized paleoshorelines of the western Interior Seaway, upper cretaceous Fox Hills sandstone, eastern Denver Basin, Colorado","interactions":[],"lastModifiedDate":"2021-09-30T12:12:02.258589","indexId":"70224614","displayToPublicDate":"2021-03-02T07:10:04","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"RS-48","title":"Beach placer mineral deposits along localized paleoshorelines of the western Interior Seaway, upper cretaceous Fox Hills sandstone, eastern Denver Basin, Colorado","docAbstract":"

Beach placers deposited within the Fox Hills Sandstone along the eastern flank of the Denver Basin contain minerals deemed critical in 2018 by the U.S. Department of the Interior. These marine beach placers, or paleoplacers, were deposited in the Late Cretaceous along the western edge of the retreating Western Interior Seaway (WIS). Preliminary investigations determined that these deposits contain potential critical mineral resources including titanium, zirconium, hafnium, and rare earth elements (REE). This report contains the results of a limited investigation conducted by the CGS in this area to provide additional information on the nature of these mineral deposits. The following tasks were completed during this investigation: review and summary of publicly available documents and publications; collection of samples and stratigraphic analysis of accessible outcrops; mineralogical analysis of select samples; and laboratory analysis of samples for select critical mineral concentrations. This report may assist with future mineral exploration efforts in this area and provide insight into the retreat of the WIS during the Late Cretaceous.

","language":"English","publisher":"Colorado Geological Survey","collaboration":"Colorado geolgical Survey, Colorado School of Mines","usgsCitation":"O’Keeffe, M.K., Dechesne, M., Morgan, M.J., Keller, S., Pfaff, K., Mahatma, A., and Peretyatko, A.I., 2021, Beach placer mineral deposits along localized paleoshorelines of the western Interior Seaway, upper cretaceous Fox Hills sandstone, eastern Denver Basin, Colorado.","ipdsId":"IP-119246","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":390032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390031,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://coloradogeologicalsurvey.org/publications/placer-minerals-cretaceous-fox-hills-denver-basin-colorado/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O’Keeffe, Michael K","contributorId":266068,"corporation":false,"usgs":false,"family":"O’Keeffe","given":"Michael","email":"","middleInitial":"K","affiliations":[{"id":12745,"text":"Colorado Geological Survey","active":true,"usgs":false}],"preferred":false,"id":824277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":824278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan, Matthew J.","contributorId":171711,"corporation":false,"usgs":false,"family":"Morgan","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":824279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keller, Stephen M","contributorId":266069,"corporation":false,"usgs":false,"family":"Keller","given":"Stephen M","affiliations":[{"id":12745,"text":"Colorado Geological Survey","active":true,"usgs":false}],"preferred":false,"id":824280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pfaff, Katherina","contributorId":266070,"corporation":false,"usgs":false,"family":"Pfaff","given":"Katherina","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":824281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahatma, Asha","contributorId":266071,"corporation":false,"usgs":false,"family":"Mahatma","given":"Asha","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":824282,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peretyatko, Alexander I","contributorId":266072,"corporation":false,"usgs":false,"family":"Peretyatko","given":"Alexander","email":"","middleInitial":"I","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":824283,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222575,"text":"70222575 - 2021 - Toward an effective global green economy: The Critical Minerals Mapping Initiative (CMMI)","interactions":[],"lastModifiedDate":"2022-01-20T17:59:58.023235","indexId":"70222575","displayToPublicDate":"2021-03-01T11:59:25","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":10041,"text":"SGA News","active":true,"publicationSubtype":{"id":30}},"title":"Toward an effective global green economy: The Critical Minerals Mapping Initiative (CMMI)","docAbstract":"Global population growth, economic development and the accelerating pace of technological innovation are driving increased demand for non-fuel mineral commodities that are vital for emerging and low-carbon technologies. Examples of such commodities include cobalt and graphite for rechargeable batteries, tellurium in thin-film solar photovoltaics and rare earth elements (REE) in permanent magnets, electronics and medical technologies. These commodities are known as critical elements and/or minerals (collectively referred to as critical minerals), with the term critical used to define not only their importance for new technologies, but also their demand and vulnerability to supply disruption. The demand for critical minerals is likely to continue to grow, but supply is not assured. Therefore, national strategies in Australia, Canada, United States and elsewhere (e.g. Europe: Wittenberg et al. 2021) are being developed to encourage exploration and production, including resolving the geological processes responsible for their enrichrichment into viable ore deposits. In 2019, Geoscience Australia (GA), the Geological Survey of Canada (GSC) and the United States Geological Survey (USGS) formed the Critical Minerals Mapping Initiative (CMMI) to undertake research to develop a better understanding of critical mineral resources in known deposits, determine the geological controls on critical mineral distribution for deposits currently producing by-products, and identify new sources of supply through mineral prospectivity mapping and resource assessment.","language":"English","publisher":"Society for Geology Applied to Mineral Deposits (SGA)","usgsCitation":"Kelley, K.D., Huston, D., and Peter, J., 2021, Toward an effective global green economy: The Critical Minerals Mapping Initiative (CMMI): SGA News, v. 48, no. March 2021, p. 1-5.","productDescription":"5 p.","startPage":"1","endPage":"5","ipdsId":"IP-124472","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":394599,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387698,"type":{"id":15,"text":"Index Page"},"url":"https://e-sga.org/publications/sga-news/news-archive/"}],"volume":"48","issue":"March 2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":820614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huston, David","contributorId":261768,"corporation":false,"usgs":false,"family":"Huston","given":"David","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":820615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peter, Jan","contributorId":261769,"corporation":false,"usgs":false,"family":"Peter","given":"Jan","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":820616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220142,"text":"70220142 - 2021 - Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California","interactions":[],"lastModifiedDate":"2021-04-21T14:25:38.79225","indexId":"70220142","displayToPublicDate":"2021-03-01T09:21:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California","docAbstract":"

The Grass Valley orogenic gold district in the Sierra Nevada foothills province, central California, is the largest historical gold producer of the North American Cordillera. Gold mineralization is associated with shallowly dipping north-south veins hosted by the 160 Ma Grass Valley granodiorite to the southwest of the Grass Valley fault and steeply dipping east-west veins in accreted oceanic rocks to the northeast of this major fault. Quartz veins from both vein types show well-preserved primary textural relationships. Using a combination of petrographic and microanalytical techniques, the paragenetic sequence of minerals within the veins and the compositions of ore minerals were determined to constrain the mechanisms of quartz vein formation and gold deposition. The veins are composed of early quartz that formed through cooling of hydrothermal fluids derived from a geopressured reservoir at depth. The early quartz shows growth zoning in optical cathodoluminescence and contains abundant growth bands of primary inclusions. The primary inclusion assemblages and myriads of crosscutting secondary fluid inclusions have been affected by postentrapment modification, suggesting that early quartz formation was postdated by pronounced pressure fluctuations. These pressure fluctuations, presumably involving changes from lithostatic to hydrostatic conditions, may be related to fault failure of the host structure as predicted by the fault-valve model. Fluid flow associated with pressure cycling took place along microfractures and grain boundaries resulting in extensive recrystallization of the early quartz. Deposition of pyrite, arsenopyrite, and first-generation gold from these hydrothermal fluids causing recrystallization of the early quartz occurred as a result of wall-rock sulfidation. The gold forms invisible gold in the compositionally zoned pyrite or micron-sized inclusions within pyrite growth zones. The latest growth zones in euhedral quartz crystals that formed in association with this stage of the paragenesis contain very rare primary fluid inclusions that have not been affected by postentrapment modification. The hydrothermal system transitioned entirely to hydrostatic conditions immediately after formation of the latest quartz, explaining the preservation of the primary fluid inclusions. The formation of minor quartz in open spaces was followed by the deposition of second-generation native gold and telluride minerals that are commonly associated with base metal sulfides. Ore formation at this stage of the paragenesis is attributed to the rapid decompression of hydrothermal fluids escaping from the geopressured part of the crust into the overlying hydrostatic realm. There is no fluid inclusion evidence that this pressure drop resulted in fluid immiscibility of the hydrothermal fluids. Fluid inclusion evidence suggests that the north-south veins formed at a paleodepth of ~8 km, whereas the east-west veins appear to have formed at ~10 to 11 km below surface, confirming previous inferences that the NE-dipping Grass Valley reverse fault accommodated a large displacement. The findings of the study at Grass Valley have significant implications for the model for orogenic gold deposits, as the reconstruction of the paragenetic relationships provides evidence for the occurrence of two discrete events of gold introduction that occurred at different conditions during the evolution of the hydrothermal system.

","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4794","usgsCitation":"Taylor, R., Monecke, T., Reynolds, T.J., and Monecke, J., 2021, Paragenesis of an orogenic gold deposit: New insights on mineralizing processes at the Grass Valley District, California: Economic Geology, v. 116, no. 2, p. 323-356, https://doi.org/10.5382/econgeo.4794.","productDescription":"34 p.","startPage":"323","endPage":"356","ipdsId":"IP-112775","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":385250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Grass Valley district","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.16845703125,\n 36.99377838872517\n ],\n [\n -118.63037109375,\n 37.622933594900864\n ],\n [\n -120.05859375,\n 39.223742741391305\n ],\n [\n -120.201416015625,\n 40.85537053192494\n ],\n [\n -122.40966796874999,\n 40.95501133048621\n ],\n [\n -122.11303710937499,\n 39.62261494094297\n ],\n [\n -121.234130859375,\n 37.96152331396614\n ],\n [\n -120.16845703125,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"116","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":814576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monecke, Thomas","contributorId":210730,"corporation":false,"usgs":false,"family":"Monecke","given":"Thomas","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":814577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, T. James","contributorId":257560,"corporation":false,"usgs":false,"family":"Reynolds","given":"T.","email":"","middleInitial":"James","affiliations":[{"id":39908,"text":"FLUID INC.","active":true,"usgs":false}],"preferred":false,"id":814578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monecke, Jochen","contributorId":237834,"corporation":false,"usgs":false,"family":"Monecke","given":"Jochen","email":"","affiliations":[{"id":47621,"text":"Institute of Theoretical Physics, TU Bergakademie Freiberg, Leipziger Strae 23, 09596 Freiberg, Germany","active":true,"usgs":false}],"preferred":false,"id":814579,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228580,"text":"70228580 - 2021 - Risky movements? Natal dispersal does not decrease survival of a large herbivore","interactions":[],"lastModifiedDate":"2022-02-14T21:16:30.942974","indexId":"70228580","displayToPublicDate":"2021-02-24T15:09:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Risky movements? Natal dispersal does not decrease survival of a large herbivore","docAbstract":"

Natal dispersal is assumed to be a particularly risky movement behavior as individuals transfer, often long distances, from birth site to site of potential first reproduction. Though, because this behavior persists in populations, it is assumed that dispersal increases the fitness of individuals despite the potential for increased risk of mortality. The extent of dispersal risk, however, has rarely been tested, especially for large mammals. Therefore, we aimed to test the relationship between dispersal and survival for both males and females in a large herbivore. Using a radio-transmittered sample of 398 juvenile male and 276 juvenile female white-tailed deer (Odocoileus virginianus), we compared survival rates of dispersers and non-dispersers. We predicted that dispersing deer would experience greater overall mortality than philopatric deer due to direct transfer-related risks (e.g., vehicular collision), indirect immigration-related mortality attributable to colonization of unfamiliar habitat, and increased over-winter mortality associated with energetic costs of movement and unfamiliarity with recently colonized habitat. For both male and female yearlings, survival rates of dispersers (male = 49.9%, female = 64.0%) did not differ from non-dispersers (male = 51.6%, female = 70.7%). Only two individuals (both female) were killed by vehicular collision during transfer, and over-winter survival patterns were similar between the two groups. Although dispersal movement likely incurs energetic costs on dispersers, these costs do not necessarily translate to decreased survival. In many species, including white-tailed deer, dispersal is likely condition-dependent, such that larger and healthier individuals are more likely to disperse; therefore, costs associated with dispersal are more likely to be borne successfully by those individuals that do disperse. Whether low-risk dispersal of large mammals is the rule or the exception will require additional research. Further, future research is needed to evaluate non-survival fitness-related costs and benefits of dispersal (e.g., increased reproductive opportunities for dispersers).

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7227","usgsCitation":"Long, E., Diefenbach, D.R., Lutz, C., Wallingford, B., and Rosenberry, C., 2021, Risky movements? 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\"}}]}","volume":"11","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Eric S.","contributorId":276215,"corporation":false,"usgs":false,"family":"Long","given":"Eric S.","affiliations":[{"id":56939,"text":"Seattle Pacific University","active":true,"usgs":false}],"preferred":false,"id":834669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lutz, Clayton L.","contributorId":276216,"corporation":false,"usgs":false,"family":"Lutz","given":"Clayton L.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallingford, Bret D.","contributorId":276217,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberry, Christopher S.","contributorId":276218,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834672,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229051,"text":"70229051 - 2021 - Uncovering process domains in large rivers: Patterns and potential drivers of benthic substrate heterogeneity in two North American riverscapes","interactions":[],"lastModifiedDate":"2022-02-28T14:29:43.181527","indexId":"70229051","displayToPublicDate":"2021-02-15T08:18:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Uncovering process domains in large rivers: Patterns and potential drivers of benthic substrate heterogeneity in two North American riverscapes","docAbstract":"

Identifying and understanding functional process domains (sensu Montgomery, 1999) in rivers is paramount for linking the physical habitat template to ecosystem structure and function. To date, efforts to do this have been rare, especially in large rivers, as they require appropriate tools for quantifying habitat heterogeneity with fine-scale resolution across broad spatial extents. In this study, we used side-scan sonar technology to map riverbed substrate at six sites in the Yellowstone and Missouri rivers. Substrate maps were then analyzed and visualized using geospatial analysis to relate fine-grained spatial substrate patterns to process domain structure. Our findings revealed two distinct nested domains of substrate patchiness, suggesting that different factors are responsible for shaping patterns of substrate at different scales. Although small-scale patchiness in substrate was likely driven by internal, or autogenic, physical processes, patterns at larger segment extents (>3 km) were often driven by abrupt transitions in habitat related to exogenous factors such as lateral erosion of talus, tributary inputs, and bank armoring. Additionally, we found that heterogeneity in benthic substrate increased with spatial extent at all of our study sites; however, this relationship was lower in the Missouri River, which is altered by impoundment. Our study represents one of the first efforts to relate benthic habitat heterogeneity to nested process domain structure in large riverscapes, and offers a unique perspective for linking landscape processes, geomorphological habitat heterogeneity, and biological structure and function in large rivers.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2020.107524","usgsCitation":"Scholl, E., Cross, W.F., Baxter, C.V., and Guy, C.S., 2021, Uncovering process domains in large rivers: Patterns and potential drivers of benthic substrate heterogeneity in two North American riverscapes: Geomorphology, v. 375, p. 1-15, https://doi.org/10.1016/j.geomorph.2020.107524.","productDescription":"107524, 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-120694","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487762,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/5832738","text":"External Repository"},{"id":396542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Missouri River, Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.820068359375,\n 47.25686404408872\n ],\n [\n -103.60107421874999,\n 47.25686404408872\n ],\n [\n -103.60107421874999,\n 48.22467264956519\n ],\n [\n -106.820068359375,\n 48.22467264956519\n ],\n [\n -106.820068359375,\n 47.25686404408872\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"375","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Scholl, E.A","contributorId":286923,"corporation":false,"usgs":false,"family":"Scholl","given":"E.A","email":"","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":836362,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, W. F.","contributorId":15412,"corporation":false,"usgs":true,"family":"Cross","given":"W.","email":"","middleInitial":"F.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":836363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, C. V.","contributorId":62853,"corporation":false,"usgs":true,"family":"Baxter","given":"C.","email":"","middleInitial":"V.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":836364,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":836361,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219165,"text":"70219165 - 2021 - Seasonal impoundment alters patterns of tidal wetland plant diversity across spatial scales","interactions":[],"lastModifiedDate":"2021-03-29T13:00:49.94313","indexId":"70219165","displayToPublicDate":"2021-02-09T07:56:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal impoundment alters patterns of tidal wetland plant diversity across spatial scales","docAbstract":"

Understanding patterns of biodiversity is a key goal of ecology and is especially pressing in the current human‐caused biodiversity crisis. In wetland ecosystems, human impacts are centered around hydrologic manipulation including the common practice of wetland diking and impoundment. Constraining how wetland management influences plant biodiversity patterns across spatial scales will provide information on how best to modify actions to preserve biodiversity and ecosystem function in managed wetlands. Here, we compare patterns of plant diversity and species presence, abundance, and community composition at several spatial scales among tidal wetlands along an estuarine salinity gradient and managed wetlands that were formerly tidal. Managed impounded wetlands had decreased alpha and gamma diversity of rare species, with less than 60% of the species richness found in tidal brackish wetlands at several spatial scales. There was little change in the overall pattern of alpha, beta, and gamma diversity for common species in impounded wetlands; however, dominant tidal brackish species, primarily perennial rhizomatous graminoids, were replaced with management target plants and non‐native annual grasses in impounded wetlands. This species replacement led to over 60% of impounded sites being classified as containing novel plant assemblages. An additional 25% of impounded sites were classified as containing tidal saline plant assemblages, suggesting potential soil salinization. Along the estuarine gradient, patchiness and codominance of common plant species drove high diversity and turnover in tidal brackish wetlands, while it remains unclear whether tidal fresh or brackish wetlands maximize rare plant diversity. With reduced species richness, altered functional dominants, and novel or saline assemblages, impounded brackish wetlands may require careful water management to balance native plant biodiversity, associated ecosystem processes, and waterfowl requirements.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3366","usgsCitation":"Jones, S., Janousek, C.N., Casazza, M.L., Takekawa, J., and Thorne, K., 2021, Seasonal impoundment alters patterns of tidal wetland plant diversity across spatial scales: Ecosphere, v. 12, no. 2, e03366, 19 p., https://doi.org/10.1002/ecs2.3366.","productDescription":"e03366, 19 p.","ipdsId":"IP-121980","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453532,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3366","text":"Publisher Index Page"},{"id":436516,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZG1Y72","text":"USGS data release","linkHelpText":"Impounded and tidal wetland plant diversity and composition across spatial scales, San Francisco Bay-Delta, California, USA (2016-2018)"},{"id":384713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.93701171874999,\n 36.89719446989036\n ],\n [\n -121.57470703125,\n 36.89719446989036\n ],\n [\n -121.57470703125,\n 38.976492485539396\n ],\n [\n -122.93701171874999,\n 38.976492485539396\n ],\n [\n -122.93701171874999,\n 36.89719446989036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janousek, Christopher N. 0000-0003-2124-6715","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":103951,"corporation":false,"usgs":false,"family":"Janousek","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":813087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203805,"corporation":false,"usgs":false,"family":"Takekawa","given":"John Y.","affiliations":[{"id":36724,"text":"Audubon California, Richardson Bay Audubon Center and Sanctuary, Tiburon, CA","active":true,"usgs":false}],"preferred":false,"id":813089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813090,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217900,"text":"70217900 - 2021 - Microbial and viral indicators of pathogens and human health risks from recreational exposure to waters impaired by fecal contamination","interactions":[],"lastModifiedDate":"2021-02-10T13:57:39.234893","indexId":"70217900","displayToPublicDate":"2021-02-09T07:55:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5896,"text":"Journal of Sustainable Water in the Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Microbial and viral indicators of pathogens and human health risks from recreational exposure to waters impaired by fecal contamination","docAbstract":"

Fecal indicator bacteria (FIB) (e.g., fecal coliforms, Escherichia coli, and enterococci) have been used for decades to monitor for and protect the public from waterborne pathogens from fecal contamination. However, FIB may not perform well at predicting the presence of waterborne pathogens or human health outcomes from recreational exposure to fecal-contaminated surface waters. Numerous factors can influence the relationship between FIB and pathogens or human health outcomes, including the source(s) of contamination, the type of pathogen(s) present, differences in the survival and behavior of FIB and pathogens in the wastewater conveyance and treatment process, and varying environmental conditions. As a result, different indicators, such as source-specific microbial source tracking (MST) markers and viral fecal indicators, have been used as possible surrogates to better approximate pathogen abundance and human health risks in recreational waters. The performance of these alternative indicators has been mixed, with some promise of viral indicators better approximating viral pathogens than bacterial fecal indicators, and FIB generally more closely associated with bacterial and protozoal pathogen presence than human MST markers. Many of the assays to detect and quantify fecal indicators and pathogens are polymerase chain reaction-based assays, which detect and quantify nucleic acid [deoxyribonucleic acid (DNA) and ribonucleic acid (RNA)] sequences specific to a target of interest. Recent advances in DNA and RNA sequencing technologies may push the field toward metabarcoding approaches, where multiple targets can be detected and quantified simultaneously. Metabarcoding is currently more applicable to bacterial and protozoal assessments than viral assessments based on a lack of universal metabarcoding markers for viruses. Innovative technologies, such as biosensors and nanotechnologies, may provide more sensitive and accurate tools to detect and quantify pathogens. When a specific pathogen is of concern for a recreational water body, a practical approach in estimating the likelihood of human health outcomes is the application of quantitative microbial risk assessments (QMRAs). Quantitative microbial risk assessments can be used to model the likelihood of pathogen-specific human health outcomes from recreational exposure as a function of a surrogate indicator. Inputs for QMRAs include the ratio between the indicator to be monitored and the pathogen of interest, the concentration of the indicator, the amount of water ingested, and the likelihood of the health outcome based on the estimated amount of pathogen consumed. There are numerous unknowns about the behavior and survival of fecal indicators and pathogens in environmental waters. Developing accurate models to predict pathogen concentrations from fecal indicators in recreational waters will require a better understanding of these unknowns. Current methods and technologies for detecting and quantifying fecal indicators and pathogens are limited due to the rare and patchy nature of pathogens. Technological advances may help improve sensitivity for detecting and quantifying pathogens.

","language":"English","publisher":"ASCE","doi":"10.1061/JSWBAY.0000936","usgsCitation":"McKee, A.M., and Cruz, M.A., 2021, Microbial and viral indicators of pathogens and human health risks from recreational exposure to waters impaired by fecal contamination: Journal of Sustainable Water in the Built Environment, v. 7, no. 2, 03121001, 15 p., https://doi.org/10.1061/JSWBAY.0000936.","productDescription":"03121001, 15 p.","ipdsId":"IP-119263","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":453534,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jswbay.0000936","text":"Publisher Index Page"},{"id":383197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Anna M. 0000-0003-2790-5320 amckee@usgs.gov","orcid":"https://orcid.org/0000-0003-2790-5320","contributorId":166725,"corporation":false,"usgs":true,"family":"McKee","given":"Anna","email":"amckee@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cruz, Marcella A. 0000-0002-8100-8738","orcid":"https://orcid.org/0000-0002-8100-8738","contributorId":248871,"corporation":false,"usgs":true,"family":"Cruz","given":"Marcella","email":"","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810121,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226958,"text":"70226958 - 2021 - The critical minerals initiative of the U.S. Geological Survey’s mineral deposit database project: USMIN","interactions":[],"lastModifiedDate":"2021-12-22T12:56:25.908739","indexId":"70226958","displayToPublicDate":"2021-02-08T06:52:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9961,"text":"Mining, Metallurgy & Exploration (MME)","active":true,"publicationSubtype":{"id":10}},"title":"The critical minerals initiative of the U.S. Geological Survey’s mineral deposit database project: USMIN","docAbstract":"

The objective of the US Geological Survey’s mineral deposit database project (USMIN) is to develop a comprehensive twenty-first century geospatial database that is the authoritative source of the most important mines, mineral deposits, and mineral districts of the US. Since May 2017, the project has focused on critical minerals. Data for critical minerals that are produced as products are relatively robust, whereas data for critical minerals that may be recovered as byproducts are commonly of much poorer quality. Similarly, more is known about critical minerals that occur in conventional deposits than where those critical minerals occur in unconventional deposits. For example, rare earth elements occur principally in deposits hosted by alkaline igneous rocks, but there is potential for their production from phosphate rock mining, which is less documented. Lithium (Li) has been recovered from pegmatites and brines, but other Li-bearing deposit types have been delineated that may go into production. Cobalt may be produced as a byproduct or coproduct from a wide range of mineral deposit types, whereas rhenium is a byproduct of copper ore. Significant opportunities for research exist that could help identify new sources of critical minerals, and may also help increase production and recovery from existing sources.

","language":"English","publisher":"Springer","doi":"10.1007/s42461-020-00372-w","usgsCitation":"Mauk, J.L., Karl, N.A., San Juan, C.A., Knudsen, L.D., Schmeda, G., Forbush, C.R., Van Gosen, B.S., Mullins, M., and Scott, P.C., 2021, The critical minerals initiative of the U.S. Geological Survey’s mineral deposit database project: USMIN: Mining, Metallurgy & Exploration (MME), v. 38, p. 775-797, https://doi.org/10.1007/s42461-020-00372-w.","productDescription":"23 p.","startPage":"775","endPage":"797","ipdsId":"IP-124056","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":393294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2021-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karl, Nick A 0000-0003-2858-2498","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":246006,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"","middleInitial":"A","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":828935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"San Juan, Carma A. 0000-0002-9151-1919 csanjuan@usgs.gov","orcid":"https://orcid.org/0000-0002-9151-1919","contributorId":1146,"corporation":false,"usgs":true,"family":"San Juan","given":"Carma","email":"csanjuan@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828939,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knudsen, Liam Dandurand 0000-0003-3691-5475","orcid":"https://orcid.org/0000-0003-3691-5475","contributorId":240625,"corporation":false,"usgs":true,"family":"Knudsen","given":"Liam","email":"","middleInitial":"Dandurand","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmeda, German 0000-0003-2676-1118","orcid":"https://orcid.org/0000-0003-2676-1118","contributorId":203280,"corporation":false,"usgs":true,"family":"Schmeda","given":"German","email":"","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828940,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forbush, Clayton Robert 0000-0002-6735-2719","orcid":"https://orcid.org/0000-0002-6735-2719","contributorId":270288,"corporation":false,"usgs":true,"family":"Forbush","given":"Clayton","email":"","middleInitial":"Robert","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828936,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":828942,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mullins, Morgan 0000-0003-1699-7688","orcid":"https://orcid.org/0000-0003-1699-7688","contributorId":270290,"corporation":false,"usgs":false,"family":"Mullins","given":"Morgan","email":"","affiliations":[],"preferred":false,"id":828938,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scott, Patrick Christopher 0000-0001-8184-4333","orcid":"https://orcid.org/0000-0001-8184-4333","contributorId":225025,"corporation":false,"usgs":true,"family":"Scott","given":"Patrick","email":"","middleInitial":"Christopher","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":828941,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70224642,"text":"70224642 - 2021 - Only sun-lit leaves of the uppermost canopy exceed both air temperature and photosynthetic thermal optima in a wet tropical forest","interactions":[],"lastModifiedDate":"2021-10-01T12:45:06.53582","indexId":"70224642","displayToPublicDate":"2021-02-06T07:43:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Only sun-lit leaves of the uppermost canopy exceed both air temperature and photosynthetic thermal optima in a wet tropical forest","docAbstract":"

Tropical forests have evolved under relatively narrow temperature regimes, and therefore may be more susceptible to climatic change than forests in higher latitudes. Recent evidence shows that lowland tropical forest canopies may already be exceeding thermal maxima for photosynthesis. Height can strongly influence both the microclimate and physiology of forest canopy foliage, yet vertical trends in canopy micrometeorology are rarely examined in tropical forests. To improve our understanding of how climatological and micrometeorological conditions affect tropical tree function, we assessed vertical gradients of photosynthetic photon flux density, vapor pressure deficit, air temperature, leaf temperature, and the difference between leaf and air temperature (ΔT) in a Puerto Rican tropical wet forest. Both air temperature and vapor pressure deficit increased linearly with height. Leaf temperature, however, did not significantly differ across the shaded foliage from 0-16 m, while the uppermost layer (20 m) was up to 4°C hotter than the rest of the foliage and up to 5°C hotter than air temperature at the highest radiation intensity. As a result, leaf temperatures in the shaded middle canopy and understory showed nearly poikilothermic behavior (i.e., leaf temperatures = air temperature), while the uppermost canopy strata showed megathermic behavior (i.e., leaf temperatures greater than air temperature), revealing different thermoregulation strategies for sun-lit versus shaded foliage. In addition, the uppermost canopy was the only stratum to exceed mean photosynthetic temperature optima for this site (Topt = 30.2 ± 1.1°C). Because the upper canopy plays a disproportionately large role in whole-forest photosynthesis, continued warming could potentially weaken the tropics’ carbon sink capacity. However, the shaded leaves may be able increase carbon uptake with further warming because they appear to be able to maintain temperatures below photosynthetic optima, possibly with the help of radiation shielding provided by the uppermost canopy layer.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2021.108347","usgsCitation":"Miller, B.D., Carter, K.R., Reed, S., Wood, T.E., and Cavaleri, M.A., 2021, Only sun-lit leaves of the uppermost canopy exceed both air temperature and photosynthetic thermal optima in a wet tropical forest: Agricultural and Forest Meteorology, v. 301-302, 108347, 10 p., https://doi.org/10.1016/j.agrformet.2021.108347.","productDescription":"108347, 10 p.","ipdsId":"IP-125332","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":453556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1776881","text":"Publisher Index Page"},{"id":390104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"301-302","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Benjamin D.","contributorId":266178,"corporation":false,"usgs":false,"family":"Miller","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":54939,"text":"College of Forest Resources and Environmental Science, Michigan Technological University, 1400 Townsend Dr., Houghton, MI 49931, USA","active":true,"usgs":false}],"preferred":false,"id":824511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Kelsey R.","contributorId":245234,"corporation":false,"usgs":false,"family":"Carter","given":"Kelsey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":824512,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824513,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":824514,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cavaleri, Molly A.","contributorId":206282,"corporation":false,"usgs":false,"family":"Cavaleri","given":"Molly","email":"","middleInitial":"A.","affiliations":[{"id":34284,"text":"School of Forest Resources and Environmental Science, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":824515,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217720,"text":"70217720 - 2021 - Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska","interactions":[],"lastModifiedDate":"2021-02-01T14:12:59.353933","indexId":"70217720","displayToPublicDate":"2021-01-29T07:47:46","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska","docAbstract":"Porphyry Cu and Mo deposits and occurrences are found throughout Alaska; they formed episodically during repeated subduction and arc-continent collisions spanning the Silurian to Quaternary. Porphyry systems occur in continental-margin and island arcs, which are broadly grouped into pre-accretionary or post-accretionary arcs. Pre-Mesozoic occurrences formed in continental or island arcs prior to accretion onto the margin of North America, whereas Mesozoic and younger systems formed in arcs that developed after terrane fragments were accreted to the margin of North America. As a result, older porphyry systems are typically in the interior and northern metallogenic belts, whereas the younger porphyry systems are predominantly found in the southern third of the state, closer to the modern continental margin.\nAlaska porphyry formation peaked in the mid-Cretaceous and continued through the Late Cretaceous to Tertiary, in association with continental-margin arcs extending from the eastern interior, into southwest Alaska and along the Alaska Peninsula and Aleutian Islands. Porphyry system formation is not generally recognized in the Early Cretaceous, Triassic, or early Paleozoic – time periods that coincide with continental collisional events or extension. Relatively few pre-accretionary porphyry systems are documented in more deeply exhumed arc segments due to low preservation potential in areas of rapid or repeated bedrock uplift and associated erosion that occurred during later tectonic events.\nSignificant diversity is observed in porphyry occurrences across the state and even within the same region. Occurrences form in association with arc-related intrusions or intrusive complexes, that range in composition from diorite to syenite, but are commonly monzonitic to granitic. Some porphyry occurrences are associated with alkaline intrusive belts that exhibit a stronger crustal contribution to magmatic sources. Intrusions associated with porphyry formation in Alaska are commonly moderately oxidized, however, a distinct group of porphyry systems are associated with more-reduced magmas.\nHydrothermal alteration described at many occurrences exhibits zoning from proximal potassic alteration to typically peripheral and(or) later sericitic alteration, that is flanked by large zones of propylitic alteration. Diversity in alteration is observed where sodic and sodic-calcic alteration is present, commonly in more-enigmatic deposits, such as Island Mountain and Chicken Mountain. Advanced argillic alteration is rare, but present in notable examples, such as the Pebble porphyry Cu(-Au-Mo) deposit. Sulfide mineralization is characterized by pyrite, chalcopyrite, molybdenite, and rare bornite hosted in veinlets, veins and disseminations in wallrocks and causative intrusions. Some porphyry systems contain abundant pyrrhotite and(or) arsenopyrite in the mineral assemblages. Systems that exhibit bornite-bearing assemblages containing abundant molybdenite are commonly arsenic- and gold-poor and tend to be associated with more oxidized arc magmas. In contrast, those systems that are pyrrhotite and(or) arsenopyrite dominant tend to be gold, arsenic, and bismuth bearing, and are commonly associated with more-reduced magmas. \nExploration for porphyry occurrences in Alaska has experienced a resurgence and currently constitutes about 20% of exploration dollars in the state. Many systems lack complete descriptions, and coupled with the cost of exploration, remain incompletely explored. Additional understanding of known occurrences combined with a framework geologic understanding of porphyry-bearing metallogenic belts will likely result in new discoveries in the future.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Porphyry deposits of the northwestern Cordillera of North America: A 25-year update","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Canadian Institute of Mining, Metallurgy and Petroleum","usgsCitation":"Kreiner, D.C., Jones, J.V., Kelley, K.D., and Graham, G.E., 2021, Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska, chap. of Porphyry deposits of the northwestern Cordillera of North America: A 25-year update, v. 57, p. 134-175.","productDescription":"42 p.","startPage":"134","endPage":"175","ipdsId":"IP-113700","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":382786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382778,"type":{"id":15,"text":"Index Page"},"url":"https://store.cim.org/en/porphyry-deposits-of-the-northwestern-cordillera-of-north-america-a-25-year-update-2"}],"country":"United 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III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":809367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":809369,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218170,"text":"70218170 - 2021 - Joint species distribution models of Everglades wading birds to inform restoration planning","interactions":[],"lastModifiedDate":"2023-07-07T14:08:20.276686","indexId":"70218170","displayToPublicDate":"2021-01-28T10:04:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Joint species distribution models of Everglades wading birds to inform restoration planning","docAbstract":"

Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0–1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0245973","usgsCitation":"D’Acunto, L., Pearlstine, L.G., and Romanach, S., 2021, Joint species distribution models of Everglades wading birds to inform restoration planning: PLoS ONE, v. 16, no. 1, e0245973, 21 p.; Data Release, https://doi.org/10.1371/journal.pone.0245973.","productDescription":"e0245973, 21 p.; Data Release","ipdsId":"IP-119201","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453665,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0245973","text":"Publisher Index Page"},{"id":383272,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418748,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P934K8T0","text":"EverWaders species distribution model development and output in the Greater Everglades from 2000-2009","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.419921875,\n 25.209911213827688\n ],\n [\n -80.474853515625,\n 25.27450351782018\n ],\n [\n -80.562744140625,\n 25.348990395713393\n ],\n [\n -80.562744140625,\n 25.55730943578312\n ],\n [\n -80.299072265625,\n 26.288490072961164\n ],\n [\n -80.1617431640625,\n 26.426308999847024\n ],\n [\n -80.26611328125,\n 26.711266913515747\n ],\n [\n -80.4473876953125,\n 26.716173757934094\n ],\n [\n -80.5133056640625,\n 26.554136386183785\n ],\n [\n -80.79345703125,\n 26.504988828743404\n ],\n [\n -81.0296630859375,\n 26.455820238459893\n ],\n [\n -81.00082397460938,\n 26.292183791046618\n ],\n [\n -81.47872924804688,\n 26.223215001067558\n ],\n [\n -81.64352416992188,\n 26.172694044887898\n ],\n [\n -81.78085327148438,\n 26.078987535225927\n ],\n [\n -81.74514770507812,\n 25.90617390922084\n ],\n [\n -81.6339111328125,\n 25.808545671771615\n ],\n [\n -81.38259887695312,\n 25.720735134412106\n ],\n [\n -81.24252319335938,\n 25.492868271257127\n ],\n [\n -81.18209838867188,\n 25.370086680063082\n ],\n [\n -81.17660522460938,\n 25.21488107113259\n ],\n [\n -81.03790283203125,\n 25.069429002821355\n ],\n [\n -80.58059692382812,\n 25.14652775303499\n ],\n [\n -80.419921875,\n 25.209911213827688\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":810303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":810304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":810305,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217716,"text":"70217716 - 2021 - Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","interactions":[],"lastModifiedDate":"2021-01-29T13:41:03.444159","indexId":"70217716","displayToPublicDate":"2021-01-28T07:33:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","docAbstract":"

Lyme disease is common in the northeastern United States, but rare in the southeast, even though the tick vector is found in both regions. Infection prevalence of Lyme spirochetes in host-seeking ticks, an important component to the risk of Lyme disease, is also high in the northeast and northern midwest, but declines sharply in the south. As ticks must acquire Lyme spirochetes from infected vertebrate hosts, the role of wildlife species composition on Lyme disease risk has been a topic of lively academic discussion. We compared tick–vertebrate host interactions using standardized sampling methods among 8 sites scattered throughout the eastern US. Geographical trends in diversity of tick hosts are gradual and do not match the sharp decline in prevalence at southern sites, but tick–host associations show a clear shift from mammals in the north to reptiles in the south. Tick infection prevalence declines north to south largely because of high tick infestation of efficient spirochete reservoir hosts (rodents and shrews) in the north but not in the south. Minimal infestation of small mammals in the south results from strong selective attachment to lizards such as skinks (which are inefficient reservoirs for Lyme spirochetes) in the southern states. Selective host choice, along with latitudinal differences in tick host-seeking behavior and variations in tick densities, explains the geographic pattern of Lyme disease in the eastern US.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pbio.3001066","usgsCitation":"Ginsberg, H., Hickling, G.J., Burke, R.L., Ogden, N.H., Beati, L., LeBrun, R.A., Arsnoe, I.M., Gerhold, R., Han, S., Jackson, K., Maestas, L., Moody, T., Pang, G., Ross, B., Rulison, E.L., and Tsao, J.I., 2021, Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density: PLoS Biology, v. 19, no. 1, e3001066, 20 p., https://doi.org/10.1371/journal.pbio.3001066.","productDescription":"e3001066, 20 p.","ipdsId":"IP-117549","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":453671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pbio.3001066","text":"Publisher Index Page"},{"id":382785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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University","active":true,"usgs":false}],"preferred":false,"id":809362,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70226209,"text":"70226209 - 2021 - Assessment of flood forecast products for a coupled tributary-Coastal model","interactions":[],"lastModifiedDate":"2021-11-17T13:49:27.905474","indexId":"70226209","displayToPublicDate":"2021-01-27T07:46:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of flood forecast products for a coupled tributary-Coastal model","docAbstract":"
Compound flooding, resulting from a combination of riverine and coastal processes, is a complex but important hazard to resolve along urbanized shorelines in the vicinity of river mouths. However, inland flooding models rarely consider oceanographic conditions, and vice versa for coastal flood models. Here, we describe the development of an operational, integrated coastal-watershed flooding model to address this issue of compound flooding in a highly urbanized estuarine environment, San Francisco Bay (CA, USA), where the surrounding communities are susceptible to flooding along the bay shoreline and inland rivers and creeks that drain to the bay. The integrated tributary-coastal forecast model (Hydro-Coastal Storm Modeling System, or Hydro-CoSMoS) was developed to provide water managers and other users with flood forecast information beyond what is currently available. Results presented here are focused on the interaction of the Napa River watershed and the San Pablo Bay at the northern end of San Francisco Bay. This paper describes the modeling setup, the scenario used in a tabletop exercise (TTE), and the assessment of the various flood forecast information products. Hydro-CoSMoS successfully demonstrated the capability to provide watershed and coastal flood information at scales and locations where no such information is currently available and was also successful in showing how tributary flows could be used to inform the coastal storm model during a flooding scenario. The TTE provided valuable feedback on how to guide continued model development and to inform what model outputs and formats are most useful to end-users. 
","language":"English","publisher":"MDPI","doi":"10.3390/w13030312","usgsCitation":"Cifelli, R., Johnson, L.E., Kim, J., Coleman, T., Pratt, G., Herdman, L.M., Martyr-Koller, R.C., Finzi-Hart, J., Erikson, L.H., Barnard, P.L., and Anderson, M., 2021, Assessment of flood forecast products for a coupled tributary-Coastal model: Water, v. 3, no. 13, 312, 21 p., https://doi.org/10.3390/w13030312.","productDescription":"312, 21 p.","ipdsId":"IP-125274","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13030312","text":"Publisher Index Page"},{"id":391794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Pablo 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States","interactions":[],"lastModifiedDate":"2021-02-15T15:43:28.004603","indexId":"70218175","displayToPublicDate":"2021-01-26T09:38:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Native American fire management at an ancient wildland–urban interface in the Southwest United States","docAbstract":"

The intersection of expanding human development and wildland landscapes—the “wildland–urban interface” or WUI—is one of the most vexing contexts for fire management because it involves complex interacting systems of people and nature. Here, we document the dynamism and stability of an ancient WUI that was apparently sustainable for more than 500 y. We combine ethnography, archaeology, paleoecology, and ecological modeling to infer intensive wood and fire use by Native American ancestors of Jemez Pueblo and the consequences on fire size, fire–climate relationships, and fire intensity. Initial settlement of northern New Mexico by Jemez farmers increased fire activity within an already dynamic landscape that experienced frequent fires. Wood harvesting for domestic fuel and architectural uses and abundant, small, patchy fires created a landscape that burned often but only rarely burned extensively. Depopulation of the forested landscape due to Spanish colonial impacts resulted in a rebound of fuels accompanied by the return of widely spreading, frequent surface fires. The sequence of more than 500 y of perennial small fires and wood collecting followed by frequent “free-range” wildland surface fires made the landscape resistant to extreme fire behavior, even when climate was conducive and surface fires were large. The ancient Jemez WUI offers an alternative model for fire management in modern WUI in the western United States, and possibly other settings where local management of woody fuels through use (domestic wood collecting) coupled with small prescribed fires may make these communities both self-reliant and more resilient to wildfire hazards.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2018733118","usgsCitation":"Roos, C., Swetnam, T.W., Ferguson, T.J., Liebmann, M.J., Loehman, R.A., Welch, J., Margolis, E.Q., Guiterman, C.H., Hockaday, W., Aiuvalasit, M., Battillo, J., Farella, J., and Kiahtipes, C., 2021, Native American fire management at an ancient wildland–urban interface in the Southwest United States: Proceedings of the National Academy of Sciences, v. 4, no. 118, e2018733118, 11 p., https://doi.org/10.1073/pnas.2018733118.","productDescription":"e2018733118, 11 p.","ipdsId":"IP-122927","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":453702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2018733118","text":"Publisher Index Page"},{"id":383270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.9404296875,\n 31.353636941500987\n ],\n [\n -108.19335937499999,\n 31.39115752282472\n ],\n [\n -108.10546875,\n 31.728167146023935\n ],\n [\n -102.919921875,\n 32.0639555946604\n ],\n [\n -103.02978515625,\n 37.16031654673677\n ],\n [\n -114.12597656249999,\n 37.125286284966805\n ],\n [\n -114.169921875,\n 35.94243575255426\n ],\n [\n -114.7412109375,\n 36.12012758978146\n ],\n [\n -114.41162109375,\n 34.470335121217474\n ],\n [\n -114.5654296875,\n 33.61461929233378\n ],\n [\n -114.58740234375,\n 33.119150226768866\n ],\n [\n -114.7412109375,\n 32.54681317351514\n ],\n [\n -111.15966796875,\n 31.372399104880525\n ],\n [\n -108.9404296875,\n 31.353636941500987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"118","noUsgsAuthors":false,"publicationDate":"2021-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Roos, Christopher","contributorId":251699,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swetnam, Thomas W.","contributorId":191872,"corporation":false,"usgs":false,"family":"Swetnam","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":810342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferguson, T. J.","contributorId":251700,"corporation":false,"usgs":false,"family":"Ferguson","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":810343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liebmann, Matthew J.","contributorId":179334,"corporation":false,"usgs":false,"family":"Liebmann","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":810344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":810345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welch, John","contributorId":251701,"corporation":false,"usgs":false,"family":"Welch","given":"John","email":"","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":810346,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810347,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guiterman, Christopher H.","contributorId":190553,"corporation":false,"usgs":false,"family":"Guiterman","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":810348,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hockaday, William","contributorId":251702,"corporation":false,"usgs":false,"family":"Hockaday","given":"William","email":"","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":810349,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aiuvalasit, Michael","contributorId":251703,"corporation":false,"usgs":false,"family":"Aiuvalasit","given":"Michael","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":810350,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Battillo, Jenna","contributorId":251704,"corporation":false,"usgs":false,"family":"Battillo","given":"Jenna","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810351,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Farella, Joshua","contributorId":179332,"corporation":false,"usgs":false,"family":"Farella","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":810352,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kiahtipes, Christopher","contributorId":251705,"corporation":false,"usgs":false,"family":"Kiahtipes","given":"Christopher","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":810353,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70217636,"text":"70217636 - 2021 - Human activities and weather drive contact rates of wintering elk","interactions":[],"lastModifiedDate":"2021-03-05T21:27:54.234412","indexId":"70217636","displayToPublicDate":"2021-01-25T07:08:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Human activities and weather drive contact rates of wintering elk","docAbstract":"
  1. Wildlife aggregation patterns can influence disease transmission. However, limited research evaluates the influence of anthropogenic and natural factors on aggregation. Many managers would like to reduce wildlife contact rates, driven by aggregation, to limit disease transmission. We develop a novel analytical framework to quantify how management activities such as supplemental feeding and hunting versus weather drive contact rates while accounting for correlated contacts. We apply the framework to the National Elk Refuge (NER), Wyoming, USA, where the probable arrival of chronic wasting disease (CWD) has magnified concerns.
  2. We used a daily proximity index to measure contact rates among 68 global positioning system collared elk from 2016 to 2019. We modelled contact rates as a function of abiotic weather‐related effects, anthropogenic effects and aggregation from the prior day. The winter of 2017–2018 had greater natural forage availability and little snow, which led to a rare non‐feeding year on the NER and provided a unique opportunity to evaluate the effect of feeding on contact rates relative to other conditions.
  3. Supplemental feeding was the strongest predictor of aggregation, and contact rates were 2.6 times larger while feeding occurred compared to the baseline rate (0.34 and 0.13, respectively). Snow‐covered area was the second strongest predictor of contact rates highlighting the importance of abiotic factors to elk aggregation, but this effect had half the strength of feeding. These results are the first to show, even in animals that congregate naturally, how greatly supplemental feeding amplifies aggregation. Contact rates were also 23% lower during times when elk hunting was active (0.10) compared to the baseline.
  4. Synthesis and applications. Supplemental feeding increased contacts between elk well above the natural effects of weather, even after accounting for correlated movement expected in wintering ungulates. Similarly, differences in hunting season timing with adjacent areas led to an increase in contacts, suggesting an additional management option for reducing aggregation. The analytical framework presented supports the evaluation of temporally varying management actions that influence aggregation broadly and can be easily implemented whether the interest in changing aggregation is related to reduction of disease transmission, human–wildlife conflict or inter‐species competition.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13818","usgsCitation":"Janousek, W.M., Graves, T., Berman, E., Chong, G.W., Cole, E.K., Dewey, S., Johnston, A.N., and Cross, P., 2021, Human activities and weather drive contact rates of wintering elk: Journal of Applied Ecology, v. 58, no. 3, p. 667-676, https://doi.org/10.1111/1365-2664.13818.","productDescription":"10 p.","startPage":"667","endPage":"676","ipdsId":"IP-117805","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453726,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13818","text":"Publisher Index Page"},{"id":436549,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF62CQ","text":"USGS data release","linkHelpText":"Daily 30-m fractional snow covered area and summary stats for the National Elk Refuge, Wyoming from 2015 to 2020"},{"id":382579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.78956604003905,\n 43.483815720045435\n ],\n [\n -110.54374694824219,\n 43.483815720045435\n ],\n [\n -110.54374694824219,\n 43.64054754952543\n ],\n [\n -110.78956604003905,\n 43.64054754952543\n ],\n [\n -110.78956604003905,\n 43.483815720045435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"58","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":809050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berman, Ethan 0000-0001-6112-6211","orcid":"https://orcid.org/0000-0001-6112-6211","contributorId":248405,"corporation":false,"usgs":false,"family":"Berman","given":"Ethan","affiliations":[],"preferred":false,"id":809052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chong, Geneva W. 0000-0003-3883-5153 geneva_chong@usgs.gov","orcid":"https://orcid.org/0000-0003-3883-5153","contributorId":419,"corporation":false,"usgs":true,"family":"Chong","given":"Geneva","email":"geneva_chong@usgs.gov","middleInitial":"W.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Eric K 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":248406,"corporation":false,"usgs":false,"family":"Cole","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":809054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dewey, Sarah","contributorId":145757,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":16229,"text":"National Park Service, Grand Teton National Park, PO Drawer 170, Moose, WY 83012 USA","active":true,"usgs":false}],"preferred":false,"id":809055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809057,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}