A new 3-D resistivity model, estimated from inversion of magnetotelluric data, images crustal and upper-mantle structure of the Wyoming Province and adjacent areas. The Archean province is imaged as a coherent resistive domain, in sharp contrast to active tectonic domains of the western U.S. Prominent high-conductivity belts define the northern, eastern, and southern margins of the Wyoming Province and are interpreted as sutures marking the remnants of Paleoproterozoic orogens. The model results suggest the northern boundary of the Wyoming Province is located 150 km south of its traditional placement and adjacent to a composite orogen separating the Wyoming Province and Medicine Hat block. The eastern province boundary is clearly imaged along the Black Hills, whereas the western margin is obscured by Cenozoic extension and magmatism. An internal boundary within the Wyoming Province is interpreted to represent a Neoarchean suture; in stark contrast to Proterozoic sutures, though, it is not marked by a high-conductivity belt. This difference in conductivity is speculated to reflect changes in the subduction process through time. The absence of high-conductivity along Archean sutures appears to be global in nature and related to reduced continental freeboard in the Archean which limited continental weathering and the delivery of carbon-rich sediments to the seafloor. Although the entire Wyoming Province has been proposed to have undergone lithospheric modification that lessened its stability, the resistivity model suggests a thick lithospheric root remains in place except along its western margin. These results suggest that Archean cratons may be more resistant to lithospheric modification by influx of heat and fluids associated with extension and plumes than previously thought, and that metasomatism does not necessarily weaken the lithosphere and set a craton on the path to destruction.
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Cyanobacterial harmful algal blooms (CyanoHABs) can lead to a decrease in water quality and affect many of the recreational and ecological benefits of parks that include lakes. The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) is a State agency within the New York State Executive Department charged with the operation of State parks and historic sites. Many New York State parks include lakes or other freshwater bodies, which can be susceptible to CyanoHABs. The OPRHP faces difficult decisions regarding prevention of and response to CyanoHABs. The U.S. Geological Survey partnered with the OPRHP and the New York State Department of Environmental Conservation to develop a structured decision-making template for managing CyanoHABs in OPRHP parks. Two parks, Moreau Lake State Park and Rockland Lake State Park, served as case studies to motivate and test the template. This report describes how the principles of structured decision making can be used to navigate the challenges associated with managing CyanoHABs in OPRHP parks. Management objectives and strategies for CyanoHABs in parks are described, strategies to evaluate consequences and manage tradeoffs are discussed, and potential challenges to the implementation of preferred alternatives are considered. General guidance is provided so the OPRHP can undertake the structured decision-making process for CyanoHABs in any of its parks. In addition, this report represents the first effort to create a strategy for applying decision analysis tools to the complex natural resource challenge of CyanoHAB mitigation and management. The case studies and template are intended to serve as an example that natural resource managers faced with CyanoHABs challenges can use to inform their decision-making processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225053","collaboration":"Prepared in cooperation with the New York State Office of Parks, Recreation and Historic Preservation and the New York State Department of Environmental Conservation","usgsCitation":"Graham, J.L., Cebada Mora, G.M., Gorney, R.M., Ball, L.C., Mengelt, C., and Runge, M.C., 2022, A structured decision-making framework for managing cyanobacterial harmful algal blooms in New York State parks: U.S. Geological Survey Scientific Investigations Report 2022–5053, 22 p., 3 app., https://doi.org/10.3133/sir20225053.","productDescription":"Report: vi, 22 p.; 3 Appendixes; Template","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122386","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":402732,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5053/sir20225053_appendix2.pdf","text":"Appendix 2","size":"2.00 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- A Structured Decision Analysis for Prevention, Management, and Mitigation of Cyanobacterial Harmful Algal Blooms at Moreau Lake State Park, New York—Results From a Structured Decision Making Workshop, February 10–14, 2020, Troy, New York"},{"id":402733,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5053/sir20225053_appendix3.pdf","text":"Appendix 3","size":"1.91 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- A Structured Decision Analysis for Management and Mitigation of Cyanobacterial Harmful Algal Blooms at Rockland Lake State Park—Results From a Structured Decision-Making Workshop, February 10–14, 2020, Troy, New York"},{"id":402734,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2022/5053/sir20225053_sdm_cyanohabs_template.docx","text":"Template","size":"27.9 KB","linkHelpText":"- Blank template for a structured decision-making report on cyanobacterial harmful algal blooms"},{"id":402736,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5053/images/"},{"id":402730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5053/coverthb2.jpg"},{"id":402731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5053/sir20225053.pdf","text":"Report","size":"2.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5053"},{"id":402735,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5053/sir20225053.XML"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
We present here a comprehensive record of Miocene terrestrial ecosystems from exposures of the Monterey Formation along the Naples coastal bluffs, west of Santa Barbara, California. Constrained by an updated chronology, pollen analyses of 28 samples deposited between 18 and 6 Ma reflect the demise of mesophytic taxa that grew in a warm, wet environment during the late early and early middle Miocene and the development of a summer-dry/winter-wet Mediterranean climate during the late Miocene. Broadleaf tree pollen from mesophytic woodlands and forests now found in the southeastern United States and China (Liquidambar, Tilia, Ulmus, Carya) characterized the Miocene climatic optimum (16.9–14.7 Ma), the middle Miocene climate transition (14.7–13.8 Ma), and the interval up to ca. 13.0 Ma. Subsequently, during the late middle to early late Miocene, between 13.3 and 9.0 Ma, oak woodlands and herbs (Asteraceae, Amaranthaceae, Poaceae) from beach scrub and chaparral increased as ocean temperatures cooled and the climate became drier. Between ca. 8.9 and 7.6 Ma, pine increased mostly at the expense of oak (Quercus) and herbs, suggesting a period of increasing precipitation. During the latest Miocene (7.5–6.0 Ma), an increase of herb-dominated ecosystems (chaparral, coastal scrub) at the expense of pine reflects the full development of a summer-dry/winter-wet climate in coastal southern California.
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These deviations are strongly correlated with the thickness of Mesozoic and younger syn- and post-rift sediments. With the recent incorporation of deep basin depth measurements in the U.S. Geological Survey National Seismic Hazard Model for select regions in the western United States, we move toward a similar analysis in the greater Coastal Plains region by constructing a sediment thickness model and considering three new site response models conditioned on sediment thickness. As of the preparation of this conference paper, we have performed a preliminary evaluation of the Chapman and Guo model and find that the predicted ratio between pseudo-spectral accelerations for the Coastal Plains relative to the continental interior are broadly consistent with our independent dataset.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th National Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Salt Lake City, UT","conferenceLocation":"June 27–30, 2022","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Boyd, O.S., Churchwell, D.H., Moschetti, M.P., Thompson, E.M., Pratt, T.L., Chapman, M.C., and Rezaeian, S., 2022, Sediment thickness and ground motion site amplification along the United States Atlantic and Gulf Coastal Plains, in Proceedings of the 12th National Conference on Earthquake Engineering, June 27–30, 2022, Salt Lake City, UT, 6 p.","productDescription":"6 p.","ipdsId":"IP-136161","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":420979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":420967,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://eeri.org/what-we-offer/digital-library/?lid=12779"}],"country":"United States","otherGeospatial":"Atlantic and Gulf Coastal Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.25291505794041,\n 43.11551051121873\n ],\n [\n -80.7330253585369,\n 38.81228650769893\n ],\n [\n -84.44447416548951,\n 33.14812360280486\n ],\n [\n -90.51541198905872,\n 32.66981507090745\n ],\n [\n -87.98950571879871,\n 36.83888863435001\n ],\n [\n -92.75088448245776,\n 37.718360164733625\n ],\n [\n -94.7144857219464,\n 33.18291348028001\n ],\n [\n -101.29229173245739,\n 31.66705056990334\n ],\n [\n -104.94537104234047,\n 30.78609372642758\n ],\n [\n -103.26634804178553,\n 28.863003064829684\n ],\n [\n -94.99069560298432,\n 21.87168982289009\n ],\n [\n -78.88377589393184,\n 23.789097057555523\n ],\n [\n -67.25291505794041,\n 43.11551051121873\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":883494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Churchwell, David Henry 0000-0003-0273-0536","orcid":"https://orcid.org/0000-0003-0273-0536","contributorId":259305,"corporation":false,"usgs":true,"family":"Churchwell","given":"David","email":"","middleInitial":"Henry","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883498,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Martin C.","contributorId":139348,"corporation":false,"usgs":false,"family":"Chapman","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":883499,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883500,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237619,"text":"70237619 - 2022 - Using in situ/ex situ research collaborations to support polar bear conservation","interactions":[],"lastModifiedDate":"2022-10-14T15:52:40.607161","indexId":"70237619","displayToPublicDate":"2022-07-01T10:40:05","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"107","title":"Using in situ/ex situ research collaborations to support polar bear conservation","docAbstract":"A warming Arctic threatens the long-term persistence of polar bears (Ursus maritimus) in the wild. Historically, little collaboration existed between the in situ and ex situ polar bear scientific communities. However, for the past decade, zoo professionals, government agencies, and non-governmental organizations (NGO’s) have partnered to leverage resources and expertise with the goal of addressing science needs and enhancing polar bear conservation efforts. We discuss examples where collaborative efforts have addressed polar bear research needs and highlight opportunities for future integrated in situ and ex situ research.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fowler's zoo and wild animal medicine current therapy","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","usgsCitation":"Meyerson, R., and Atwood, T.C., 2022, Using in situ/ex situ research collaborations to support polar bear conservation, chap. 107 of Fowler's zoo and wild animal medicine current therapy, v. 10.","ipdsId":"IP-127574","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":408329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":408328,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/fowler's-zoo-and-wild-animal-medicine-current-therapyvolume-10/978-0-323-82852-9"}],"volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Miller, Eric","contributorId":294470,"corporation":false,"usgs":false,"family":"Miller","given":"Eric","affiliations":[],"preferred":false,"id":854700,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lamberski, Nadine","contributorId":259228,"corporation":false,"usgs":false,"family":"Lamberski","given":"Nadine","affiliations":[{"id":38792,"text":"San Diego Zoo Global","active":true,"usgs":false}],"preferred":false,"id":854701,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Calle, Paul","contributorId":294471,"corporation":false,"usgs":false,"family":"Calle","given":"Paul","email":"","affiliations":[{"id":47877,"text":"Wildlife Conservation Society, Bronx, NY, USA","active":true,"usgs":false}],"preferred":false,"id":854702,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Meyerson, Randi","contributorId":146389,"corporation":false,"usgs":false,"family":"Meyerson","given":"Randi","email":"","affiliations":[{"id":16683,"text":"Toledo Zoo, Toledo, OH","active":true,"usgs":false}],"preferred":false,"id":854666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":854667,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236819,"text":"70236819 - 2022 - Egg retention in wild-caught Python bivittatus in the Greater Everglades Ecosystem, Florida, USA","interactions":[],"lastModifiedDate":"2022-09-19T15:52:06.211731","indexId":"70236819","displayToPublicDate":"2022-07-01T10:39:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1895,"text":"Herpetological Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Egg retention in wild-caught Python bivittatus in the Greater Everglades Ecosystem, Florida, USA","title":"Egg retention in wild-caught Python bivittatus in the Greater Everglades Ecosystem, Florida, USA","docAbstract":"Retention of eggs in oviducts beyond the normal oviposition period is a common problem for captive reptiles, but the occurrence of egg retention in wild populations is largely unknown. The Burmese python (Python [molurus] bivittatus; Kühl 1820) is an oviparous snake native to south-eastern Asia that is now established in southern Florida. From 2011–2019, invasive Burmese pythons were opportunistically removed from Everglades National Park and Big Cypress National Preserve, humanely euthanised, and necropsied to determine reproductive condition. A total of 258 females of reproductive size were found to exhibit various stages of oviposition which generally aligned with purported annual reproductive timing. However, we encountered five pythons during the post-ovulatory period (Aug–Feb) showing signs of recent oviposition with retained eggs. Most of these cases comprised a small number of retained eggs, likely representing some portion of the total clutch. Because this condition is nearly absent in wild animal literature, our observations suggest retained eggs in wild snakes may be more common than previously assumed, possibly slowing or otherwise impacting population growth. However, we recognise that for an invasive species like the Burmese python in Florida, the egg retention rate may be higher in the non-native range compared to the native range due to maladaptation to novel habitats or environmental conditions. Additional research is needed to determine the exact causes of egg retention and investigate the implications for population dynamics on this and other snake species.
","language":"English","publisher":"British Herpetological Society","doi":"10.33256/32.3.109113","usgsCitation":"Anderson, G.E., Ridgley, F.N., Josimovich, J.M., Reed, R., Falk, B., Yackel Adams, A.A., and Currylow, A.F., 2022, Egg retention in wild-caught Python bivittatus in the Greater Everglades Ecosystem, Florida, USA: Herpetological Journal, v. 32, p. 109-113, https://doi.org/10.33256/32.3.109113.","productDescription":"5 p.","startPage":"109","endPage":"113","ipdsId":"IP-124676","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":447252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.33256/32.3.109113","text":"Publisher Index Page"},{"id":406973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.771240234375,\n 25.075648445630527\n ],\n [\n -80.343017578125,\n 25.075648445630527\n ],\n [\n -80.343017578125,\n 26.657277674217585\n ],\n [\n -81.771240234375,\n 26.657277674217585\n ],\n [\n -81.771240234375,\n 25.075648445630527\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","noUsgsAuthors":false,"publicationDate":"2022-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":852256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ridgley, Frank N.","contributorId":296701,"corporation":false,"usgs":false,"family":"Ridgley","given":"Frank","email":"","middleInitial":"N.","affiliations":[{"id":54678,"text":"Zoo Miami, Conservation and Research Department, 12400 SW 152nd St., Miami, Florida 33177, USA","active":true,"usgs":false}],"preferred":false,"id":852257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Josimovich, Jillian Maureen 0000-0002-7523-3496 jjosimovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7523-3496","contributorId":257058,"corporation":false,"usgs":true,"family":"Josimovich","given":"Jillian","email":"jjosimovich@usgs.gov","middleInitial":"Maureen","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":852258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":852259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falk, Bryan G.","contributorId":296702,"corporation":false,"usgs":false,"family":"Falk","given":"Bryan G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":852260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":852261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":852262,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270792,"text":"70270792 - 2022 - Standard operating protocol for mark and recapture monitoring of Brook Floater in streams","interactions":[],"lastModifiedDate":"2025-08-25T15:33:06.25202","indexId":"70270792","displayToPublicDate":"2022-07-01T10:32:28","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-142-2022","title":"Standard operating protocol for mark and recapture monitoring of Brook Floater in streams","docAbstract":"The Brook Floater (Alasmidonta varicosa) is a small (<100 mm) freshwater mussel (Family: Unionidae) found in streams of the eastern United States (U.S.) (Nedeau 2008). While there has been limited effort to document the status of Brook Floater across its range, there is evidence of Brook Floater range contraction and declining local abundances over recent decades (Wicklow et al. 2017, NatureServe 2021). Brook Floater is a Species of Greatest Conservation Need (SGCN) in 15 states (94% of range); listed as endangered, threatened, or special concern in nearly every state and province where it still occurs; and has been extirpated from two states (Rhode Island and Delaware). Brook Floater was petitioned for Federal listing under the U.S. Endangered Species Act; however, the listing was determined not to be warranted (U.S. FWS 2019), although it remains a Regional SGCN of very high concern in U.S. Fish & Wildlife Service (U.S. FWS) Regions 5 (Terwilliger 2015) and 4 (SEAFWA-WDC 2019) and is an At-Risk Species in U.S. FWS Region 5.
A critical component of understanding population declines is site-specific information about population density and demographics (e.g., growth, age structure) to assess population viability. This information had previously only been collected for a few populations of Brook Floater (e.g., Massachusetts Division of Fisheries & Wildlife, North Carolina Wildlife Resources Commission) and methods to collect these data varied from state to state, thus limiting comparisons across the range. In 2016, a competitive State Wildlife Grant (SWG) was awarded to develop a standardized monitoring technique that will aid in understanding differences in population viability across its range and assess changes in populations through time. The protocol described in this report was subsequently developed and tested by Massachusetts and Maine (2 sites in each state) and revised based on field experiences. Data collected using this protocol will allow for state managers to make informed decisions about management actions for Brook Floater.
Monitoring approaches are ideally designed to meet management objectives. Management objectives are specific, quantifiable outcomes that reflect the values of the decision makers and relate directly to the management decisions (Conroy and Peterson 2013). Lack of well-defined objectives hinders success of conservation and management actions because there are undefined metrics to determine when the objectives have been met (Yoccoz et al. 2001, Nichols and Thompson 2006). While monitoring to understand a system (i.e., status and trends; Reynolds et al. 2016) provides baseline information for developing management recommendations in the future, Nichols and Thompson (2006) criticize status and trends monitoring because of time lags associated with conservation and the costs and resource availability needed for surveillance, among other reasons. State partners in the Brook Floater SWG have a variety of different monitoring objectives (e.g., abundance/density, survival, recruitment) that depend on the population sizes and demographics.
There are many approaches for estimating population parameters such as density, age structure, recruitment, and growth rates. For example, presence/absence (i.e., multistate models), counts (i.e., multi-state models or Dail-Madsen model; Dail and Madsen 2011), and capture mark-recapture (CMR; e.g. Cormack-Jolly-Seber models; Lindberg and Rexstad 2002) are all approaches for assessing population status and viability.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css67282137","usgsCitation":"Sterrett, S., Roy, A.H., Hazelton, P., Swartz, B., Nedeau, E., Carmignani, J., and Skorupa, A., 2022, Standard operating protocol for mark and recapture monitoring of Brook Floater in streams: Cooperator Science Series CSS-142-2022, https://doi.org/10.3996/css67282137.","ipdsId":"IP-132939","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Sterrett, Sean","contributorId":360459,"corporation":false,"usgs":false,"family":"Sterrett","given":"Sean","affiliations":[{"id":69149,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":947082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":947081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazelton, Peter","contributorId":360462,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":947083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swartz, Beth","contributorId":360463,"corporation":false,"usgs":false,"family":"Swartz","given":"Beth","affiliations":[{"id":86011,"text":"Maine Department of Inland Fisheries & Wildlife","active":true,"usgs":false}],"preferred":false,"id":947084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nedeau, Ethan","contributorId":360464,"corporation":false,"usgs":false,"family":"Nedeau","given":"Ethan","affiliations":[{"id":86012,"text":"Biodrawversity","active":true,"usgs":false}],"preferred":false,"id":947085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carmignani, Jason","contributorId":360465,"corporation":false,"usgs":false,"family":"Carmignani","given":"Jason","affiliations":[{"id":86008,"text":"Natural Heritage and Endangered Species Program","active":true,"usgs":false}],"preferred":false,"id":947086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skorupa, Ayla","contributorId":360466,"corporation":false,"usgs":false,"family":"Skorupa","given":"Ayla","affiliations":[{"id":69149,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":947087,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237200,"text":"70237200 - 2022 - Modelagem de qualidade da agua: Aplicação do SPARROW","interactions":[],"lastModifiedDate":"2022-10-05T15:34:58.137568","indexId":"70237200","displayToPublicDate":"2022-07-01T10:18:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Modelagem de qualidade da agua: Aplicação do SPARROW","docAbstract":"No abstract available.
","language":"Portuguese","publisher":"Agência Nacional de Águas e Saneamento Básico","usgsCitation":"Hadler Troger, F., Ayrimoraes Soares, S.R., Leite Cavalcanti, D., de Souza, M.L., Restivo, D., and Miller, O.L., 2022, Modelagem de qualidade da agua: Aplicação do SPARROW, 44 p.","productDescription":"44 p.","ipdsId":"IP-134335","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":407964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407963,"rank":1,"type":{"id":15,"text":"Index 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Exposure and perennial grass sensitivity","interactions":[],"lastModifiedDate":"2023-08-10T14:56:47.596456","indexId":"70229969","displayToPublicDate":"2022-07-01T09:46:28","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2022/2432","title":"Southeast Utah Group climate and drought adaptation report: Exposure and perennial grass sensitivity","docAbstract":"National Park Service (NPS) managers face growing challenges resulting from the effects of climate change. In particular, as temperatures rise in coming decades, natural resource management in the western United States must cope with expectations for elevated severity and frequency of droughts. These challenges are particularly pronounced for vegetation managers in dryland environments. Developing adaptive strategies requires specific information about the expected magnitude of change in climate and drought conditions as well as insights into how those changes will affect important vegetation resources. This report describes research focused on Southeast Utah Group (SEUG) park units designed to provide information about exposure and sensitivity of perennial grasses to aridification. Analyses at larger regional scales are also reported for context and comparison.
This report is a product of an ongoing climate adaptation collaboration between the U.S. Geological Survey (USGS), NPS, and Northern Arizona University. The study it summarizes contributes quantitative ingredients for vulnerability assessments that are needed in the Climate-Smart Conservation framework. As such, the results informed a series of climate adaptation workshops conducted between 2018 and 2021 for Colorado Plateau scientists and managers. This is a giant step forward in science-informed management. The information in this report can be used to craft management strategies that can be implemented at the right place and time for individual species of concern.
","language":"English","publisher":"National Park Service","doi":"10.36967/2293951","usgsCitation":"Bradford, J., Havrilla, C., Hartsell, J.A., Schlaepfer, D.R., McCormick, M.L., Munson, S.M., Yackulic, C., Fisk, T.T., Thoma, D., Perkins, D., Witwicki, D.L., VanScoyoc, M., Duniway, M.C., and Reed, S., 2022, Southeast Utah Group climate and drought adaptation report: Exposure and perennial grass sensitivity: Natural Resource Report 2022/2432, x, 158 p., https://doi.org/10.36967/2293951.","productDescription":"x, 158 p.","ipdsId":"IP-135759","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":419709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Arches National Park, Canyonlands National Park, Colorado Plateau, Hovenweep National Monument, Natural Bridges National Monument","geographicExtents":"{\n \"type\": 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The Smallmouth Bass Micropterus dolomieu is an example of a fish that has been introduced globally, often spreads after introduction, and has substantial predatory impacts on fish assemblages. Nonnative Smallmouth Bass in the free-flowing Yellowstone River, Montana, have expanded from warmer, downstream sections of river into colder, upstream sections containing socio-economically valuable trout fisheries. We sought insight into mechanisms controlling upstream spread by evaluating whether progressively colder upstream climates physiologically constrained successful recruitment by limiting age-0 growth and preventing overwinter survival (i.e., population establishment). We documented the phenology, growth, and overwinter survival of age-0 Smallmouth Bass across a temperature gradient leading to their upstream extent in the Yellowstone River. The upstream extent of population establishment did not appear limited by water temperature alone. Age-0 body size at the onset of winter did not differ significantly between colder, upstream reaches and warmer, downstream reaches. Instead, the earlier hatch timing exhibited by some age-0 individuals in upstream sections allowed them to experience longer growing seasons than many individuals in downstream sections. This counter-intuitive hatching phenology mediated much of the expected decreases in growth in colder, upstream climates. Furthermore, evidence of successful overwinter survival and simulations of age-0 starvation mortality indicated that age-0 individuals at the upstream extent of their distribution successfully recruited to the age-1 year-class during four consecutive years. However, age-0 individuals were rare or absent throughout the uppermost upstream distribution of adults, suggesting that something other than temperature limits or discourages reproduction farther upstream. Taken together, our results suggest that Smallmouth Bass have not yet reached the thermal limit of their upstream distribution in the Yellowstone River and that future spread may challenge fisheries managers tasked with management of coldwater trout fisheries in this river.
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It then introduces a new form of spatial analytics—geospatial artificial intelligence (GeoAI)—and describes the advantages of this new strategy in big data analytics and data-driven discovery. Finally, a convergent spatial analytical framework is suggested as a potential future pathway for spatial analysis.
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The degree to which clastic sediment is mixed and homogenized during transfer across broad shelves has important implications for understanding deep-sea detrital records. Wide continental shelves are thought to act as capacitors characterized by transient sediment storage during sea level rise and sediment remobilization during sea level fall. This study attempts to test the hypothesis that sea level lowstand yields more efficient and direct sediment transfer from fluvial sources to deep-sea sinks compared to highstand when sediment is sequestered and mixed on the shelf. We test this by evaluating U-Pb and Lu-Hf detrital zircon provenance trends along the vast Bering Sea shelf and deep-marine Beringian continental margin. We present 5884 U-Pb ages and 402 Lu-Hf analyses from 30 samples to characterize the provenance of modern to Pleistocene sediment across the Bering Sea region. We used both forward and inverse numerical mixture modeling to estimate the abundance of distinct fluvial sources in shelfal and deep-water deposits. These results demonstrate that sediment in the Bering Sea is derived from a mixture of regional fluvial sources, but that the Yukon River is the primary detrital source for sediment throughout the region. Although Yukon River signatures are abundant in all basin samples, the relative proportions of Yukon vs other sources vary spatially across the shelf. A comparison of Holocene and surficial sediment with Pleistocene deposits shows that sediment across the shelf and in the deep-sea remains well-mixed between climate states. Thus, detrital provenance signatures in deep-marine deposits outward of broad transfer zones are likely to represent mixtures of fluvial sources regardless of sea level.","language":"English","publisher":"Wiley","doi":"10.1002/dep2.203","usgsCitation":"Malkowski, M., Johnstone, S., Sharman, G.R., White, C.J., Scheirer, D.S., and Barth, G., 2022, Continental shelves as detrital mixers: U-Pb and Lu-Hf detrital zircon provenance of the Pleistocene–Holocene Bering Sea and its margins: The Depositional Record, v. 8, no. 3, p. 1008-1030, https://doi.org/10.1002/dep2.203.","productDescription":"23 p.","startPage":"1008","endPage":"1030","ipdsId":"IP-130161","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447258,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/dep2.203","text":"Publisher Index Page"},{"id":435789,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FUXON3","text":"USGS data release","linkHelpText":"Detrital zircon geochronology and geochemistry data from the seafloor of the Bering Sea and adjacent river systems"},{"id":402821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -179.9,\n 50\n ],\n [\n -150,\n 50\n ],\n [\n -150,\n 68\n ],\n [\n -179.9,\n 68\n ],\n [\n -179.9,\n 50\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 160,\n 50\n ],\n [\n 179.9,\n 50\n ],\n [\n 179.9,\n 66\n ],\n [\n 160,\n 66\n ],\n [\n 160,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Malkowski, Matthew A.","contributorId":221753,"corporation":false,"usgs":false,"family":"Malkowski","given":"Matthew A.","affiliations":[{"id":40415,"text":". 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","language":"English","publisher":"The Wildlife Society","usgsCitation":"Atwood, T.C., 2022, The ice don’t lie: The Wildlife Professional, p. 39-41.","productDescription":"3 p.","startPage":"39","endPage":"41","ipdsId":"IP-139708","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":403471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403453,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.org/the-july-august-issue-of-the-wildlife-professional-5/"}],"country":"Canada, United States","otherGeospatial":"southern Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.609375,\n 69.41124235697256\n ],\n [\n -123.04687499999999,\n 69.41124235697256\n ],\n [\n -123.04687499999999,\n 73.32785809840696\n ],\n [\n -159.609375,\n 73.32785809840696\n ],\n [\n -159.609375,\n 69.41124235697256\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":846311,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248034,"text":"70248034 - 2022 - New craters on Mars: An updated catalog","interactions":[],"lastModifiedDate":"2023-09-01T13:00:34.786362","indexId":"70248034","displayToPublicDate":"2022-07-01T07:53:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"New craters on Mars: An updated catalog","docAbstract":"We present a catalog of new impacts on Mars. These craters formed in the last few decades, constrained with repeat orbital imaging. Crater diameters range from 58 m down to <1 m. For each impact, we report whether it formed a single crater or a cluster (58% clusters); albedo features of the blast zone (88% halos; 64% linear rays; 10% arcuate rays; majority dark-toned; 4% light-toned; 14% dual-toned); and exposures of ice (4% definite; 2% possible). We find no trends in the occurrences of clusters with latitude, elevation, or impact size. Albedo features do not depend on atmospheric fragmentation. Halos are more prevalent at lower elevations, indicating an atmospheric pressure dependence; and around smaller impacts, which could be an observational bias. Linear rays are more likely to form from larger impacts into more consolidated material and may be enhanced by lower atmospheric pressure at higher elevations. Light- and dual-toned blast zones occur in specific regions and more commonly around larger impacts, indicating excavation of compositionally distinct material. Surfaces covered with bright dust lacking cohesion are favored to form detectable surface features. The slope of the cumulative size frequency distribution for this data set is 2.2 for diameters >8 m (differential slope 2.9), significantly shallower than the slope of new lunar craters. We believe that no systematic biases exist in the Martian data set sufficient to explain the discrepancy. This catalog is complete at the time of writing, although observational biases exist, and new discoveries continue.
","language":"English","publisher":"Wiley","doi":"10.1029/2021JE007145","usgsCitation":"Daubar, I.J., Dundas, C., McEwen, A.S., Gao, A., Wexler, D., Piqueux, S., Collins, G.S., Miljkovic, K., Neidhart, T., Eschenfelder, J., Bart, G.D., Wagstaff, K.L., Doran, G., Posiolova, L., Malin, M.C., Speth, G., Susko, D., and Werynski, A., 2022, New craters on Mars: An updated catalog: Journal of Geophysical Research E: Planets, v. 127, no. 7, e2021JE007145, 21 p., https://doi.org/10.1029/2021JE007145.","productDescription":"e2021JE007145, 21 p.","ipdsId":"IP-135587","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":447259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021je007145","text":"Publisher Index 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Assessing the variability of composition and structure in floodplain forest ecosystems across spatial scales in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2022-07-12T12:27:03.988899","indexId":"70232695","displayToPublicDate":"2022-07-01T07:23:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"What is a stand? Assessing the variability of composition and structure in floodplain forest ecosystems across spatial scales in the Upper Mississippi River","docAbstract":"The forest stand typically represents relatively homogenous forest conditions; the forest stand is generally the unit at which forest attributes are assessed, summarized, and subsequently managed. However, some ecosystems, such as the floodplain forests of the Upper Mississippi River (UMR), can exhibit high variability at fine spatial scales that can confound prescription development, implementation, and ultimate success of stand-level management actions. Here we assess how forest composition and structure vary within and across stand management units on the UMR and test at what spatial scale environmental variables relate to forest characteristics. We found that plot-level measures of composition, structure, and diversity were not well represented by site-level averages of these values. When basal area of all overstory species was combined, this variable was more closely related to “site” than to any of the environmental variables, but when analyzed by species, within-plot topographic variation (“microtopography”) was a significant positive predictor for both importance values of an individual species (swamp white oak (Quercus bicolor Willd.)) as well as importance value of a specific group of species (oaks (Quercus spp.), bitternut hickory (Carya cordiformis (Wangenh.) K. Koch), hackberry (Celtis occidentalis L.), and American basswood (Tilia americana L.)). This work highlights the challenges of using average stand conditions to summarize complex or heterogeneous systems and the need for flexibility and relaxed assumptions in defining management units in these forests.
There have been over 507 million cases of COVID-19, the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in 6 million deaths globally. Wastewater surveillance has emerged as a valuable tool in understanding SARS-CoV-2 burden in communities. The National Wastewater Surveillance System (NWSS) partnered with the United States Geological Survey (USGS) to implement a high-frequency sampling program. This report describes basic surveillance and sampling statistics as well as a comparison of SARS-CoV-2 trends between high-frequency sampling 3–5 times per week, referred to as USGS samples, and routine sampling 1–2 times per week, referred to as NWSS samples. USGS samples provided a more nuanced impression of the changes in wastewater trends, which could be important in emergency response situations. Despite the rapid implementation time frame, USGS samples had similar data quality and testing turnaround times as NWSS samples. Ensuring there is a reliable sample collection and testing plan before an emergency arises will aid in the rapid implementation of a high-frequency sampling approach. High-frequency sampling requires a constant flow of information and supplies throughout sample collection, testing, analysis, and data sharing. High-frequency sampling may be a useful approach for increased resolution of disease trends in emergency response.
There exists over a century of instrumental seismic data; however, most seismograms recorded before the 1980s are only available in analog form. Although analog seismograms are of great value, they are underutilized due to the difficulties of making quantitative measurements on the original media and in converting them to digital time series. In this study, we present an alternative workflow, based on deep learning, to reconstruct an earthquake catalog from images of analog data without conversion to vector time series. We trained a convolutional neural network—DevelNet, using synthetic analog data to detect earthquakes on scanned multichannel Develocorder film images. We then developed an image‐based processing workflow to measure arrival times, locate, and determine the magnitudes of earthquakes in the data. We demonstrate the performance of this approach on two years of continuous Develocorder film recordings from the Rangely earthquake control experiment in the mid‐1970s. Our approach detects twice the number of events reported in the original catalog (Raleigh et al., 1976). This demonstrates that DevelNet efficiently detects earthquakes from Develocorder film scans, performs consistently over time, and is robust to changes in network geometry. Our locations generally agree with the original study, although the automatically measured arrival times are less precise than manual reading, leading to increased location scatter. Our automatic workflow of Develocorder films rivals the performance of skilled analysts in earthquake detection, but with minimal human intervention. This image‐based processing offers a new approach for effectively and efficiently extracting earthquake information from analog seismic data.
The distribution of groundwater age is useful for evaluating the susceptibility and sustainability of groundwater resources. Here, we compute the aquifer-scale cumulative distribution function to characterize the age distribution for 21 Principal Aquifers that account for ~80% of public-supply pumping in the United States. The aquifer-scale cumulative distribution function for each Principal Aquifer was derived from an ensemble of modeled age distributions (~60 samples per aquifer) based on multiple tracers: tritium, tritiogenic helium-3, sulfur hexafluoride, chlorofluorocarbons, carbon-14, and radiogenic helium-4. Nationally, the groundwater is 38% Anthropocene (since 1953), 34% Holocene (75 – 11,800 years ago), and 28% Pleistocene (>11,800 years ago). The Anthropocene fraction ranges from <5 to 100%, indicating a wide range in susceptibility to land-surface contamination. The Pleistocene fraction of groundwater exceeds 50% in 7 eastern aquifers that are predominately confined. The Holocene fraction of groundwater exceeds 50% in 5 western aquifers that are predominately unconfined. The sustainability of pumping from these Principal Aquifers depends on rates of recharge and release of groundwater stored in fine-grained layers.
In 2018–20, the U.S. Geological Survey, in cooperation with Upper Black Squirrel Creek Ground Water Management District, sampled 48 wells for Phase III of a multiphase plan investigating groundwater quality in the alluvial aquifer of the Upper Black Squirrel Creek Basin (UBSB), El Paso County, Colorado. Results for samples collected from October to December each year were used to assess spatial and temporal changes in groundwater quality and to differentiate sources of nitrate. Groundwater was predominantly classified as mixed-cation and mixed-anion water type in the aquifer, with variable chemistry along the periphery. Concentrations of constituents in groundwater were generally less than regulatory standards, except for nitrate in four wells. Isotopes of nitrogen and oxygen in nitrate identified four different potential sources or processes affecting nitrate in the alluvial aquifer: naturally occurring nitrate from soils, nitrate from animal and (or) human waste, and an unknown source, along with evidence of denitrification. Pharmaceutical compounds and personal-care products were detected in seven wells, with three wells having multiple detections. Stable isotopes of water indicated variability in seasonality of recharge throughout the UBSB alluvial aquifer. Nitrate concentrations from the 1984 study and the 1996 study were compared to the more recent concentrations in the 2013 study and the 2018–20 study. The northern one-third of the UBSB alluvial aquifer had a statistically significant increase in nitrate concentration from the 2013 study to the 2018–20 study, but no change was shown from the 1984 study to the 1996 study. The opposite was found true for the southern two-thirds of the UBSB alluvial aquifer with no statistically significant difference in nitrate concentration from the 2013 study to the 2018–20 study. Analysis of temporal changes indicated an increase in median and maximum nitrate concentrations from the 2013 study to the 2018–20 study throughout the UBSB alluvial aquifer. Continued sampling of wells in the UBSB would be beneficial to better determine temporal changes in groundwater quality, characterize human effects on water quality, and understand characteristics of the alluvial aquifer pertaining to sustainability of the resource.
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U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Many may recall “Take Me Home, Country Roads,” made famous by John Denver, leads with the lyric “almost heaven, West Virginia, Blue Ridge Mountains, Shenandoah River.” The descriptors are apt. Nicknamed the “Mountain State,” West Virginia inspires thoughts of coal mining or logging in the Appalachian Mountains and valleys, or the leaping trout in the winding waters of New River Gorge National Park & Reserve.
West Virginia is second only to Wyoming in coal production nationwide. Its mines produced more than 67 million tons of coal in 2020. Logging pumped about $3.4 billion into the State’s economy in 2019; tourist spending added another $4.6 billion.
Those industries are key for West Virginia, but agriculture and fisheries also play a role in the State's economic fortunes. Peaches and apples are major drivers of food production, as are beef and poultry. Trout, meanwhile, are caught and sold commercially, and are stocked throughout the State's rivers for local and visiting anglers.
Scientists, land managers, and others use imagery from the U.S. Geological Survey Landsat satellite program's deep historical archive to better understand and manage West Virginia’s storied forests, fields, mountains, and foothills.
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Virginia\",\"nation\":\"USA \"}}]}","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Cyanobacterial blooms are an issue drawing increasing concern in freshwater lakes and reservoirs in the United States due to the real and sometimes perceived harms they can cause through cyanotoxin production or other effects. These types of blooms are often referred to as cyanobacterial harmful algal blooms (cyanoHABs). Cyanotoxin exposure can potentially lead to human health effects through recreation and consumption of drinking water and may impact fisheries, wildlife, domestic pets, and livestock. Characterizing the societal impacts of cyanotoxin production, exposure, and effects and estimating the potential value of information of an early warning system can inform and support freshwater lake and reservoir management decisions and future research directions. A Bayesian decision tree analysis was utilized to identify uses, users, and benefits of the information provided by this research. Specifically, the potential value related to a cyanoHAB early warning system, based on potential toxicity, was analyzed that would provide information two additional days earlier relative to cyanoHAB toxicity. The evaluation considers the application of this information for freshwater lake management - whether or not to post an advisory or warning to avoid recreational water contact. The model was parameterized with data from the state of Kansas and the value of avoided foregone recreation and avoided health effects was derived. The estimated annual value of information ranges between \\$565 thousand to \\$2.3 million (2018 United States Dollars (USD)) for the state of Kansas alone based on provided assumptions. The results demonstrate a lower bound of the value of a cyanoHAB early warning system and suggest additional research to understand how the use and value of this information could support research prioritization and further illustrate the return on research investment. This analysis does not incorporate the full suite of potential societal costs that may be associated with a cyanoHAB event such as drinking water treatment, impacts to irrigation, or power generation.
Atmospheric dust deposited to snow cover (dust-on-snow) diminishes snow-surface albedo (SSA) to result in early onset and accelerated rate of melting, effects that challenge management of downstream water resources. During ongoing investigations to identify the light-energy absorbing dust particles most responsible for diminished SSA in the Upper Colorado River Basin of the Colorado Rocky Mountains, we found microplastic particles, which are defined as those less than 5 millimeters in any dimension. In each of the 38 samples that represented the last remaining dust layer during melt seasons of 2013–16, microplastics were identified by size, shape, and color, and their relative amounts were visually estimated using stereomicroscopy. Considering the remote, high-elevation settings of the sample sites, the microplastic particles must have been deposited from the atmosphere. The possible role of microplastics for diminishing SSA of snow cover in the Upper Colorado River Basin may be linked to the solar-energy absorptive properties of polymers and is the subject of ongoing investigation.
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\"}}]}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
P.O. Box 25046, Mail Stop 980
Denver, CO 80225