Table Rock Lake was completed in 1958 on the White River in southwestern Missouri and northwestern Arkansas for flood control, hydroelectric power, public water supply, and recreation. The surface area of Table Rock Lake is about 42,400 acres, and about 715 miles of shoreline are at the conservation pool level (915 feet above the North American Vertical Datum of 1988). Sedimentation in reservoirs can result in reduced water storage capacity and a reduction in usable aquatic habitat; therefore, accurate and up-to-date estimates of reservoir water capacity are important for managing pool levels, power generation, recreation, and downstream aquatic habitat. Many of the lakes operated by the U.S. Army Corps of Engineers are periodically surveyed to monitor bathymetric changes that affect water capacity. In October and November 2020, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed one such survey of Table Rock Lake using a multibeam echosounder. The echosounder data were combined with U.S. Geological Survey 1/3 arc-second digital elevation model data and light detection and ranging (lidar) data, where present, to prepare a bathymetric map and a surface area and capacity table up to the flood pool elevation of 931 feet above the North American Vertical Datum of 1988.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3499","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Southwestern Division, Little Rock District","usgsCitation":"Huizinga, R.J., Rivers, B.C., and Richards, J.M., 2022, Bathymetric map and surface area and capacity table for Table Rock Lake near Branson, Missouri, 2020: U.S. Geological Survey Scientific Investigations Map 3499, 3 sheets, https://doi.org/10.3133/sim3499.","productDescription":"3 Sheets: 40.00 × 48.00 inches or smaller; Data Release","onlineOnly":"Y","ipdsId":"IP-137684","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501939,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113828.htm","linkFileType":{"id":5,"text":"html"}},{"id":409452,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sim3499/full","text":"Report"},{"id":409450,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FAFJZG","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for Table Rock Lake near Branson, Missouri, 2020"},{"id":409449,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3499/images"},{"id":409448,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3499/sim3499.XML"},{"id":409447,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet03.pdf","text":"Sheet 3","size":"3.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 3"},{"id":409446,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet02.pdf","text":"Sheet 2","size":"3.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 2"},{"id":409445,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3499/sim3499_sheet01.pdf","text":"Sheet 1","size":"4.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3499 sheet 1"},{"id":409444,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3499/coverthb.jpg"}],"country":"United States","state":"Missouri","city":"Branson","otherGeospatial":"Table Rock Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.46162698604762,\n 36.673080825378904\n ],\n [\n -93.46162698604762,\n 36.45192970827965\n ],\n [\n -93.25043226339268,\n 36.45192970827965\n ],\n [\n -93.25043226339268,\n 36.673080825378904\n ],\n [\n -93.46162698604762,\n 36.673080825378904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Biological nitrogen fixation represents the largest natural flux of new nitrogen (N) into terrestrial ecosystems, providing a critical N source to support net primary productivity of both natural and agricultural systems. When they are common, symbiotic associations between plants and bacteria can add more than 100 kg N ha−1 y−1 to ecosystems. Yet, these associations are uncommon in many terrestrial ecosystems. In most cases, N inputs derive from more cryptic sources, including mutualistic and/or free-living microorganisms in soil, plant litter, decomposing roots and wood, lichens, insects, and mosses, among others. Unfortunately, large gaps remain in the understanding of cryptic N fixation. We conducted a literature review to explore rates, patterns, and controls of cryptic N fixation in both unmanaged and agricultural ecosystems. Our analysis indicates that, as is common with N fixation, rates are highly variable across most cryptic niches, with N inputs in any particular cryptic niche ranging from near zero to more than 20 kg ha−1 y−1. Such large variation underscores the need for more comprehensive measurements of N fixation by organisms not in symbiotic relationships with vascular plants in terrestrial ecosystems, as well as identifying the factors that govern cryptic N fixation rates. We highlight several challenges, opportunities, and priorities in this important research area, and we propose a conceptual model that posits an interacting hierarchy of biophysical and biogeochemical controls over N fixation that should generate valuable new hypotheses and research.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-022-00804-2","usgsCitation":"Cleveland, C., Reis, C., Perakis, S.S., Dynarski, K.A., Batterman, S., Crews, T., Gei, M., Gundale, M.J., Menge, D., Peoples, M., Reed, S., Salmon, V., Soper, F.M., Taylor, B., Turner, M., and Wurzburger, N., 2022, Exploring the role of cryptic nitrogen fixers in terrestrial ecosystems: A frontier in nitrogen cycling research: Ecosystems, v. 25, p. 1653-1669, https://doi.org/10.1007/s10021-022-00804-2.","productDescription":"17 p.","startPage":"1653","endPage":"1669","ipdsId":"IP-123016","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467145,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1899843","text":"External Repository"},{"id":410106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cleveland, Cory","contributorId":257259,"corporation":false,"usgs":false,"family":"Cleveland","given":"Cory","affiliations":[{"id":48908,"text":"U Montana","active":true,"usgs":false}],"preferred":false,"id":858329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reis, Carla R. 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G.","affiliations":[{"id":48124,"text":"Center for Earth System Science, National Institute for Space Research (INPE), Av. dos Astronautas 1758, São José dos Campos, São Paulo 12227-010, Brazil","active":true,"usgs":false}],"preferred":false,"id":858330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dynarski, Katherine A 0000-0001-5101-9666","orcid":"https://orcid.org/0000-0001-5101-9666","contributorId":225403,"corporation":false,"usgs":false,"family":"Dynarski","given":"Katherine","email":"","middleInitial":"A","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":858332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Batterman, Sarah","contributorId":299670,"corporation":false,"usgs":false,"family":"Batterman","given":"Sarah","email":"","affiliations":[{"id":51995,"text":"Cary Inst","active":true,"usgs":false}],"preferred":false,"id":858333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crews, Timothy","contributorId":299673,"corporation":false,"usgs":false,"family":"Crews","given":"Timothy","email":"","affiliations":[{"id":64924,"text":"The Land Institute","active":true,"usgs":false}],"preferred":false,"id":858334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gei, Maga","contributorId":299674,"corporation":false,"usgs":false,"family":"Gei","given":"Maga","email":"","affiliations":[{"id":64927,"text":"Association for Tropical Biology and Conservation","active":true,"usgs":false}],"preferred":false,"id":858335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gundale, Michael J.","contributorId":299675,"corporation":false,"usgs":false,"family":"Gundale","given":"Michael","middleInitial":"J.","affiliations":[{"id":64928,"text":"SLU","active":true,"usgs":false}],"preferred":false,"id":858336,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":858337,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Peoples, Mark","contributorId":257258,"corporation":false,"usgs":false,"family":"Peoples","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":858338,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":858339,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Salmon, Verity","contributorId":298812,"corporation":false,"usgs":false,"family":"Salmon","given":"Verity","email":"","affiliations":[],"preferred":false,"id":858340,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Soper, Fiona M.","contributorId":207085,"corporation":false,"usgs":false,"family":"Soper","given":"Fiona","email":"","middleInitial":"M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":858341,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Taylor, Benton 0000-0002-9834-9192","orcid":"https://orcid.org/0000-0002-9834-9192","contributorId":245071,"corporation":false,"usgs":false,"family":"Taylor","given":"Benton","email":"","affiliations":[{"id":49081,"text":"Smithsonian Environmental Research Center, Edgewater, MD, 21037 USA","active":true,"usgs":false}],"preferred":false,"id":858342,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Turner, Monica","contributorId":193037,"corporation":false,"usgs":false,"family":"Turner","given":"Monica","affiliations":[],"preferred":false,"id":858343,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wurzburger, Nina","contributorId":299676,"corporation":false,"usgs":false,"family":"Wurzburger","given":"Nina","email":"","affiliations":[{"id":27235,"text":"U Georgia","active":true,"usgs":false}],"preferred":false,"id":858344,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70257019,"text":"70257019 - 2022 - Adult white-tailed deer survival in hunted populations on public and private lands","interactions":[],"lastModifiedDate":"2024-09-04T16:01:42.732631","indexId":"70257019","displayToPublicDate":"2022-11-18T08:50:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Adult white-tailed deer survival in hunted populations on public and private lands","docAbstract":"Estimates of sex- and age-specific survival are important for guiding population management decisions for white-tailed deer (Odocoileus virginianus). However, differences in deer survival between public and private lands can exist and, if unaccounted for, may affect wildlife agencies' ability to effectively manage statewide and local deer populations. From 2014 to 2016, we radiocollared and monitored survival of 79 adult white-tailed deer (141 deer-years; 62 male, 79 female) on 2 public and 2 private properties in Alabama, USA. We assessed the effects of sex, age, and landownership type (i.e., public or private) on adult white-tailed deer harvest and survival patterns using an information-theoretic approach. Hunter harvest accounted for 77% of observed mortalities (n = 23/30), but harvest and survival rates varied by sex and age. Harvest and survival were similar between public and private property despite more restrictive hunting regulations for antlered deer on public areas. Similar harvest rates were likely due to self-imposed, quality deer management (QDM) harvest strategies on private land that emulated the effects of a state-mandated antler point restriction (APR) on public land. Our findings indicate survival rates of adult white-tailed deer may be applicable across landownership types where state-mandated harvest regulations with respect to males are more restrictive on public than private property, due to the popularity of QDM by private-land deer hunters. However, where regulations are similar across landownership types (e.g., no state-mandated APR), differences in harvest and survival rates may exist.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.1391","usgsCitation":"Wiskirchen, K.H., Jacobsen, T., Ditchkoff, S., Demarais, S., and Grand, J.B., 2022, Adult white-tailed deer survival in hunted populations on public and private lands: Wildlife Society Bulletin, v. 47, no. 1, e1391, 13 p., https://doi.org/10.1002/wsb.1391.","productDescription":"e1391, 13 p.","ipdsId":"IP-085200","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445852,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1391","text":"Publisher Index Page"},{"id":433456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.42615158756091,\n 31.634110578684883\n ],\n [\n -84.94437825615643,\n 31.634110578684883\n ],\n [\n -84.94437825615643,\n 33.347781473762865\n ],\n [\n -88.42615158756091,\n 33.347781473762865\n ],\n [\n -88.42615158756091,\n 31.634110578684883\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wiskirchen, Kevyn H.","contributorId":341929,"corporation":false,"usgs":false,"family":"Wiskirchen","given":"Kevyn","email":"","middleInitial":"H.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":909175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobsen, T.C.","contributorId":341930,"corporation":false,"usgs":false,"family":"Jacobsen","given":"T.C.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":909176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ditchkoff, S.S.","contributorId":220075,"corporation":false,"usgs":false,"family":"Ditchkoff","given":"S.S.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":909177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demarais, S.","contributorId":341933,"corporation":false,"usgs":false,"family":"Demarais","given":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":909178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":909179,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238406,"text":"70238406 - 2022 - In situ soil moisture sensors in undisturbed soils","interactions":[],"lastModifiedDate":"2022-12-02T13:42:23.337438","indexId":"70238406","displayToPublicDate":"2022-11-18T07:39:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"In situ soil moisture sensors in undisturbed soils","docAbstract":"Soil moisture directly affects operational hydrology, food security, ecosystem services, and the climate system. However, the adoption of soil moisture data has been slow due to inconsistent data collection, poor standardization, and typically short record duration. Soil moisture, or quantitatively volumetric soil water content (SWC), is measured using buried, in situ sensors that infer SWC from an electromagnetic response. This signal can vary considerably with local site conditions such as clay content and mineralogy, soil salinity or bulk electrical conductivity, and soil temperature; each of these can have varying impacts depending on the sensor technology.,
Furthermore, poor soil contact and sensor degradation can affect the quality of these readings over time. Unlike more traditional environmental sensors, there are no accepted standards, maintenance practices, or quality controls for SWC data. As such, SWC is a challenging measurement for many environmental monitoring networks to implement. Here, we attempt to establish a community-based standard of practice for in situ SWC sensors so that future research and applications have consistent guidance on site selection, sensor installation, data interpretation, and long-term maintenance of monitoring stations.,
The videography focuses on a multi-agency consensus of best-practices and recommendations for the installation of in situ SWC sensors. This paper presents an overview of this protocol along with the various steps essential for high-quality and long-term SWC data collection. This protocol will be of use to scientists and engineers hoping to deploy a single station or an entire network.
","language":"English","publisher":"MyJoVE Corporation","doi":"10.3791/64498","usgsCitation":"Caldwell, T., Cosh, M.H., Evett, S.R., Edwards, N., Hofman, H., Illston, B., Meyers, T.P., Skumanich, M., and Sutcliffe, K., 2022, In situ soil moisture sensors in undisturbed soils: Journal of Visualized Experiments, no. 189, e64498, 35 p., https://doi.org/10.3791/64498.","productDescription":"e64498, 35 p.","ipdsId":"IP-131823","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":445855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.library.noaa.gov/view/noaa/62072","text":"Publisher Index Page"},{"id":409993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"189","noUsgsAuthors":false,"publicationDate":"2022-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cosh, Michael H.","contributorId":146998,"corporation":false,"usgs":false,"family":"Cosh","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":857432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evett, Steven R. 0000-0003-3418-5771","orcid":"https://orcid.org/0000-0003-3418-5771","contributorId":244949,"corporation":false,"usgs":false,"family":"Evett","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":857433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Nathan","contributorId":260132,"corporation":false,"usgs":false,"family":"Edwards","given":"Nathan","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":857434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hofman, Heather","contributorId":260134,"corporation":false,"usgs":false,"family":"Hofman","given":"Heather","email":"","affiliations":[{"id":52518,"text":"USDA NRCS National Climate Center","active":true,"usgs":false}],"preferred":false,"id":857435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Illston, Bradley","contributorId":299264,"corporation":false,"usgs":false,"family":"Illston","given":"Bradley","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":857436,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyers, Tilden P.","contributorId":146138,"corporation":false,"usgs":false,"family":"Meyers","given":"Tilden","email":"","middleInitial":"P.","affiliations":[{"id":16598,"text":"NOAA/ATDD","active":true,"usgs":false}],"preferred":false,"id":857437,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Skumanich, Marina","contributorId":260137,"corporation":false,"usgs":false,"family":"Skumanich","given":"Marina","email":"","affiliations":[{"id":52519,"text":"NOAA National Integrated Drought Information System","active":true,"usgs":false}],"preferred":false,"id":857438,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sutcliffe, Kent","contributorId":299265,"corporation":false,"usgs":false,"family":"Sutcliffe","given":"Kent","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":857439,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238660,"text":"70238660 - 2022 - Carbon and carbon storage in the national wilderness preservation system of the conterminous United States","interactions":[],"lastModifiedDate":"2022-12-02T13:35:13.336547","indexId":"70238660","displayToPublicDate":"2022-11-18T07:34:42","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"7","title":"Carbon and carbon storage in the national wilderness preservation system of the conterminous United States","docAbstract":"No abstract available.
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H","contributorId":299611,"corporation":false,"usgs":false,"family":"Hand","given":"Michael","email":"","middleInitial":"H","affiliations":[{"id":32414,"text":"Forest Service","active":true,"usgs":false}],"preferred":false,"id":858219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Froemke, Pamela M","contributorId":299612,"corporation":false,"usgs":false,"family":"Froemke","given":"Pamela","email":"","middleInitial":"M","affiliations":[{"id":32414,"text":"Forest Service","active":true,"usgs":false}],"preferred":false,"id":858220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858221,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257255,"text":"70257255 - 2022 - Rainforest carnivore ecology in a managed forest reserve: Differential seasonal correlates between habitat components and relative abundance","interactions":[],"lastModifiedDate":"2024-08-14T12:04:58.815419","indexId":"70257255","displayToPublicDate":"2022-11-18T07:04:02","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Rainforest carnivore ecology in a managed forest reserve: Differential seasonal correlates between habitat components and relative abundance","docAbstract":"Studies of relationships between seasons and Neotropical carnivore distributions tend to focus on water and prey availability without considering other habitat components such as escape, foraging, and resting cover. Our goal was to evaluate habitat characteristics that may be important for predicting the seasonal (dry or rainy) relative abundance of four commonly captured Neotropical carnivores (i.e., jaguar [Panthera onca], puma [Puma concolor], ocelot [Leopardus pardalis], and grey fox [Urocyon cinereoargenteus]) in Chiquibul Forest Reserve in Belize, Central America. We used trail camera data and random-effect Poisson models to investigate how prey ratios (number of prey detections/total detections), cover (e.g., logs and stumps used for hiding cover from predators), vegetation structure, and environmental site characteristics (e.g., site harvest-history, slope, aspect) were related to carnivore relative abundance. Both prey ratios and vegetation structure appeared in supported models more frequently than other environmental site characteristics and were negatively correlated with carnivore relative abundance. Supported models differed for each season for all species except jaguars for which mammalian prey ratios and prey cover at sites was always negatively correlated with jaguar relative abundance. Carnivores appeared to avoid sites where vegetation created ideal escape and hiding cover for prey even though prey may be less abundant. Our data suggest that vegetation structure and composition can create conditions conducive to carnivore foraging and that these characteristics can differ by season in the tropics.
Imaging sonar was used to assess the behavior, abundance, and timing of fish at the entrances to the Selective Water Withdrawal (SWW) intake structure located in the forebay of Round Butte Dam, Oregon during the spring of 2021. The purposes of the SWW are (1) to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and (2) to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. Part of the evaluation, to determine how well the structure performs at collecting juvenile salmonids, needs (A) to regularly assess how fish are approaching the entrance, and (B) to determine if operational flows could be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The primary goals of this study were (1) to assess the abundance and behaviors of smolt-size fish observed near the SWW and (2) to provide data of the effect of two-night generation operation timing conditions on movements and behaviors of fish near the entrance to the SWW structure. The purpose of this assessment is to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2021 smolt out-migration period. One unit monitored fish movements near the south entrance and one unit monitored movements near the north entrance of the SWW. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances with greater abundances observed during night, corresponding with greater discharge through the SWW than during the day when discharge was reduced. Differences in fish abundance were observed between the night generation operation timing conditions, with increased fish counts observed when elevated discharge was extended to 6:00 a.m., rather than when discharges have been traditionally reduced in the early morning at 4:00 a.m. Fish of all size groups were primarily observed near the center of the SWW, and greater abundances of fish were observed at the south entrance. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that (A) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (B) bull trout-size fish were present at the SWW, and (C) fish were more numerous at the SWW when night generation operation timing was extended later into the morning hours rather than the traditional operation timing flow reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221098","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2022, Evaluation of fish behavior at the entrances to a Selective Water Withdrawal structure in Lake Billy Chinook, Oregon, 2021: U.S. Geological Survey Open-File Report 2022–1098, 28 p., https://doi.org/10.3133/ofr20221098.","productDescription":"viii, 28 p.","onlineOnly":"Y","ipdsId":"IP-139510","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409425,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1098/images"},{"id":409424,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1098"},{"id":409423,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.pdf","text":"Report","size":"36.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1098"},{"id":409422,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1098/coverthb.jpg"},{"id":409426,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5557866634069,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.75388913871075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
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6505 NE 65th Street
Seattle, Washington 98115-5016
The 21–22 June 2019 eruption of Raikoke volcano, Russia, provided an opportunity to explore how spatial trends in volcanic lightning locations provide insights into pulsatory eruption dynamics. Using satellite-derived plume heights, we examine the development of lightning detected by Vaisala’s Global Lightning Dataset (GLD360) from eleven, closely spaced eruptive pulses. Results from one-dimensional plume modeling show that the eruptive pulses with maximum heights 9–16.5 km above sea level were capable of producing ice in the upper troposphere, which contributed variably to electrification and volcanic lightning. A key finding is that lightning locations not only followed the main dispersal direction of these ash plumes, but also tracked a lower-level cloud derived from pyroclastic density currents. We show a positive relationship between umbrella cloud expansion and the area over which lightning occurs (the ‘lightning footprint’). These observations suggest useful metrics to characterize ongoing eruptive activity in near real-time.
","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.05.02.385395","usgsCitation":"Smith, C., Van Eaton, A.R., Schneider, D.J., Mastin, L.G., Matoza, R.S., McKee, K., and Maher, S., 2022, Spatial analysis of globally detected volcanic lightning from the June 2019 eruption of Raikoke volcano, Kuril Islands: Volcanica, v. 5, no. 2, p. 385-395, https://doi.org/10.30909/vol.05.02.385395.","productDescription":"11 p.","startPage":"385","endPage":"395","ipdsId":"IP-144250","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.05.02.385395","text":"Publisher Index Page"},{"id":466647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Kuril Islands, Raikoke volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.22845752671452,\n 48.304580250458486\n ],\n [\n 153.22845752671452,\n 48.27759609075218\n ],\n [\n 153.27313900396035,\n 48.27759609075218\n ],\n [\n 153.27313900396035,\n 48.304580250458486\n ],\n [\n 153.22845752671452,\n 48.304580250458486\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Cassandra M.","contributorId":349097,"corporation":false,"usgs":false,"family":"Smith","given":"Cassandra M.","affiliations":[{"id":83431,"text":"NSF Postdoc, Alaska Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":924002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":924004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":924006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKee, Kathleen 0000-0003-3189-9189","orcid":"https://orcid.org/0000-0003-3189-9189","contributorId":265977,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","email":"","affiliations":[{"id":54848,"text":"Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":924007,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":924008,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262035,"text":"70262035 - 2022 - Investigating impacts of small dams and dam removal on dissolved oxygen in streams","interactions":[],"lastModifiedDate":"2025-01-10T18:11:45.778127","indexId":"70262035","displayToPublicDate":"2022-11-17T10:54:08","publicationYear":"2022","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":"Investigating impacts of small dams and dam removal on dissolved oxygen in streams","docAbstract":"Small surface-release dams are prevalent across North American watersheds and can alter stream flow, thermal regimes, nutrient dynamics, and sediment transport. These dams are often implicated as a cause of negative water quality impacts—including reduced dissolved oxygen (DO)—and dam removal is increasingly employed to restore natural stream processes and improve DO. However, published impacts of small dams on DO vary widely across sites, and even less is known about the extent and timescale of DO recovery following removal. Therefore, we sought to quantify the effects of small dams and dam removal on DO and determine the dam, stream, and watershed characteristics driving inter-site variation in responses. We deployed continuous data loggers for 3 weeks during summer months in upstream (reference), impoundment, and downstream reaches at each of 15 dammed sites and collected equivalent data at 10 of those sites following dam removal. Prior to dam removal, most sites (60%) experienced a decrease in DO (an average of 1.15 mg/L lower) within the impoundment relative to upstream, but no consistent impacts on diel ranges or on downstream reaches. Before dam removal, 5 impacted stream reaches experienced minimum DO levels below acceptable water quality standards (<5 mg/L); after dam removal, 4 of 5 of these reaches met DO standards. Sites with wider impoundments relative to upstream widths and sites located in watersheds with more cultivated land experienced the greatest decreases in impoundment DO relative to upstream. Within one year following dam removal, impoundment DO recovered to upstream reference conditions at 80% of sites, with the magnitude of recovery strongly related to the magnitude of pre-removal impacts. These data suggest that broadly, small dams negatively affect stream DO, and the extent of effects are modulated by impoundment geometry and watershed characteristics. These results may help practitioners to prioritize restoration efforts at those sites where small dams are having outsized impacts, and therefore where the greatest water quality benefits may occur.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0277647","usgsCitation":"Abbott, K., Zaidel, P., Roy, A.H., Houle, K., and Nislow, K., 2022, Investigating impacts of small dams and dam removal on dissolved oxygen in streams: PLoS ONE, v. 17, no. 11, e0277647, 23 p., https://doi.org/10.1371/journal.pone.0277647.","productDescription":"e0277647, 23 p.","ipdsId":"IP-143494","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0277647","text":"Publisher Index Page"},{"id":466019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"17","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Abbott, Katherine M.","contributorId":347949,"corporation":false,"usgs":false,"family":"Abbott","given":"Katherine M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":922764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaidel, Peter A.","contributorId":347950,"corporation":false,"usgs":false,"family":"Zaidel","given":"Peter A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":922765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":922766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houle, Kristopher M.","contributorId":347951,"corporation":false,"usgs":false,"family":"Houle","given":"Kristopher M.","affiliations":[{"id":83272,"text":"Massachusetts Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":922767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nislow, Keith H.","contributorId":347953,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":922768,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230334,"text":"70230334 - 2022 - Preliminary national-scale seismic risk assessment of natural gas pipelines in the United States","interactions":[],"lastModifiedDate":"2023-05-16T21:05:04.159768","indexId":"70230334","displayToPublicDate":"2022-11-16T14:04:15","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary national-scale seismic risk assessment of natural gas pipelines in the United States","docAbstract":"Although the gas pipeline infrastructure in the United States is vulnerable to the seismic hazards of (i) strong ground shaking, and (ii) ground failures induced by surface faulting, liquefaction, or landslides, limited national guidance exists for operators to consistently evaluate the earthquake response of their pipelines. To provide additional information for stakeholders and establish more consistency at a national scale, we attempt to quantify seismic risk for gas transmission pipelines in the conterminous United States using a metric such as average annual loss, which helps readily distinguish geographic areas of high and low relative risk. Specifically, we integrate the 2018 National Pipeline Mapping System, the 2018 National Seismic Hazard Model, and several candidate models from the literature for estimating pipeline damage. Through this effort, we highlight major research needs for ultimately reducing the many uncertainties associated with a comprehensive seismic risk assessment of gas pipelines.
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Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, J. 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The typical AEL framework has been augmented with new replacement unit cost data and bridge-specific parameters for modifying default fragility curves. Earthquake hazard is defined using spectral acceleration hazard curves that account for location-specific soil conditions. Hazard is integrated with bridge-specific fragility curves to compute annual probabilities of exceeding various damage states. Further, economic loss for each bridge was estimated using the repair costs associated with specific damage states and indirect costs incurred from downtimes. Quantitative assessments of seismic risk, especially those that account for downtime-related impacts, enable us to illustrate the distribution of risk with respect to geographic region, era of construction, or type of bridge.
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Resident flycatchers were only found on two drainages in San Diego County, at San Dieguito and San Luis Rey Rivers, with 99 percent occurring on the San Luis Rey River. Resident flycatchers were detected at 18 percent of survey locations (Bonsall, Cleveland National Forest, Rey River Ranch, San Dieguito, and Vista Irrigation District [VID], and VID Lake Henshaw). Resident flycatchers were documented for the first time at Lake Henshaw, the only new location surveyed that supported flycatchers. We detected a minimum of 80 resident flycatchers from 2015 to 2019, most of these were upstream and downstream from Lake Henshaw. Transient flycatchers were found at 42 percent of survey locations; 38 transient individuals were detected at Agua Hedionda Creek, Otay River, San Diego River, San Dieguito River, and the San Luis Rey River.
Over the course of this study, 11 locations historically occupied by resident flycatchers were resurveyed; only 5 were found to have resident flycatchers: (1) Bonsall, (2) Cleveland National Forest, (3) Rey River Ranch, (4) San Dieguito, and (5) Vista Irrigation District. The number of resident flycatchers declined from previous high counts at all five locations. Collectively, the number of resident flycatcher territories within the historically occupied area of the upper San Luis Rey River downstream from Lake Henshaw (Cleveland National Forest, Rey River Ranch, and Vista Irrigation District) declined 71 percent between 1999 (48) and 2019 (14); 42 percent of the decline occurred between 1999 and 2016, with an additional decline (50 percent) occurring between 2016 and 2019. In 2016, the distribution of flycatcher territories at the historically occupied area of the upper San Luis Rey River changed relative to the distribution in 1999: the proportion of territories at Cleveland National Forest and Rey River Ranch decreased to 36 percent each, while Vista Irrigation District increased to 29 percent, creating a more equal distribution of territories across the historically occupied area. By 2019, the distribution changed relative to 2016, with most of the territories spread equally between Cleveland National Forest and Rey River Ranch (43 percent each), while the proportion of territories at Vista Irrigation District declined to 14 percent.
During countywide surveys, we documented the dispersal of two natal banded flycatchers; both were females that were originally banded as nestlings at Marine Corps Base Camp Pendleton and were seen for the first time as breeding adults. One of the females dispersed to San Dieguito, a distance of 41 kilometers, and a second female dispersed to Cleveland National Forest, a distance of 55 kilometers. We also documented the within-season movement of a uniquely banded male that was seen at the beginning of the 2017 breeding season at Bonsall and was later documented at San Dieguito, a movement distance of 31 kilometers.
We completed nest monitoring activities along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California from 2016 to 2019. Monitoring occurred at three locations: (1) Cleveland National Forest, (2) Rey River Ranch, and (3) Vista Irrigation District, collectively the upper San Luis Rey River monitoring area. The number of flycatcher territories monitored each year ranged from 14 to 27. We observed polygynous pairings (one male paired with multiple females) in all years, with the lowest rate of polygyny (number of polygynous pairs/total number of pairs) observed in 2016 (10 percent) and the highest in 2017 (70 percent). The proportion of paired males that were polygynous ranged from 5 to 54 percent between 2016 and 2019.
We monitored the nesting activity of 14–27 pairs annually during the course of the study. Most of the first nesting attempts were initiated during late May and early June. We monitored 18–41 Southwestern Willow Flycatcher nests per year from 2016 to 2019. Apparent nest success ranged from 11 to 37 percent and differed significantly by year, with higher success in 2016 and 2017 compared to 2018 and 2019. Predation was the presumed to be the primary source of nest failure, with 63–84 percent of failures annually attributed to predation. Although none of the failures were attributed to Brown-headed cowbird (Molothrus ater) parasitism, 4–27 percent of nests were parasitized annually from 2016 to 2019, with increased parasitism rates observed in 2018 and 2019 compared to 2016 and 2017. We “rescued” 11 parasitized nests between 2016 and 2019 by removing cowbird eggs; if those nests had been allowed to fail, apparent nest success would have been up to 45 percent lower annually.
Flycatcher egg clutch size ranged from 2.8±0.8 to 3.1±0.8 annually and did not vary significantly between years. The number of fledglings per pair ranged from 0.5±1.0 to 1.6±1.5 annually from 2016 to 2019. There was a significant difference in the number of young fledged per pair between years, with pairs in 2016 producing more than three times the number of fledglings compared to 2019. The percent of pairs fledging at least one young ranged from 18 to 62 percent annually but did not vary significantly by year.
Analysis of flycatcher daily nest survival rates suggested that both early and late winter precipitation influenced nest survival, with increases in early winter precipitation positively influencing nest survival and later winter precipitation negatively influencing nest survival. The second-best supported model included year, with the lowest daily nest survival occurring in 2018 and 2019.
A total of 119 flycatchers were newly banded over the course of this study; 36 adult flycatchers were banded with a unique color combination, and 83 nestlings (57 of which survived to fledging) were banded with a single band on the left or right leg. In addition, two adults that were banded before 2015 were observed in the monitoring area. Between 2015 and 2019, we accumulated 94 resights of 49 individual color-banded adult flycatchers that ranged in age from 1 to 8 years old.
Banding allowed us to examine differences in annual survivorship among flycatchers of different ages and sexes. We estimated annual survivorship of adult males to be 69±7 percent, which is higher than estimates of female survivorship (45±10 percent). Annual survivorship of first-year flycatchers ranged from 24 to 41 percent, which is roughly half the estimates calculated for adult flycatchers (52–75 percent). We found no evidence that precipitation in the previous breeding year had an effect on flycatcher survival.
We were also able to observe dispersal and movement among adults and first-year flycatchers. Average first-year dispersal distance was 3.1±2.6 kilometers, with the longest dispersal (8.5 kilometers) by a natal female dispersing from the monitoring area to Lake Henshaw. Of the first-year flycatchers, 65 percent returned to the monitoring area to establish an adult breeding territory, while the remaining 35 percent dispersed to Lake Henshaw.
Territory fidelity among adult flycatchers was high with 69±13 percent of returning adults occupying the same territory (or within 100 meters) from the previous year. There was no significant difference in territory fidelity between males and females, or across years. Nesting success in the previous year appeared to be a strong driver of territory fidelity, with adults more likely to return to the same territory following years when they successfully fledged young. The average between-year movement for returning adult flycatchers was 0.5±0.8 km. We documented the movement of two adult males from the monitoring area to Lake Henshaw. Between-year movement distances did not differ by sex or year.
Resident flycatchers in the upper San Luis Rey River monitoring area used five habitat types from 2016 to 2019: (1) willow-oak, (2) willow-ash, (3) oak-sycamore, (4) mixed willow riparian, and (5) willow-sycamore, with willow-oak the most commonly used habitat type. The most commonly recorded dominant species at flycatcher territories included coast live oak (Quercus agrifolia), red or arroyo willow (Salix laevigata or Salix lasiolepis), California sycamore (Platanus racemosa), and velvet ash (Fraxinus velutina).
In 2018, we anecdotally began to observe dead and dying oaks in the monitoring area, which we believe to be the result of goldspotted oak borer (Agrilus auroguttatus) infestation. At the conclusion of this study, we investigated the overall change in normalized difference vegetation index (NDVI) in flycatcher territories within the monitoring area. The greatest negative change in NDVI occurred in territories closest to Lake Henshaw, and many of the affected territories were no longer occupied in the later years of the study.
Flycatchers used 13 plant species for nesting at the monitoring area from 2016 to 2019; 70 percent of all nests were placed in coast live oak. None of the nest characteristics including host height, nest height, distance to the edge of the host, or distance to the edge of the vegetation clump where the nest was placed differed between years. In 2016, successful nests were placed higher than unsuccessful nests; no other within-year differences were observed.
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Sacramento, California 95819
This study evaluates the economic impacts of a Mw7.0 Hayward fault scenario earthquake on the greater San Francisco Bay Region’s economy and the California economy as a whole using a detailed multiregional, static computable general equilibrium model. Economic impacts in terms of Gross Regional Product (GRP) losses caused by both capital stock (building and content) damages and water and electricity utilities, and telecommunications-service disruptions are estimated. The results indicate that the total losses are primarily caused by capital stock damages. In the 6 months following the earthquake, total GRP losses are estimated to be $44.2 billion (4.2 percent of California’s projected baseline GRP over the period), but this result could be reduced by about 43 percent to $25.3 billion after factoring in microeconomic resilience tactics. The GRP losses associated with lifeline service disruptions are estimated to be $1.4 billion, which can be reduced by over 85 percent when resilience tactics are implemented. The most effective tactics are the ability to make up lost production by people working overtime or extra shifts (production recapture), making greater use of processes that do not need disrupted goods or services (production isolation), and substituting for disrupted supplies and services (input substitution), though their impact varies across the various causal factors influencing GRP losses.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lifelines 2022","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Lifelines 2022","conferenceDate":"Jan 31-Feb 11, 2022","conferenceLocation":"Virtual","language":"English","doi":"10.1061/9780784484449.046","usgsCitation":"Sue Wing, I., Wei, D., Rose, A., and Wein, A., 2022, Economic consequences of the HayWired earthquake scenario, in Lifelines 2022, Virtual, Jan 31-Feb 11, 2022, p. 523-533, https://doi.org/10.1061/9780784484449.046.","productDescription":"11 p.","startPage":"523","endPage":"533","ipdsId":"IP-132809","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":416239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.98386509807902,\n 38.40622823110516\n ],\n [\n -122.98386509807902,\n 36.891902309301216\n ],\n [\n -121.44288105987195,\n 36.891902309301216\n ],\n [\n -121.44288105987195,\n 38.40622823110516\n ],\n [\n -122.98386509807902,\n 38.40622823110516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sue Wing, Ian","contributorId":304246,"corporation":false,"usgs":false,"family":"Sue Wing","given":"Ian","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":869872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wei, Dan","contributorId":248873,"corporation":false,"usgs":false,"family":"Wei","given":"Dan","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":869873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Adam","contributorId":248874,"corporation":false,"usgs":false,"family":"Rose","given":"Adam","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":869874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248899,"text":"70248899 - 2022 - Applying consequence-driven scenario selection to lifelines","interactions":[],"lastModifiedDate":"2023-09-25T14:52:47.193278","indexId":"70248899","displayToPublicDate":"2022-11-16T09:47:33","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Applying consequence-driven scenario selection to lifelines","docAbstract":"We present a new consequence-driven framework for earthquake scenario selection. For emergency managers, utility operators, policy makers, and other stakeholders, a scenario-based seismic risk assessment is often necessary for the purpose of emergency management and planning. In developing a scientifically defensible scenario, stakeholders can simulate a realistic event in order to pre-identify vulnerabilities in the system and support action to address these vulnerabilities. Selecting scenarios is particularly challenging for important population centers and critical infrastructure in stable tectonic environments, such as in the central and eastern United States, where uncertain long-term seismicity and unknown faults offer inadequate constraints. Notably, significant events in these so-called stable regions do occur (e.g., Nahanni, Canada, 1985, M6.9; Tennant Creek, Australia, 1998, M6.7). In regions of low seismicity, even moderate events can be consequential due to the higher vulnerability of buildings typical of such regions when compared to regions of higher seismicity. Furthermore, communicating seismic risk to stakeholders and the general public in these regions can be especially challenging due to the complexities of characterizing the hazard level. This framework has been developed to address these challenges for scenario selection in low seismic hazard regions. In this new approach, the analysis begins instead with the explicit definition of a consequence of concern to the specific stakeholder. This can range from a definition of loss (in lives, dollars, or another metric of interest), or a performance metric for critical infrastructure. The framework leverages United States Geological Survey software to run the hazard and consequence analysis. Driven by this stakeholder-defined consequence, an inversion analysis generates a complete event set of candidate scenarios that could breach this consequence. The final selection of a scenario, or family of scenarios, is then scientifically informed, but not limited by our lack of constraints in characterizing the hazard.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Lifelines","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Lifelines 2022","conferenceDate":"January 31 - February 11, 2022","conferenceLocation":"Online","language":"English","publisher":"American Society of Civil Engineers","usgsCitation":"Lin, Y.C., Wald, D.J., Thompson, E.M., and Lallemant, D., 2022, Applying consequence-driven scenario selection to lifelines, in Lifelines, Online, January 31 - February 11, 2022, p. 411-422.","productDescription":"12 p.","startPage":"411","endPage":"422","ipdsId":"IP-130792","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":421131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421117,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ascelibrary.org/doi/abs/10.1061/9780784484449.036","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Yolanda C 0000-0002-0423-4248","orcid":"https://orcid.org/0000-0002-0423-4248","contributorId":317878,"corporation":false,"usgs":false,"family":"Lin","given":"Yolanda","email":"","middleInitial":"C","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":884130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":884131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":884132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lallemant, David 0000-0001-5759-9972","orcid":"https://orcid.org/0000-0001-5759-9972","contributorId":290680,"corporation":false,"usgs":false,"family":"Lallemant","given":"David","email":"","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":884133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247864,"text":"70247864 - 2022 - Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador","interactions":[],"lastModifiedDate":"2023-08-22T12:13:20.9477","indexId":"70247864","displayToPublicDate":"2022-11-16T07:09:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador","docAbstract":"Stratovolcanoes are commonly characterised by cyclic eruptive activity marked by transitions between dome-forming, Vulcanian, Subplinian and Plinian eruptions. Guagua Pichincha volcano (Ecuador) has been a location of such cyclicity for the past ~ 2000 years, with Plinian eruptions in the first and tenth centuries AD (Anno Domini/after Christ), and CE (Common Era) 1660, which were separated by dome-forming to Subplinian eruptions, such as the recent 1999–2001 eruption. These cycles are therefore a prominent example of effusive-explosive transitions at varying timescales. Here, we investigate the reasons for such shifts in activity by focusing on degassing and outgassing processes within the conduit. We have coupled a petrophysical and textural analysis of dacites from the CE 1660 Plinian eruption and the 1999–2001 dome-forming/Vulcanian eruption, with different percolation models in order to better understand the role of degassing on eruptive style. We demonstrate that the transition from dome-forming to Plinian activity is correlated with differences in phenocryst content and consequently in bulk viscosity. A lower initial phenocryst content and viscosity is inferred for the Plinian case, which promotes faster ascent, closed-system degassing, fragmentation and explosive activity. In contrast, dome-forming phases are promoted by a higher magma viscosity due to higher phenocryst content, with slower ascent enhancing gas escape and microlite crystallization, decreasing explosivity and yielding effusive activity.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01612-1","usgsCitation":"Colombier, M., Bernard, B., Wright, H.M., Le Pennec, J., Caceres, F., Cimarelli, C., Heap, M.J., Samaniego, P., Vasseur, J., and Dingwell, D.B., 2022, Conduit processes in crystal-rich dacitic magma and implications for eruptive cycles at Guagua Pichincha volcano, Ecuador: Bulletin of Volcanology, v. 84, 105, 23 p., https://doi.org/10.1007/s00445-022-01612-1.","productDescription":"105, 23 p.","ipdsId":"IP-143030","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-022-01612-1","text":"Publisher Index Page"},{"id":420006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Guagua Pichincha volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.96144509158114,\n 0.9806815363857169\n ],\n [\n -77.96144509158114,\n 0.45944639801014375\n ],\n [\n -77.4628312552756,\n 0.45944639801014375\n ],\n [\n -77.4628312552756,\n 0.9806815363857169\n ],\n [\n -77.96144509158114,\n 0.9806815363857169\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"84","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Colombier, Mathieu","contributorId":328620,"corporation":false,"usgs":false,"family":"Colombier","given":"Mathieu","email":"","affiliations":[{"id":78422,"text":"LMU Munich","active":true,"usgs":false}],"preferred":false,"id":880777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernard, Benjamin","contributorId":178529,"corporation":false,"usgs":false,"family":"Bernard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":880778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":880779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Le Pennec, Jean-Luc","contributorId":315394,"corporation":false,"usgs":false,"family":"Le Pennec","given":"Jean-Luc","affiliations":[{"id":68303,"text":"CNRS, France","active":true,"usgs":false}],"preferred":false,"id":880780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caceres, Francisco","contributorId":328621,"corporation":false,"usgs":false,"family":"Caceres","given":"Francisco","email":"","affiliations":[{"id":78422,"text":"LMU Munich","active":true,"usgs":false}],"preferred":false,"id":880781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cimarelli, Corrado","contributorId":257017,"corporation":false,"usgs":false,"family":"Cimarelli","given":"Corrado","affiliations":[{"id":47800,"text":"Ludwig Maximilian University of Munich","active":true,"usgs":false}],"preferred":false,"id":880782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":880783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Samaniego, Pablo","contributorId":205724,"corporation":false,"usgs":false,"family":"Samaniego","given":"Pablo","email":"","affiliations":[{"id":37157,"text":"Université Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France","active":true,"usgs":false}],"preferred":false,"id":880784,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vasseur, Jeremie","contributorId":315405,"corporation":false,"usgs":false,"family":"Vasseur","given":"Jeremie","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":880785,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dingwell, Donald B.","contributorId":201841,"corporation":false,"usgs":false,"family":"Dingwell","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":36273,"text":"Ludwig-Maximilians-Universität (LMU) München","active":true,"usgs":false}],"preferred":false,"id":880786,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70240713,"text":"70240713 - 2022 - Grasshopper species composition differs between prairie dog colonies and undisturbed sites in a sagebrush grassland","interactions":[],"lastModifiedDate":"2023-02-16T12:54:27.069165","indexId":"70240713","displayToPublicDate":"2022-11-16T06:52:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2556,"text":"Journal of the Kansas Entomological Society","active":true,"publicationSubtype":{"id":10}},"title":"Grasshopper species composition differs between prairie dog colonies and undisturbed sites in a sagebrush grassland","docAbstract":"Grasshoppers are major consumers of plant biomass in grassland and shrubland ecosystems. While often considered generalists, grasshopper species have differing habitat preferences and interactions with other consumers in grasslands. There are conflicting accounts of how prairie dog colonies and differences in vegetation impact grasshopper abundance and composition. We conducted a landscape-scale survey of grasshopper communities, plant communities, and prairie dogs in a grassland/shrubland ecosystem in eastern Wyoming. Over the study landscape, spurthroat grasshoppers (Melanoplinae) were associated with lower sagebrush cover and lower cover of C3 perennial graminoids, bandwing grasshoppers (Oedipodinae) were associated with low-lying areas with a high cover of C4 grasses and a low cover of cheatgrass, and slantface grasshoppers (Gomphocerinae) were associated with low vegetation height. Prairie dogs, presumably because of their effects on vegetation, had different impacts on different groups of grasshoppers. Melanoplinae grasshoppers, the Wyoming toothpick grasshopper (Paropomala wyomingensis Thomas), and grasshoppers with early-season phenology were associated with prairie dog colonies. However, because some species of grasshoppers were positively and others negatively associated with prairie dogs, the net effect of prairie dogs on total grasshopper biomass was neutral. Thus, to determine the role of grasshoppers in prairie ecosystems, it will be important to determine whether there is functional equivalence of grasshopper species in consuming plant biomass and as food for vertebrates.
Invasive plants such as Asiatic bittersweet (Celastrus orbiculatus Thunb.) are a significant problem for land managers as they impact plant species composition, disrupt nutrient dynamics and structure of native ecosystems, and are difficult to eradicate. As a result of the increasing abundance of Asiatic bittersweet across the eastern U.S., we have been investigating underlying factors potentially contributing to the success of this plant. Recently, ecologists have been investigating the role of plant-soil-microbe interactions contributing to plant invasion. This work has led to question: are there certain microbes (e.g., bacteria, fungi) contributing to the success of some invasive plants? We hypothesize that despite differences in geologic age of soils where Asiatic bittersweet has established in the Indiana Dunes National Park there are sufficient common factors that led to common bacterial taxa in their rhizosphere. The objectives were to determine differences and commonalities in the soil chemistry, plant community and bacterial communities of Asiatic bittersweet plants. To achieve these objectives, bittersweet plants were collected at thirteen locations in the national park from soils ranging in geologic age from 150 to over 14,500 years. Surrounding soil chemistry, plant cover and the 16S rRNA gene amplicon sequences of rhizosphere soil bacterial communities of these Asiatic bittersweet were compared. Asiatic bittersweet coverage of sampling sites ranged from 2 to 77% averaging 52 ± 2%. There were statistically significant differences (p < 0.05) in alpha diversity (Shannon, Faith’s PD and Pielou’s evenness) and beta diversity (Bray Curtis, Jaccard, unweighted Unifrac, weighted Unifrac) among the samples when grouped by soil age or habitat. Despite these differences in the bacterial communities from different soil ages and habitats, some bacterial taxa (e.g., Bacillus, Streptomyces, Sphingomonas and Rhizobiales) previously found in other studies to be beneficial to plant growth were found in every rhizosphere community sampled. These microbes provide insight into a possible contributing factor to the success of this invasive plant at the Indiana Dunes National Park, and a strategy for future work to reduce the impact of Asiatic bittersweet establishment and offer some new strategies to manage this nuisance species.
The St. Croix National Scenic Riverway (SACN) has been the site of propagation and restoration efforts for two federally endangered unionid mussels: Higgins’ Eye, Lampsilis higginsii and Winged Mapleleaf (WML), Quadrula fragosa. Since about 2000, government agencies have collaboratively developed techniques to successfully propagate Higgins’ Eye and reintroduce the captive-reared subadult mussels into rehabilitated habitats in the upper Mississippi River Basin and several tributaries, including the SACN. However, propagation efforts for the WML have had limited success from 2003 to present. The population of WML in the SACN has high value because it is physically isolated and genetically distinct from four southern populations, and it is the only known self-sustaining population within the upper Mississippi River. Unionids have a complex reproductive cycle that includes a parasitic larval stage (glochidia) that requires species-specific fish hosts. WML are one of the few species that are fall, short-term (~6 weeks) brooders—brooding begins at end of August. In the SACN, Channel Catfish (Ictalurus punctatus) are the only known host for WML and glochidia are assumed to overwinter on their host fish and detach the following spring. Research has shown that holding hatchery reared channel catfish that are infested with WML glochidia in cages, either in situ or in a hatchery, over winter has been a challenge due to high fish mortality; rearing juveniles after transformation has also resulted in high mortality rates and juvenile loss (Wege et al. 2007). The importance of the overwintering parasitic period and the overall health of the host fish for successful transformation of juvenile WML is unknown, but these key criteria could play an important role in successful propagation efforts. This research has three objectives: (1) compile historic data from >14 years of Q. fragosa propagation efforts into a searchable database to identify potential knowledge gaps that could be limiting its success, (2) explore in situ and ex situ propagation techniques to optimize production of Q. fragosa juveniles, and (3) characterize the movement pattern of Channel Catfish that are artificially inoculated with the SACN strain of Q. fragosa to identify potential juvenile release survey locations in future years.
","language":"English","publisher":"National Park Service","usgsCitation":"Bartsch, M., 2022, Evaluate propagation efforts and determine dispersal patterns for Quadrula fragosa from tagged, artificially infested host fish (Ictalurus punctatus) in the St. Croix National Scenic Riverway (SACN), 5 p.","productDescription":"5 p.","ipdsId":"IP-137874","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":431293,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573106"},{"id":431619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"St. Croix National Scenic Riverway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.81523481710744,\n 46.384142491911746\n ],\n [\n -92.9593012517021,\n 45.83577178783574\n ],\n [\n -92.88228401067886,\n 45.02255043765251\n ],\n [\n -92.63799466266059,\n 45.025139082376654\n ],\n [\n -92.3311370342298,\n 45.680248149277205\n ],\n [\n -91.9556447587581,\n 46.00451688552345\n ],\n [\n -91.73426769125393,\n 46.297290552169756\n ],\n [\n -91.81523481710744,\n 46.384142491911746\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartsch, Michelle 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":3165,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906707,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256623,"text":"70256623 - 2022 - Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion","interactions":[],"lastModifiedDate":"2024-08-27T15:10:10.350182","indexId":"70256623","displayToPublicDate":"2022-11-15T09:58:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion","docAbstract":"Diverse communities of groundwater-dwelling organisms (i.e., stygobionts) are important for human wellbeing; however, we lack an understanding of the factors driving their distributions, making it difficult to protect many at-risk species. Therefore, our study objective was to determine the landscape factors related to the occurrence of cavefishes and cave crayfishes in the Ozark Highlands ecoregion, USA. We sampled cavefishes and cave crayfishes at 61 sampling units using both visual and environmental DNA surveys. We then modeled occurrence probability in relation to lithology and human disturbance while accounting for imperfect detection. Our results indicated that occurrence probability of cave crayfishes was negatively associated with human disturbance, whereas there was a weak positive relationship between cavefish occurrence and disturbance. Both cavefishes and cave crayfishes were more likely to occur in limestone rather than dolostone lithology. Our results indicate structuring factors are related to the distribution of these taxa, but with human disturbance as a prevalent modifier of distributions for cave crayfishes. Limiting human alteration near karst features may be warranted to promote the persistence of some stygobionts. Moreover, our results indicate current sampling efforts are inadequate to detect cryptic species; therefore, expanding sampling may be needed to develop effective conservation actions.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-022-21791-3","usgsCitation":"Mouser, J., Brewer, S.K., Niemiller, M., Mollenhauer, R., and Van Den Bussche, R.A., 2022, Lithology and disturbance drive cavefish and cave crayfish occurrence in the Ozark Highlands ecoregion: Scientific Reports, v. 12, 19559, 10 p., https://doi.org/10.1038/s41598-022-21791-3.","productDescription":"19559, 10 p.","ipdsId":"IP-136389","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445870,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-21791-3","text":"Publisher Index Page"},{"id":433200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.19813639078185,\n 36.971706993010315\n ],\n [\n -94.76416998727156,\n 36.88121743833784\n ],\n [\n -94.9821977429566,\n 36.432177796608784\n ],\n [\n -94.29247532353017,\n 36.292055756716266\n ],\n [\n -93.663549105208,\n 36.467590353199\n ],\n [\n -93.75579161722848,\n 36.98846283086834\n ],\n [\n -94.19813639078185,\n 36.971706993010315\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, Joshua B.","contributorId":341406,"corporation":false,"usgs":false,"family":"Mouser","given":"Joshua B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niemiller, Matthew L.","contributorId":341407,"corporation":false,"usgs":false,"family":"Niemiller","given":"Matthew L.","affiliations":[{"id":81735,"text":"The University of Alabama in Huntsville","active":true,"usgs":false}],"preferred":false,"id":908363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mollenhauer, Robert","contributorId":341408,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Den Bussche, Ronald A.","contributorId":341409,"corporation":false,"usgs":false,"family":"Van Den Bussche","given":"Ronald","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908365,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238344,"text":"70238344 - 2022 - Evaluating noninvasive methods for estimating cestode prevalence in a wild carnivore population","interactions":[],"lastModifiedDate":"2022-11-17T13:12:09.830263","indexId":"70238344","displayToPublicDate":"2022-11-15T07:10:07","publicationYear":"2022","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":"Evaluating noninvasive methods for estimating cestode prevalence in a wild carnivore population","docAbstract":"Helminth infections are cryptic and can be difficult to study in wildlife species. Helminth research in wildlife hosts has historically required invasive animal handling and necropsy, while results from noninvasive parasite research, like scat analysis, may not be possible at the helminth species or individual host levels. To increase the utility of noninvasive sampling, individual hosts can be identified by applying molecular methods. This allows for longitudinal sampling of known hosts and can be paired with individual-level covariates. Here we evaluate a combination of methods and existing long-term monitoring data to identify patterns of cestode infections in gray wolves in Yellowstone National Park. Our goals were: (1) Identify the species and apparent prevalence of cestodes infecting Yellowstone wolves; (2) Assess the relationships between wolf biological and social characteristics and cestode infections; (3) Examine how wolf samples were affected by environmental conditions with respect to the success of individual genotyping. We collected over 200 wolf scats from 2018–2020 and conducted laboratory analyses including individual wolf genotyping, sex identification, cestode identification, and fecal glucocorticoid measurements. Wolf genotyping success rate was 45%, which was higher in the winter but decreased with higher precipitation and as more time elapsed between scat deposit and collection. One cestode species was detected in 28% of all fecal samples, and 38% of known individuals. The most common infection was Echinococcus granulosus sensu lato (primarily E. canadensis). Adult wolves had 4x greater odds of having a cestode infection than pups, as well as wolves sampled in the winter. Our methods provide an alternative approach to estimate cestode prevalence and to linking parasites to known individuals in a wild host system, but may be most useful when employed in existing study systems and when field collections are designed to minimize the time between fecal deposition and collection.
The primary source of chronic exposures to per- and polyfluoroalkyl substances (PFASs) in humans is through the ingestion of contaminated foods and drinking water, with fish and other seafood being a major contributor. Nevertheless, there is scant literature on the dietary exposure to PFASs for the general United States (U.S.) population. The Tampa Bay (Florida, USA) region has the highest population density in the State and communities and their attendant support services are arrayed in an urban to semi-rural continuum from the head of the Bay to the ocean mouth. Tampa Bay supports productive recreational and commercial fisheries, providing a diverse community of species. A variety of potential PFAS sources surround Tampa Bay including airports, industry, wastewater treatment plants, fire-fighting training areas and military installations. The objective of this study is to quantify PFASs in sediment and fishes collected from Tampa Bay to further estimate human health risks from dietary exposures. Sediment (n = 17) and fish (24 species, n = 140) were collected throughout Tampa Bay in 2020 and 2021 and analyzed for 25 PFAS compounds. Concentrations of PFASs in sediments and edible tissues of fish ranged from 36.8 to 2,990 ng kg-1 (dry weight) and 307 to 33,600 ng kg-1 (wet weight), respectively. Generally, levels were highest in Old Tampa Bay and decreased south towards the Gulf of Mexico. Profiles in both matrices were generally dominated by perfluorooctane sulfonic acid (PFOS) with variations by location. Estimated human health risks from the consumption of contaminated fish collected in Tampa Bay exceeded concentration thresholds for minimum risk levels (MRLs) and tolerable weekly intake (TWIs) values for adults and youths. Additionally, concentrations of PFOS in edible fish tissues of several recreationally important species collected in Tampa Bay exceeded consumption guideline levels established by several governmental agencies. In the current context, the elevated levels of PFAS in Tampa Bay and the exceedances of available thresholds for potential human health risks are a cause for concern and justify a more intensive examination especially for more heavily utilized species, particularly those used in subsistence-level fishing, which, as elsewhere may be significantly under documented.
Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543-1598
USGS Scientific Collections
USGS Coastal and Marine Geoscience Data System
Woods Hole Coastal and Marine Science Center Samples Repository
Volcanic ashfall forecasts are highly dependent on eruption source parameters (ESPs) and synoptic weather conditions at the time and location of the eruption. In New Zealand, MetService and GNS Science have been jointly developing an ashfall forecast system that incorporates four-dimensional high-resolution numerical weather prediction (NWP) and ESPs into the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic ash. However, these forecasts are based on discrete ESPs combined with a deterministic weather forecast and thus provide no information on output uncertainty. This shortcoming hinders stakeholder decision making, particularly near the geographical margin of forecasted ashfall and in areas with large gradients in forecasted ash deposition. Our study presents a new approach that incorporates uncertainty from both eruptive and meteorological inputs to deliver uncertainty in the model output. To this end, we developed probability density functions (PDFs) for three key ESPs (plume height, mass eruption rate, eruption duration) tailored to New Zealand’s volcanoes and combine them with NWP ensemble datasets to generate probabilistic ashfall forecasts using the HYSPLIT model. We show that the Latin Hypercube Sampling (LHS) technique can be used to representatively span this four-dimensional parameter space and allow us to add uncertainty quantification to rapid response forecast systems. For a case study of a hypothetical eruption at Tongariro, New Zealand we suggest that large parts of New Zealand’s North Island would not receive adequate warning for potential ashfall if uncertainties were not included in the forecasts. We also propose new probabilistic summary products to support public information and emergency responders decision making.