Rockland habitat in South Florida, USA, is a threatened ecosystem that has been lost, fragmented, or degraded because of urbanization or other anthropogenic disturbance. Furthermore, low-lying islands and coastal areas are experiencing sea level rise (SLR) and an increased frequency and intensity of tidal flooding, putting rockland habitats there at increasing risk of ecological change. We evaluated changes in the extent of rockland habitat under various scenarios of future SLR, tidal flooding, and human development for two endemic state-listed threatened species of snakes, the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring-necked Snake (Diadophis punctatus acricus). Both snakes are restricted to South Florida. We used recent and historical species' records to determine each species' habitat range. We then estimated the extent of future habitat loss due to SLR and continued human development, as well as degradation of the remaining habitat. We also asked whether the future potential drivers of habitat loss and degradation differ between the two species and across their habitat ranges. We predicted that saltwater intrusion could negatively affect rocklands by 2050, resulting in degradation of 80% of the existing habitat because of an anticipated 42 cm of SLR. Moreover, our model suggests short-term stochastic events such as storm surge and high tides may increasingly saturate the root zone of rockland vegetation before complete inundation. Under the extreme scenario, we predict most of the rockland habitat used by these two species of snakes may be inundated by 2080. Under the extreme SLR scenario, current rocklands are likely to convert to more halophytic habitat (mangrove or salt marsh wetland) within 50–60 years. Under the low scenario, 31% of rockland habitat may be lost due to human development by 2030. Therefore, mitigation actions may help to conserve specialist species within rockland habitat threatened by human activities and climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/csp2.12802","usgsCitation":"Subedi, S.C., Walls, S., Barichivich, W., Boyles, R., Ross, M.S., Hogan, J.A., and Tupy, J.A., 2022, Future changes in habitat availability for two specialist snake species in the imperiled rocklands of South Florida, U.S.A.: Conservation Science and Practice, v. 4, no. 10, e12802, 12 p.; Data Release, https://doi.org/10.1111/csp2.12802.","productDescription":"e12802, 12 p.; Data Release","ipdsId":"IP-137625","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446400,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12802","text":"Publisher Index Page"},{"id":406959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414897,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TRHCLU"}],"country":"United States","state":"Florida","county":"Miami-Dade County, Monroe County","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.80895642460405,\n 24.453130854268252\n ],\n [\n -81.0587041726492,\n 24.65004795330806\n ],\n [\n -80.4614884497,\n 24.968530156464837\n ],\n [\n -80.12555950968002,\n 25.52220481330157\n ],\n [\n -80.21887446639069,\n 25.505361805372416\n ],\n [\n -80.45776075557028,\n 25.296312583579905\n ],\n [\n -80.69664704475028,\n 24.975295417537964\n ],\n [\n -81.30506056250486,\n 24.741608543790022\n ],\n [\n -81.58873803090547,\n 24.77889253696236\n ],\n [\n -81.857485106233,\n 24.60254250373599\n ],\n [\n -81.80895642460405,\n 24.453130854268252\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Subedi, Suresh C. 0000-0001-8689-0689","orcid":"https://orcid.org/0000-0001-8689-0689","contributorId":217984,"corporation":false,"usgs":false,"family":"Subedi","given":"Suresh","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":852138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":3055,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":true,"id":852139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichivich, William 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":215988,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":852140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyles, Ryan 0000-0001-9272-867X","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":221983,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":852141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Michael S.","contributorId":202431,"corporation":false,"usgs":false,"family":"Ross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36434,"text":"Florida International University, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":852142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hogan, J. Aaron","contributorId":266106,"corporation":false,"usgs":false,"family":"Hogan","given":"J.","email":"","middleInitial":"Aaron","affiliations":[{"id":54906,"text":"Department of Biological Sciences, Florida International University, Miami, FL 33199, USA","active":true,"usgs":false}],"preferred":false,"id":852143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tupy, John A.","contributorId":296678,"corporation":false,"usgs":false,"family":"Tupy","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":64127,"text":"U.S. Fish and Wildlife Service Mississippi Ecological Services Office","active":true,"usgs":false}],"preferred":false,"id":852144,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236764,"text":"70236764 - 2022 - Comparative susceptibilities of selected California Chinook salmon and steelhead populations to isolates of L Genogroup Infectious Hematopoietic Necrosis Virus (IHNV)","interactions":[],"lastModifiedDate":"2022-09-19T13:15:31.160078","indexId":"70236764","displayToPublicDate":"2022-09-19T08:09:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Comparative susceptibilities of selected California Chinook salmon and steelhead populations to isolates of L Genogroup Infectious Hematopoietic Necrosis Virus (IHNV)","docAbstract":"Salmonid species demonstrate varied susceptibility to the viral pathogen infectious hematopoietic necrosis virus (IHNV). In California conservation hatcheries, juvenile Chinook salmon (Oncorhynchus tshawytscha) have experienced disease outbreaks due to L genogroup IHNV since the 1940s, while indigenous steelhead (anadromous O. mykiss) appear relatively resistant. To characterize factors contributing to the losses of California salmonid fish due to IHNV, three populations of Chinook salmon and two populations of steelhead native to California watersheds were compared in controlled waterborne challenges with California L genogroup IHNV isolates at viral doses of 104–106 pfu mL−1. Chinook salmon fry were moderately to highly susceptible (CPM = 47–87%) when exposed to subgroup LI and LII IHNV. Susceptibility to mortality decreased with increasing age and also with a higher temperature. Mortality for steelhead fry exposed to two IHNV isolates was low (CPM = 1.3–33%). There was little intraspecies variation in susceptibility among populations of Chinook salmon and no differences in virulence between viruses strains. Viral persistence was demonstrated by the isolation of low levels of infectious IHNV from the skin of two juvenile Chinook salmon at 215 d post exposure. The persistence of the virus among Chinook salmon used for stocking into Lake Oroville may be an explanation for the severe epidemics of IHN at the Feather River hatchery in 1998–2002.
","language":"English","publisher":"MDPI","doi":"10.3390/ani12131733","usgsCitation":"Bendorf, C.M., Yun, S.C., Kurath, G., and Hedrick, R.P., 2022, Comparative susceptibilities of selected California Chinook salmon and steelhead populations to isolates of L Genogroup Infectious Hematopoietic Necrosis Virus (IHNV): Animals, v. 12, no. 13, 1733, 16 p., https://doi.org/10.3390/ani12131733.","productDescription":"1733, 16 p.","ipdsId":"IP-141052","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":446405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani12131733","text":"Publisher Index Page"},{"id":406949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"12","issue":"13","noUsgsAuthors":false,"publicationDate":"2022-07-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Bendorf, Christin M.","contributorId":296669,"corporation":false,"usgs":false,"family":"Bendorf","given":"Christin","email":"","middleInitial":"M.","affiliations":[{"id":64125,"text":"Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California 95616 USA","active":true,"usgs":false}],"preferred":false,"id":852118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yun, Susan C.","contributorId":296670,"corporation":false,"usgs":false,"family":"Yun","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":64125,"text":"Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, California 95616 USA","active":true,"usgs":false}],"preferred":false,"id":852119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hedrick, Ronald P.","contributorId":120917,"corporation":false,"usgs":false,"family":"Hedrick","given":"Ronald","email":"","middleInitial":"P.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":852121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236493,"text":"ofr20221049 - 2022 - Understanding the Avian-Impact Offset Method—A tutorial","interactions":[],"lastModifiedDate":"2022-09-20T10:54:26.893321","indexId":"ofr20221049","displayToPublicDate":"2022-09-19T07:22:59","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1049","displayTitle":"Understanding the Avian-Impact Offset Method—A Tutorial","title":"Understanding the Avian-Impact Offset Method—A tutorial","docAbstract":"Biodiversity offsetting, or compensatory mitigation, is increasingly being used in temperate grassland and wetland ecosystems to compensate for unavoidable environmental damage from anthropogenic disturbances such as energy development and road construction. Energy-extraction and -generation facilities continue to proliferate across the natural landscapes of the United States, yet mitigation tools to ameliorate the negative behavioral effects on wildlife from these types of facilities are rarely implemented. Scientists from the U.S. Geological Survey conducted a 10-year before-after-control-impact (commonly referred to as BACI) study that evaluated the displacement effects of wind facilities on breeding grassland birds. The study determined behavioral avoidance for 7 of 9 species. This research is notable because of its design, geographical scope, and duration, which allowed for the determination of immediate, short-term effects; delayed or sustained effects; and discrete distances at which effects occurred. In addition, the U.S. Fish and Wildlife Service and Ducks Unlimited conducted a 3-year concurrent-year paired-reference study to determine behavioral avoidance for five species of dabbling ducks. By quantifying displacement rate from these two studies, U.S. Geological Survey and U.S. Fish and Wildlife Service scientists developed the Avian-Impact Offset Method (AIOM) to quantify and compensate for loss in value of breeding habitat. The AIOM converts the biological value (that is, number of bird pairs) lost by way of avoidance and estimates the site-specific number of hectares of grasslands and number of wetlands needed to compensate for displaced pairs of grassland birds and waterfowl. By converting biological value to traditional units of measure in which land is described and purchased or sold, the AIOM lends itself readily to the delivery of offsetting measures such as easement protections and restoration projects. The AIOM tool is applicable to wind, solar, oil, gas, and transportation infrastructure.
This tutorial was designed to increase awareness of the AIOM and to promote its proper application. The tutorial is divided into four sections, each of which explains a discrete topic concerning aspects of behavioral displacement. The first section provides geographical and biological context, and the second section describes the field and statistical methods and results. The third section provides step-by-step instructions for applying the AIOM to several scenarios involving grassland birds or waterfowl at wind or oil facilities. The fourth section describes decision-support tools created to implement the AIOM. The appendices provide the actual field protocols constituting the methods for the research, provide detailed results by species and wind facility for that research, and provide detailed instructions for downloading and applying the decision-support tools.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221049","collaboration":"Prepared in collaboration with the U.S. Fish and Wildlife Service","usgsCitation":"Shaffer, J.A., Loesch, C.R., and Buhl, D.A., 2022, Understanding the Avian-Impact Offset Method—A tutorial: U.S. Geological Survey Open-File Report 2022–1049, 227 p., https://doi.org/10.3133/ofr20221049.","productDescription":"Report: v, 227 p.; 2 Data Releases","numberOfPages":"238","onlineOnly":"Y","ipdsId":"IP-134338","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":406394,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1049/coverthb.jpg"},{"id":406396,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J6QUF6","text":"USGS data release","linkHelpText":"North American Breeding Bird Survey dataset 1966–2019"},{"id":406395,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1049/ofr20221049.pdf","text":"Report","size":"95.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1049"},{"id":406397,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T43SDG","text":"USGS data release","linkHelpText":"Effects of wind-energy facilities on breeding grassland bird distributions"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.236328125,\n 52.10650519075632\n ],\n [\n -113.73046875,\n 52.16045455774706\n ],\n [\n -114.78515624999999,\n 51.17934297928927\n ],\n [\n -112.8515625,\n 48.922499263758255\n ],\n [\n -111.796875,\n 47.45780853075031\n ],\n [\n -107.40234375,\n 47.040182144806664\n ],\n [\n -103.798828125,\n 47.81315451752768\n ],\n [\n -102.39257812499999,\n 47.338822694822\n ],\n [\n -100.72265625,\n 45.82879925192134\n ],\n [\n -100.37109375,\n 44.5278427984555\n ],\n [\n -99.49218749999999,\n 43.32517767999296\n ],\n [\n -96.064453125,\n 41.96765920367816\n ],\n [\n -94.39453125,\n 42.87596410238256\n ],\n [\n -95.09765625,\n 45.644768217751924\n ],\n [\n -95.97656249999999,\n 49.03786794532644\n ],\n [\n -98.7890625,\n 50.45750402042058\n ],\n [\n -112.236328125,\n 52.10650519075632\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
This report describes geodetic and geologic information used to constrain deformation models of the 2023 update to the National Seismic Hazard Model (NSHM), a set of deformation models to interpret these data, and their implications for earthquake rates in the western United States. Recent updates provide a much larger data set of Global Positioning System crustal velocities than used in the 2014 NSHM, as well as hundreds of new faults considered as active sources for the 2023 NSHM. These data are interpreted by four geodetic models of deformation that estimate fault slip rates and their uncertainties together with off‐fault moment release rates. Key innovations in the 2023 NSHM relative to past practice include (1) the addition of two new (in addition to two existing) deformation models, (2) the revision and expansion of the geologic slip rate database, (3) accounting for fault creep through development of a creep‐rate model that is employed by the four deformation models, and (4) accounting for time‐dependent earthquake‐cycle effects through development of viscoelastic models of the earthquake cycle along the San Andreas fault and the Cascadia subduction zone. The effort includes development of a geologic deformation model that complements the four geodetic models. The current deformation models provide a new assessment of outstanding discrepancies between geologic and geodetic slip rates, at the same time highlighting the need for both geologic and geodetic slip rates to robustly inform the earthquake rate model.
Global Positioning System (GPS) velocity solutions of the western United States (WUS) are compiled from several sources of field networks and data processing centers for the 2023 U.S. Geological Survey National Seismic Hazard Model (NSHM). These solutions include both survey and continuous‐mode GPS velocity measurements. I follow the data processing procedure of Parsons et al. (2013) for the Uniform California Earthquake Rupture Forecast, version 3 and McCaffrey, Bird, et al. (2013) and Zeng and Shen (2013) for their WUS deformation models in support of the 2014 NSHM update. All GPS velocity vectors are first rotated to a common North American reference frame. I edit the velocities to remove outliers and data with significant influence from volcanism. The solutions are then combined into a final GPS velocity field consisting of 4979 horizontal velocity vectors. I compute strain rates based on these GPS velocities using the method of Shen et al. (2015). These strain rates correlate closely with seismicity rates in the WUS. The results are used for WUS geodetic and geologic deformation modeling in support of the 2023 NSHM update.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220180","usgsCitation":"Zeng, Y., 2022, GPS velocity field of the Western United States for the 2023 National Seismic Hazard Model update: Seismological Research Letters, v. 93, no. 6, p. 3121-3134, https://doi.org/10.1785/0220220180.","productDescription":"14 p.","startPage":"3121","endPage":"3134","ipdsId":"IP-142151","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":407046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.94726562499999,\n 28.459033019728043\n ],\n [\n -103.0078125,\n 28.459033019728043\n ],\n [\n -103.0078125,\n 49.61070993807422\n ],\n [\n -125.94726562499999,\n 49.61070993807422\n ],\n [\n -125.94726562499999,\n 28.459033019728043\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":852329,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70242153,"text":"70242153 - 2022 - Western U.S. geologic deformation model for use in the U.S. National Seismic Hazard Model 2023","interactions":[],"lastModifiedDate":"2023-04-10T11:52:49.463107","indexId":"70242153","displayToPublicDate":"2022-09-19T06:48:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Western U.S. geologic deformation model for use in the U.S. National Seismic Hazard Model 2023","docAbstract":"Fault geometry and slip rates are key input data for geologic deformation models, which are a fundamental component of probabilistic seismic hazard analyses (PSHAs). However, geologic sources for PSHA have traditionally been limited to faults with field‐based slip rate constraints, which results in underrepresentation of known, but partially characterized, active faults. Here, we evaluate fault geometries and geologic fault slip rates for the western United States to construct a new geologic deformation model for the U.S. National Seismic Hazard Model 2023 update (NSHM23). In previous NSHM iterations, only faults with published geologic slip rates were included. In the NSHM23 fault sections database compilation, this inclusion criterion was expanded to include faults without known slip rates. In this updated geologic deformation model, preferred slip rates and associated uncertainty distributions are incorporated for faults with slip rates derived from field studies. For faults without site‐specific slip rates, we evaluate a suite of uncertainty distributions derived from broad slip rate categories in the U.S. Geological Survey Quaternary Fault and Fold Database. Preferred slip rate distributions are selected via comparison with geodetic strain rates in tectonic subregions. The resultant moment of the geologic deformation model is generally in deficit compared with the geodetic moment within each region. Primary advances in the NSHM23 geologic deformation model include the following: (1) slip rates are presented as preferred values with uncertainties rather than single values; (2) the representation of the western U.S. active fault network is more complete; and (3) the geologic deformation model leverages geodetic information to assess regional constraints on geologic fault slip rates.
Mason Spur is a deeply eroded Middle Miocene to Pleistocene (c. 13 to 0.37 Ma) volcanic complex in southern Victoria Land, within the West Antarctic Rift System (WARS). The oldest rocks include a large volume of trachyte ignimbrites that provided abundant volcanic detritus recovered in McMurdo Sound drill cores. The ignimbrites together with early-formed intrusions were strongly deformed during a substantial caldera collapse at c. 13 Ma. Intense erosion modified the volcanic landscape, creating a paleo-relief of several hundred metres. Deep ravines were cut and filled by deposits of multiple lahars probably linked to gravitational collapses of trachyte dome(s). Small-volume trachytic magmas were also erupted, forming lavas and at least one tuff cone. The youngest trachytic activity comprises a lava dome and related block-and-ash-flow deposits, erupted at 6 Ma. Basanite erupted throughout the history of the complex and eruptions younger than 12 Ma are almost exclusively basanite, forming scoria cones, water-cooled lavas, and tuff cones. Three peripheral outcrops are composed of basanitic ‘a‘ā lava-fed deltas, probably erupted from vents on neighbouring volcanoes at Mount Discovery and Mount Morning. Abundant ignimbrite deposits at Mason Spur differentiate this volcanic complex from others in the WARS. Eruptions were triggered by rift extension initially, yielding the voluminous trachytes sourced from a magma chamber on the margin of the WARS. Later mafic eruptions were associated with deep crustal faults related to residual intraplate deformation. These results add important details to the eruptive history of the intracontinental WARS.
This study presents Raman spectroscopic data paired with scanning electron microscopy (SEM) images to assess solid bitumen composition as a function of solid bitumen texture and association with minerals. A series of hydrous pyrolysis experiments (1–103 days, 300–370 °C) using a low maturity (0.25% solid bitumen reflectance, BRo), high total organic carbon [(TOC), 14.0 wt%] New Albany Shale sample as the starting material yielded pyrolysis residues designed to evaluate the evolution of solid bitumen aromaticity with increasing temperature and heating duration. Solid bitumen was analyzed by Raman spectroscopy wherein point data were collected from accumulations that ranged in size and degree of association with the mineral matrix. Raman spectroscopy results show that with increasing temperature and experimental duration, solid bitumen aromaticity increases and compositional variability decreases. With regards to texture and composition, coarser-grained solid bitumen (>1.3 μm from nearest mineral grain) has consistently higher, but less variable aromaticity than thinner, wispy solid bitumen which is more intimately associated with the mineral matrix. Collocated scanning electron microscope images were used to provide qualitative assessments of porosity hosted by the organic matter. These paired data sets suggest that solid bitumen porosity development and molecular composition are linked, and these parameters are related to the textural relationships of the organic matter within the whole rock. These results are discussed with perspective towards understanding how rock fabric and texture can influence organic matter evolution during thermal maturation of organic-rich marine shales and inform our broader understanding of these important energy resources.
The Loch Vale Watershed Research and Monitoring Program collects long-term datasets of ecological and biogeochemical parameters in Rocky Mountain National Park to support both (1) management of this protected area and (2) research into watershed-scale ecosystem processes as those processes respond to atmospheric deposition and climate variability. The program collects data on precipitation depth and atmospheric deposition chemistry—as well as surface water biogeochemistry—within the watershed and in other areas of the park. These data are used by resource managers, scientists, policy makers, and students, so it is important that all collected data meet high quality standards. This report presents an evaluation of data quality for precipitation, atmospheric ammonia, and surface water quality samples collected from 2010 to 2019. This report also presents changes made to the monitoring and laboratory equipment used during the study period and describes new data streams added to the project, including atmospheric ammonia, surface water chlorophyll-a, and dissolved oxygen in two lakes: The Loch and Sky Pond.
Quality-assurance procedures looked at the accuracy and precision of measurements made over the study period and found that precipitation and surface water chemistry data were 99 percent accurate and precise. Records that failed to meet quality standards were removed from published databases. From 2010 to 2014, a colocated precipitation gauge and deposition collector were installed on site as quality checks. From 2014 to 2018, power loss at the site resulted in significant loss of precipitation data records during the snow seasons. Those problems were addressed by installing new solar-power equipment in 2019. Measurements of deposition chemistry, atmospheric ammonia deposition, and surface water biogeochemistry were all sufficiently complete and consistent to support project data needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D9","usgsCitation":"Weinmann, T., Baron, J.S., and Jayo, A., 2022, Quality assurance report for Loch Vale Watershed, 2010–19: U.S. Geological Survey Techniques and Methods 1–D9, 21 p., https://doi.org/10.3133/tm1D9.","productDescription":"Report: viii, 21 p.; Data Release; Database","onlineOnly":"Y","ipdsId":"IP-127394","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":406494,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d9/coverthb.jpg"},{"id":406495,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d9/tm1d9.pdf","text":"Report","size":"2.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 1-D9"},{"id":406498,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92ULNAG","text":"USGS data release","linkHelpText":"Climatological data for the Loch Vale watershed in Rocky Mountain National Park, Colorado, water years 1992–2019"},{"id":406738,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/01/d9/images"},{"id":406739,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/01/d9/tm1d9.xml"},{"id":406741,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://nadp.slh.wisc.edu/","text":"National Atmospheric Deposition Program [NADP], 2021, National Atmospheric Deposition Program web page—","linkHelpText":"accessed August 17, 2021"},{"id":406742,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://www2.nrel.colostate.edu/projects/lvws/index.html","text":"National Resource Ecology Lab [NREL], 2011, Loch Vale Watershed—Long-term Ecological Research and Monitoring Program: National Resource Ecology Laboratory web page—","linkHelpText":"accessed April 15, 2021"},{"id":406744,"rank":9,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation—","linkHelpText":"U.S. Geological Survey National Water Information System database, accessed July 28, 2021"},{"id":406743,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://co.water.usgs.gov/lochvale/","text":"Water, Energy, and Biochemical Budgets (WEBB)—Loch Vale Watershed: Colorado Water Science Center web page—","linkHelpText":"accessed July 13, 2021"}],"country":"United States","state":"Colorado","otherGeospatial":"Loch Vale Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.292724609375,\n 39.605688178320804\n ],\n [\n -105.01281738281249,\n 39.605688178320804\n ],\n [\n -105.01281738281249,\n 40.56806745430726\n ],\n [\n -106.292724609375,\n 40.56806745430726\n ],\n [\n -106.292724609375,\n 39.605688178320804\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
This report summarizes data-collection activities associated with the U.S. Geological Survey Humboldt Bay Water-Quality and Salt Marsh Monitoring Project. This work was undertaken to gain a comprehensive understanding of water-quality conditions, salt marsh accretion processes, marsh-edge erosion, and soil-carbon storage in Humboldt Bay, California. Multiparameter sondes recorded water temperature, specific conductance, and turbidity at a 15-minute timestep at two U.S. Geological Survey water-quality stations: (1) Mad River Slough near Arcata, California (U.S. Geological Survey station 405219124085601) and (2) Hookton Slough near Loleta, California (U.S. Geological Survey station 404038124131801). At each station, discrete water samples were collected to develop surrogate regression models that were used to compute a continuous time series of suspended-sediment concentration from continuously measured turbidity. Data loggers recorded water depth at a 6-minute timestep in the primary tidal channels (Mad River Slough and Hookton Slough) in two adjacent marshes (Mad River marsh and Hookton marsh). The marsh monitoring network included five study marshes. Three marshes (Mad River, Manila, and Jacoby) are in the northern embayment of Humboldt Bay and two marshes (White and Hookton) are in the southern embayment. Surface deposition and elevation change were measured using deep rod surface elevation tables and feldspar marker horizons. Sediment characteristics and soil-carbon storage were measured using a total of 10 shallow cores, distributed across 5 study marshes, collected using an Eijkelkamp peat sampler. Rates of marsh edge erosion (2010–19) were quantified in four marshes (Mad River, Manila, Jacoby, and White) by estimating changes in the areal extent of the vegetated marsh plain using repeat aerial imagery and light detection and ranging (LiDAR)-derived elevation data. During the monitoring period (2016–19), the mean suspended-sediment concentration computed for Hookton Slough (50±20 milligrams per liter [mg/L]) was higher than Mad River Slough (18±7 mg/L). Uncertainty in mean suspended-sediment concentration values is reported using a 90-percent confidence interval. Across the five study marshes, elevation change (+1.8±0.6 millimeters per year [mm/yr]) and surface deposition (+2.5±0.5 mm/yr) were lower than published values of local sea-level rise (4.9±0.8 mm/yr), and mean carbon density was 0.029±0.005 grams of carbon per cubic centimeter. From 2010 to 2019, marsh edge erosion and soil carbon loss were greatest in low-elevation marshes with the marsh edge characterized by a gentle transition from mudflat to vegetated marsh (herein, ramped edge morphology) and larger wind-wave exposure. Jacoby Creek marsh experienced the greatest edge erosion. In total, marsh edge erosion was responsible for 62.3 metric tons of estuarine soil carbon storage loss across four study marshes. Salt marshes are an important component of coastal carbon, which is frequently referred to as “blue carbon.” The monitoring data presented in this report provide fundamental information needed to manage blue carbon stocks, assess marsh vulnerability, inform sea-level rise adaptation planning, and build coastal resiliency to climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221076","collaboration":"Prepared in cooperation with the California State Coastal Conservancy, California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service—Humboldt Bay National Wildlife Refuge","usgsCitation":"Curtis, J.A., Thorne, K.M., Freeman, C.M., Buffington, K.J., and Drexler, J.Z., 2022, A summary of water-quality and salt marsh monitoring, Humboldt Bay, California: U.S. Geological Survey Open-File Report 2022–1076, 30 p., https://doi.org/10.3133/ofr20221076.","productDescription":"Report: viii, 30 p.; 3 Data Releases","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-133425","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":501826,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113519.htm","linkFileType":{"id":5,"text":"html"}},{"id":406874,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221076/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":406865,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TVX0Z8","text":"Model archive summary for a suspended-sediment concentration surrogate regression model for station 405219124085601; Mad River Slough near Arcata, CA","description":"Curtis, J.A., 2021b, Model archive summary for a suspended-sediment concentration surrogate regression model for station 405219124085601; Mad River Slough near Arcata, CA: U.S. Geological Survey data release, https://doi.org/10.5066/P9TVX0Z8."},{"id":406863,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1076/images"},{"id":406864,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RJTAIL","text":"Model archive summary for a suspended-sediment concentration surrogate regression model for station 404038124131801; Hookton Slough near Loleta, CA","description":"Curtis, J.A., 2021a, Model archive summary for a suspended-sediment concentration surrogate regression model for station 404038124131801; Hookton Slough near Loleta, CA: U.S. Geological Survey data release, https://doi.org/10.5066/P9RJTAIL."},{"id":406866,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QLAL7B","text":"Salt marsh monitoring during water years 2013 to 2019, Humboldt Bay, CA—Water levels, surface deposition, elevation change, and soil carbon storage","description":"Curtis, J.A., Thorne, K.M., Freeman, C.M., Buffington, K.J., and Drexler, J.Z., 2022, Salt marsh monitoring during water years 2013 to 2019, Humboldt Bay, CA—Water levels, surface deposition, elevation change, and soil carbon storage: U.S. Geological Survey data release, https://doi.org/10.5066/P9QLAL7B."},{"id":406860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1076/covrthb.jpg"},{"id":406861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1076/ofr20221076.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":406862,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1076/ofr20221076.xml"}],"country":"United States","state":"California","otherGeospatial":"Humboldt Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.35699462890624,\n 40.55972134684838\n ],\n [\n -124.0191650390625,\n 40.55972134684838\n ],\n [\n -124.0191650390625,\n 40.97678774053031\n ],\n [\n -124.35699462890624,\n 40.97678774053031\n ],\n [\n -124.35699462890624,\n 40.55972134684838\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Preliminary models for gate operations at the new outlet control structure for Reelfoot Lake were developed by the U.S. Geological Survey, using calibrated ratings of the lift gates, to support the U.S. Fish and Wildlife Service in managing lake level. In 2018, the old structure at the outlet of Reelfoot Lake was buried and lake level control was transferred to a new structure. The transition from lake-level management of the old control structure to the new control structure was documented using historical lake level and discharge measurements and records of stop-log management from March 7, 2013, to August 12, 2018. Discharge into Running Reelfoot Bayou was determined using a standard stage-discharge rating curve. Discharge measured using an acoustic Doppler current profiler was used to calibrate gate-discharge equations for free and submerged orifice flow at the new structure.
Two lake operation models, one for the summer season and another for the winter season, are provided for the new structure based on data from this period. The summer operation model is based on operation of the gates once the lake level exceeds an elevation of 282.7 feet (ft) above the North American Vertical Datum of 1988 (NAVD 88). Free flow begins when lake level reaches 282.3 ft above NAVD 88 and becomes transitional once the lake level exceeds 282.8 ft above NAVD 88. Submerged flow begins once the lake level reaches 283 ft above NAVD 88 and the tail-water depth is above critical flow depth. The winter operation model is based on operation of the gates once the lake level exceeds 283.2 ft above NAVD 88. Submerged flow begins when the lake rises to an elevation of 283.5 ft above NAVD 88 and the tail-water depth is above critical flow depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20221073","collaboration":"Prepared in cooperation with the Tennessee Wildlife Resources Agency","usgsCitation":"Heal, E.N., Diehl, T.H., and Garrett, J.W., 2022, Preliminary models relating lake level gate operation and discharge at Reelfoot Lake in Tennessee and Kentucky: U.S. Geological Survey Open-File Report 2022–1073, 27 p., https://doi.org/10.3133/ofr20221073.","productDescription":"Report: vii, 27 p.; Data Release; Database","onlineOnly":"Y","ipdsId":"IP-103756","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":406684,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GY1UF4","text":"USGS data release","linkHelpText":"Preliminary model data for lake level gate operation and discharge at Reelfoot Lake—Tennessee and Kentucky"},{"id":501823,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113520.htm","linkFileType":{"id":5,"text":"html"}},{"id":406683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1073/ofr20221073.pdf","text":"Report","size":"2.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1073"},{"id":406682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1073/coverthb.jpg"},{"id":406685,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation—","linkHelpText":"U.S. Geological Survey National Water Information System database"},{"id":406844,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1073/images"},{"id":406845,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1073/ofr20221073.xml"},{"id":409059,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221073/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1073"}],"country":"United States","state":"Kentucky, Tennessee","otherGeospatial":"Reelfoot Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.46441650390625,\n 36.30350540784278\n ],\n [\n -89.25155639648438,\n 36.30350540784278\n ],\n [\n -89.25155639648438,\n 36.52453591500483\n ],\n [\n -89.46441650390625,\n 36.52453591500483\n ],\n [\n -89.46441650390625,\n 36.30350540784278\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Sandbars are an important resource in the Colorado River corridor in Marble and Grand Canyons, Arizona, downstream from Glen Canyon Dam. Sandbars provide aquatic and riparian habitat and are used as campsites by river runners and hikers. The study area is the Colorado River between Glen Canyon Dam and Diamond Creek, which is about 388 kilometers (241 miles) downstream from the dam. Closure of Glen Canyon Dam in 1963 and subsequent flow regulation reduced the sediment supply, limited the magnitude and frequency of floods, and increased the magnitude of baseflows. The result has been widespread erosion of sandbars and expansion of native and non-native vegetation on previously bare sand deposits in this debris-fan dominated canyon river. This study reports on the on-going long-term measurement program of Northern Arizona University, initiated in 1990 with the Bureau of Reclamation, and now also with the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center. We report on all sandbar measurements made between 1990 and 2020 to demonstrate the multi-decadal response of the sandbar monitoring sites resulting from flow regulation by Glen Canyon Dam. Because only one study site is located in Glen Canyon, the 25 kilometer (15.5 miles) reach just below Glen Canyon Dam, analyses of sandbar response are only made for the next two canyon segments in the down-river direction, Marble Canyon (388 kilometers [99 miles]) and Grand Canyon (265 kilometers [165 miles]), respectively, where the majority of study sites are located.
We show that a majority of monitoring sites increased in volume during a period of frequent controlled floods intended to rebuild sandbars. In the period from 2004 to 2020, which included seven controlled floods, a median discharge of 350 cubic meters per second (m3/s), and greater than average tributary sand inputs in more than half of the years, net deposition occurred at 86 percent of long-term monitoring sites. This period was preceded by a period of net erosion (1990–2003) when there was one controlled flood greater than the nominal powerplant capacity of 940 m3/s. During this period the median discharge from Glen Canyon Dam was 376 m3/s and greater than average sand inputs occurred in only 36 percent of those years. At the end of the monitoring period in 2020, 61 percent of the study sites measured since 1990 underwent a net increase in sand volume. For the entire 31-year period, these trends were statistically significant for all six sandbar types studied, indicating that increased frequency of controlled flooding maintained sandbar volume at the majority of sites monitored. These floods, also referred to as high-flow experiments (HFEs), are part of a decision-making protocol approved in 2012 for coordinating dam releases timed to occur following large sand inputs to the Colorado River by a major tributary.
These findings are based on digital elevation models (DEMs) derived from approximately (~)1,800 repeat surveys of sandbar and channel bed topography made annually, or more frequently, at the 45 long-term monitoring sites, of which 31 have been monitored since 1990 and 14 were added between 1990 and 2008. This large collection of monitoring sites comprises just 7 to 9 percent of all sandbars in Marble and Grand Canyons, respectively. Nevertheless, when compared with measurements of a larger sample, these sites provide consistent characterization of average sandbar response, despite the local variability in channel and debris fan geometry. We use sand volume and normalized sand volume for tracking geomorphic changes of sandbars, because these metrics are sensitive to both changes in sandbar area and sandbar elevation. Based on checkpoint comparisons and repeat measurements, DEM elevation uncertainty was determined to be ±0.05 meter (m) and this uncertainty was used in a spatially uniform estimate of volume uncertainty. We find that the magnitudes of the topographic changes were substantially greater than the measurement uncertainty.
Sandbars of similar type throughout both Marble and Grand Canyons have responded similarly during the period of the HFE protocol, despite variations in sand supply and longitudinal extent of those inputs. It should be noted that tributary-supplied sand to Glen Canyon is negligible, much of the riverbed is now armored with cobbles, and the channel bed degradation is irreversible in the current flow and sediment supply regime. Because all these HFEs have been conducted during periods of sediment enrichment, other factors such as vegetation and geomorphic setting are likely the primary causes of variation among the monitoring sites. A larger percentage of the sandbar population, predominantly located in narrow reaches where stage changes are greater, is composed of sandbar types that remain dynamic and consistently aggrade during HFEs. In contrast, wide reaches of the river corridor where stage change is not as great are characterized by sandbars that have been stabilized by vegetation and progressive aggradation during floods. In the former case, a majority of sandbars are likely to remain dynamic, requiring continued use of HFEs to achieve desired management goals. In the latter case, HFEs can do no better than replace the sediment eroded during normal dam operation between high-flow events, as they become less effective because of a diminishing amount of accommodation space available for deposition. Long-term sandbar trajectory and the continued effectiveness of HFEs are related to the differential vegetation establishment at each bar type. Future sandbar monitoring may need to consider the effects of riparian vegetation removal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1873","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Hazel, J.E., Jr., Kaplinski, M.A., Hamill, D., Buscombe, D., Mueller, E.R., Ross, R.P., Kohl, K., and Grams, P.E., 2022, Multi-decadal sandbar response to flow management downstream from a large dam—The Glen Canyon Dam on the Colorado River in Marble and Grand Canyons, Arizona: U.S. Geological Survey Professional Paper 1873, 104 p., https://doi.org/10.3133/pp1873.","productDescription":"Report: ix, 104 p.; Data Release","numberOfPages":"104","onlineOnly":"Y","ipdsId":"IP-123041","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501887,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113518.htm","linkFileType":{"id":5,"text":"html"}},{"id":406788,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93F8JJK","text":"Long-term sandbar monitoring data along the Colorado River in Marble and Grand Canyons, Arizona","description":"Grams, P.E., Hazel, J.E., Jr., Kaplinski, M.A., Ross, R.P., Hamill, D., Hensleigh, J., and Gushue, T., 2020, Long-term sandbar monitoring data along the Colorado River in Marble and Grand Canyons, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P93F8JJK."},{"id":406787,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1873/pp1873.pdf","text":"Report","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":406786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1873/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam, Marble Canyon, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.06005859375,\n 35.35321610123823\n ],\n [\n -111.42333984375,\n 35.35321610123823\n ],\n [\n -111.42333984375,\n 36.79169061907076\n ],\n [\n -114.06005859375,\n 36.79169061907076\n ],\n [\n -114.06005859375,\n 35.35321610123823\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chronic wasting disease (CWD) is a fatal prion disease affecting cervids (deer, elk, moose). Current methods to monitor individual disease state include highly invasive antemortem rectal biopsy or postmortem brain biopsy. Efficient, sensitive, and selective antemortem and postmortem testing of populations would increase knowledge of the dynamics of CWD epizootics as well as provide a means to track CWD progression into previously unaffected areas. Here, we analyzed the presence of CWD prions in skin samples from two easily accessed locations (ear and belly) from 30 deceased white-tailed deer (Odocoileus viginianus). The skin samples were enzymatically digested and analyzed by real-time quaking-induced conversion (RT-QuIC). The diagnostic sensitivity of the ear and belly skin samples were both 95%, and the diagnostic specificity of the ear and belly skin were both 100%. Additionally, the location of the skin biopsy on the ear does not affect specificity or sensitivity. These results demonstrate the efficacy of CWD diagnosis with skin biopsies using RT-QuIC. This method could be useful for large scale antemortem population testing.
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\"}}]}","volume":"17","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Burgener, Kate","contributorId":338037,"corporation":false,"usgs":false,"family":"Burgener","given":"Kate","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lichtenberg, Stuart Siegfried","contributorId":338040,"corporation":false,"usgs":false,"family":"Lichtenberg","given":"Stuart","email":"","middleInitial":"Siegfried","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":936245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lomax, Aaron","contributorId":338045,"corporation":false,"usgs":false,"family":"Lomax","given":"Aaron","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storm, Daniel J.","contributorId":341059,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":936247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pedersen, Joel","contributorId":338048,"corporation":false,"usgs":false,"family":"Pedersen","given":"Joel","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936249,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238951,"text":"70238951 - 2022 - Mass wasting along the Cascadia subduction zone: Implications for abyssal turbidite sources and the earthquake record","interactions":[],"lastModifiedDate":"2022-12-19T14:18:12.446472","indexId":"70238951","displayToPublicDate":"2022-09-16T08:12:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mass wasting along the Cascadia subduction zone: Implications for abyssal turbidite sources and the earthquake record","docAbstract":"The only submarine records of large (>Mw7) prehistoric earthquakes along the Cascadia subduction zone are derived from sequences of deep sea turbidites interpreted to represent synchronous, shaking-induced failures along the continental slope. However, the spatial correlation of these deposits along the margin is complicated and the chronological constraints involve significant uncertainties, raising questions about how these deposits were generated. Here we present the most comprehensive spatial database of seafloor failure scarps across the Cascadia margin to date, with more than 8700 features mapped. We observe pervasive mass wasting of the steep lower slope along the ∼800 km length of the margin. This portion of the margin is heavily deformed, uplifted and oversteepened, such that it may be optimally preconditioned to fail during intense shaking events. Our results suggest disintegration of the steep lower slope is likely the primary source of turbidity flows triggered by earthquake shaking in Cascadia. This more proximal source for seismoturbidite generation may be the principal process along subduction margins with steep lower slope topography and may explain why seismoturbidites are found in areas containing few submarine canyons. Furthermore, the extensive mass wasting present on the steep lower slope of central Cascadia, a critical 250 km long section where no records currently exist, suggests additional turbidite records may be found along this portion of the margin by selecting optimal sample sites based on failure patterns. The strong clustering of seafloor failures along the lower slope also suggests the most earthquake intense shaking may be spatially restricted to a narrow zone along the deformation front, which could have important implications for hazard predictions across the region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2022.117797","usgsCitation":"Hill, J.C., Watt, J., and Brothers, D., 2022, Mass wasting along the Cascadia subduction zone: Implications for abyssal turbidite sources and the earthquake record: Earth and Planetary Science Letters, v. 597, 117797, 14 p., https://doi.org/10.1016/j.epsl.2022.117797.","productDescription":"117797, 14 p.","ipdsId":"IP-141994","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446416,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2022.117797","text":"Publisher Index Page"},{"id":410701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 48.5\n ],\n [\n -128,\n 48.5\n ],\n [\n -128,\n 41\n ],\n [\n -123,\n 41\n ],\n [\n -123,\n 48.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"597","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":859334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236831,"text":"70236831 - 2022 - You vs. us: Framing adaptation behavior in terms of private or social benefits","interactions":[],"lastModifiedDate":"2022-09-20T12:13:12.624844","indexId":"70236831","displayToPublicDate":"2022-09-16T07:10:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"You vs. us: Framing adaptation behavior in terms of private or social benefits","docAbstract":"Private actions to mitigate and adapt to climate change may have benefits to both the individual and society. In some cases, an individual may be motivated by appeals that highlight benefits to others, rather than to oneself. We test whether such prosocial framing influences information-seeking behavior to address wildfire risk among homeowners. In a field experiment across ten communities in western Colorado, property owners (n = 2977) received a postcard from their local fire department highlighting the impact of risk mitigation to either “your property” (private benefits) or “our community” (social benefits). The postcard directed recipients to visit a personalized webpage on wildfire risk. Overall, 10.5% of property owners visited their personalized risk webpage. There was little difference in webpage visitation between those who received the social (11.3%) rather than the private (9.7%) benefits message (χ2 = 1.74, p = 0.19). However, response may depend on a property owner’s relationship to the community. Those who reside within the community (as opposed to out-of-town owners) or who were in an evacuation zone during a recent wildfire were more likely to visit their webpages after receiving the social benefits message. How homeowners view their contributions to shared risk and whether simple changes in messaging influence prosocial behavior can inform efforts to address climate-exacerbated hazards.
Dissolved atmogenic gasses in groundwater provide significant information about recharge conditions, flowpath, and age. Free phase gas in aquifers is largely ignored in these analyses and there is a lack of quantitative analysis for gas flux mechanisms. Many related fields encountering multiphase flow acknowledge that the presence of bubbles allows for the rapid exsolution of dissolved gasses and volatile compounds through diffusive and polar forces. By measuring the mass flow of the exsolved gas at a spring, coupled with compositional analysis in the free and dissolved phases, we show that not incorporating the effects of the free gas phase of bubbling springs introduces error in the estimation of total gas quantities, particularly light noble gasses. This can significantly affect the corresponding estimation of noble gas temperature (NGT) and apparent age. We examine the transport of free and dissolved gas from the recharge zone, using water level variation data, to the discharge location where the gases are measured. This technique of using the free gas phase for assessing aquifer dynamics will improve groundwater conceptual models, particularly in karstic aquifers where rapid fluctuations in the water table facilitate the development of excess air, generating multiphase spring discharge.
Remote sensing geodetic observations (Interferometric Synthetic Aperture Radar [InSAR] and optical correlation [“pixel tracking”]) serve an increasingly diverse and important role in earthquake monitoring and response. This study introduces the Geodetic Centroid (gCent) catalog—an earthquake catalog derived solely from space‐based geodetic observations—and analysis of 74 earthquakes (MW4.3–7.4) imaged from 1 August 2019 to 01 February 2022. For gCent, we use InSAR and optical correlation observations derived from the Sentinel‐1 satellites and various publicly available optical satellites to systematically image all global earthquakes MW 5.5 or larger and shallower than 25 km, MW 7.0 or larger at any depth, and other high‐impact earthquakes or seismic events of special interest. We invert surface displacements from successfully imaged earthquakes for the location, orientation, and dimensions of a single slipping fault patch that describes the centroid characteristics of the earthquake. These centroid models, in turn, are compiled into a catalog and used in U.S. Geological Survey/Advanced National Seismic System (ANSS) operational earthquake response products such as ShakeMaps and finite‐fault models. We provide a comparison of the gCent catalog to the ANSS Comprehensive Catalog and Global Centroid Moment Tensor (Global CMT) catalog to compare reported locations, depths, and magnitudes. We find that global earthquake catalogs not only generally provide reasonably comparable locations (within 10 km on average), but also they systematically overestimate depth that may have implications for earthquake shaking predictions based solely on earthquake origin information. Geodetic magnitudes are comparable to seismically inferred magnitudes, indicating that gCent models are unlikely to be systematically biased by the presence of postseismic deformation. We additionally highlight limitations of the gCent catalog induced by both the limitations of remote sensing imaging of earthquakes and our imposition of a simplified earthquake source description that does not include spatially distributed slip.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220072","usgsCitation":"Barnhart, W.D., and Shea, H.N., 2022, The Geodetic Centroid (gCent) Catalog: Global earthquake monitoring with satellite imaging geodesy: Bulletin of the Seismological Society of America, v. 112, no. 6, p. 2646-2957, https://doi.org/10.1785/0120220072.","productDescription":"12 p.","startPage":"2646","endPage":"2957","ipdsId":"IP-139951","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"links":[{"id":502008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, William D. 0000-0003-0498-1697 wbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0003-0498-1697","contributorId":294678,"corporation":false,"usgs":true,"family":"Barnhart","given":"William","email":"wbarnhart@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":958504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shea, Hannah N.","contributorId":215980,"corporation":false,"usgs":false,"family":"Shea","given":"Hannah","email":"","middleInitial":"N.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":958610,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236658,"text":"sir20225076 - 2022 - Evaluation of sample preservation methods for analysis of selected volatile organic compounds in groundwater at the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2026-04-23T17:17:00.355623","indexId":"sir20225076","displayToPublicDate":"2022-09-15T10:37:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5076","displayTitle":"Evaluation of Sample Preservation Methods for Analysis of Selected Volatile Organic Compounds in Groundwater at the Idaho National Laboratory, Idaho","title":"Evaluation of sample preservation methods for analysis of selected volatile organic compounds in groundwater at the Idaho National Laboratory, Idaho","docAbstract":"During 2020, water samples were collected from 25 wells completed in the eastern Snake River Plain aquifer and from 1 well completed in perched groundwater above the aquifer at the Idaho National Laboratory to determine the effect of different sample-preservation methods on the laboratory determinations of concentrations of volatile organic compounds. Paired-sample sets were collected at each well. One sample in each set was preserved with hydrochloric acid, and one sample without. Both samples were chilled after collection and during shipping to the laboratory for analysis. The samples were analyzed for 61 volatile organic compounds at the U.S. Geological Survey National Water Quality Laboratory in cooperation with the U.S. Department of Energy. A comparison of the reproducibility of the analyses of co-located unpreserved and preserved samples by a relative percent difference method determined that all sample pairs were statistically equivalent. Using a normalized absolute difference method, 81 percent of the analyses were found to be statistically equivalent. This study confirms that the results of analyses of historical collected samples, which were preserved by chilling only, are statistically comparable to the analyses of samples being currently collected and preserved by both hydrochloric acid and chilling, and thus are valid for use in future geochemical evaluations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225076","collaboration":"DOE/ID-22257Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
This Memo to All Banders (MTAB 101) was released in September 2022. Subjects in this this memo are 1. The Chief’s Chirp; 2. Alerts – Highly Pathogenic Avian Influenza; 3. Staff updates – staff spotlight: BBL’s new contractor database manager; 4. News – Gamebirds Release, 1-Year Anniversary of Banders Without Borders, Latino Conservation Week, and Bander Portal Update Release; 5. A note from the permitting shelves; 6. A note from the supply room; 7. Data management – including important information regarding Bandit,, How to sign up for a Bander Portal account, why you should sign up for a bander portal account, and cleaning up your locations; 8. Banding and encounter highlights; 9. Auxiliary marker corner; 10. Message to the Flyways; 11. Message regarding the Banding Associations; 12. Moments in history; 13. Recent Publications; 14. Upcoming events; 15. Message from Canada’s Bird Banding Office; and 16. Request for information.
","language":"English","publisher":"U. S. Geological Survey","usgsCitation":"Harvey, K., and McKay, J.L., 2022, MTAB 101, September 2022: Memo to All Banders (MTAB), v. 101, 11 p.","productDescription":"11 p.","ipdsId":"IP-144775","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":406752,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/mtab-101-september-2022"},{"id":406759,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Kyra 0000-0003-4781-1874","orcid":"https://orcid.org/0000-0003-4781-1874","contributorId":296250,"corporation":false,"usgs":true,"family":"Harvey","given":"Kyra","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":851825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKay, Jennifer L. 0000-0002-8893-0231","orcid":"https://orcid.org/0000-0002-8893-0231","contributorId":296562,"corporation":false,"usgs":true,"family":"McKay","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":851826,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236675,"text":"70236675 - 2022 - Intra-site sources of restoration variability in severely invaded rangeland: Strong temporal effects of herbicide-weather interactions; weak spatial effects of plant-community patch type and litter","interactions":[],"lastModifiedDate":"2022-09-15T14:39:33.672311","indexId":"70236675","displayToPublicDate":"2022-09-15T09:32:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Intra-site sources of restoration variability in severely invaded rangeland: Strong temporal effects of herbicide-weather interactions; weak spatial effects of plant-community patch type and litter","docAbstract":"Anoxic conditions within reservoirs related to thermal stratification and oxygen depletion lead to methylmercury (MeHg) production, a key process governing the uptake of mercury in aquatic food webs. Once formed within a reservoir, the timing and magnitude of the biological uptake of MeHg and the relative importance of MeHg export in water versus biological compartments remain poorly understood. We examined the relations between the reservoir stratification state, anoxia, and the concentrations and export loads of MeHg in aqueous and biological compartments at the outflow locations of two reservoirs of the Hells Canyon Complex (Snake River, Idaho-Oregon). Results show that (1) MeHg concentrations in filter-passing water, zooplankton, suspended particles, and detritus increased in response to reservoir destratification; (2) zooplankton MeHg strongly correlated with MeHg in filter-passing water during destratification; (3) reservoir anoxia appeared to be a key control on MeHg export; and (4) biological MeHg, primarily in zooplankton, accounted for only 5% of total MeHg export from the reservoirs (the remainder being aqueous compartments). These results improve our understanding of the role of biological incorporation of MeHg and the subsequent downstream release from seasonally stratified reservoirs and demonstrate that in-reservoir physical processes strongly influence MeHg incorporation at the base of the aquatic food web.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.2c03958","usgsCitation":"Baldwin, A.K., Eagles-Smith, C., Willacker, J., Poulin, B., Krabbenhoft, D.P., Naymik, J., Tate, M., Bates, D., Gastelecutto, N., Hoovestol, C., Larsen, C.F., Yoder, A.M., Chandler, J.A., and Myers, R., 2022, In-reservoir physical processes modulate aqueous and biological methylmercury export from a seasonally anoxic reservoir: Environmental Science and Technology, v. 56, no. 19, p. 13751-13760, https://doi.org/10.1021/acs.est.2c03958.","productDescription":"10 p.","startPage":"13751","endPage":"13760","ipdsId":"IP-135446","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":446424,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.2c03958","text":"Publisher Index Page"},{"id":435690,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96E3DYN","text":"USGS data release","linkHelpText":"Biomass and methylmercury concentrations in biweekly biological samples from Brownlee and Oxbow Reservoir outflows, Snake River Hells Canyon Complex (Idaho-Oregon), 2018-2019"},{"id":406837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Brownlee Reservoir, Hells Canyon Reservoir, Oxbow Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3065185546875,\n 44.337600831495635\n ],\n [\n -117.12799072265625,\n 44.351350365612326\n ],\n [\n -116.400146484375,\n 45.596743928454124\n ],\n [\n -116.630859375,\n 45.625563438215984\n ],\n [\n -117.28179931640626,\n 44.69599298172069\n ],\n [\n -117.3065185546875,\n 44.337600831495635\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"19","noUsgsAuthors":false,"publicationDate":"2022-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":851934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":851935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":207883,"corporation":false,"usgs":true,"family":"Willacker","given":"James","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":851936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poulin, Brett 0000-0002-5555-7733","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":260893,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett","affiliations":[{"id":52706,"text":"Department of Environmental Toxicology, University of California Davis, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":851937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":851938,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naymik, Jesse","contributorId":229386,"corporation":false,"usgs":false,"family":"Naymik","given":"Jesse","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":851939,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":851940,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bates, Dain","contributorId":296596,"corporation":false,"usgs":false,"family":"Bates","given":"Dain","email":"","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":851941,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gastelecutto, Nick","contributorId":296597,"corporation":false,"usgs":false,"family":"Gastelecutto","given":"Nick","email":"","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":851942,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hoovestol, Charles","contributorId":229387,"corporation":false,"usgs":false,"family":"Hoovestol","given":"Charles","email":"","affiliations":[{"id":41632,"text":"Idaho Power Company","active":true,"usgs":false}],"preferred":false,"id":851943,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Larsen, Christopher F.","contributorId":147408,"corporation":false,"usgs":false,"family":"Larsen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":851944,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Yoder, Alysa Muir 0000-0002-3683-6729","orcid":"https://orcid.org/0000-0002-3683-6729","contributorId":296598,"corporation":false,"usgs":true,"family":"Yoder","given":"Alysa","email":"","middleInitial":"Muir","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":851945,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chandler, James A.","contributorId":210045,"corporation":false,"usgs":false,"family":"Chandler","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":38056,"text":"Idaho Power Company 1221 West Idaho Street, Boise, ID 83702","active":true,"usgs":false}],"preferred":true,"id":851947,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Myers, Ralph","contributorId":172701,"corporation":false,"usgs":false,"family":"Myers","given":"Ralph","email":"","affiliations":[{"id":12541,"text":"Idaho Power Company, P.O. Box 70, Boise ID 83707","active":true,"usgs":false}],"preferred":false,"id":851946,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70237916,"text":"70237916 - 2022 - Combining eddy covariance and chamber methods to better constrain CO2 and CH4 fluxes across a heterogeneous restored tidal wetland","interactions":[],"lastModifiedDate":"2022-11-01T12:26:20.958262","indexId":"70237916","displayToPublicDate":"2022-09-15T07:18:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8116,"text":"Journal of Geophysical Research-Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Combining eddy covariance and chamber methods to better constrain CO2 and CH4 fluxes across a heterogeneous restored tidal wetland","docAbstract":"Tidal wetlands play an important role in global carbon cycling by storing carbon in sediment at millennial time scales, transporting dissolved carbon into coastal waters, and contributing significantly to global CH4 budgets. However, these ecosystems' greenhouse gas monitoring and predictions are challenging due to spatial heterogeneity and tidal flooding. We utilized eddy covariance and chamber measurements to quantify fluxes of CO2 and CH4 at a restored tidal saltmarsh across spatial and temporal scales. Eddy covariance data revealed that the site was a strong net sink for CO2 (−387 g C-CO2 m−2 yr−1, SD = 46) and a small net source of CH4 (0.7 g C-CH4 m−2 yr−1, SD = 0.4). After partitioning net ecosystem exchange of CO2 into gross primary production and ecosystem respiration, we found that high net uptake of CO2 was due to low respiration emissions rather than high photosynthetic rates. We also found that respiration rates varied between land covers with increased respiration in mudflats compared to vegetated areas. Daytime soil chamber measurements revealed that the greatest CO2 emission was from higher elevation mudflat soils (0.5 μmol m−2s−1, SE = 1.3) and CH4 emission was greatest from lower elevation Spartina foliosa soils (1.6 nmol m−2s−1, SD = 8.2). Overall, these results highlight the importance of the relationships between wetland plant community and elevation, and inundation for CO2 and CH4 fluxes. Future research should include the use of high-resolution imagery, automated chambers, and a focus on quantifying carbon exported in tidal waters.
Multiple instruments and methods exist for collecting discrete streamflow measurements in small streams with low flows, defined here as less than 5.7 m3/s (200 ft3/s). Included in the available methods are low-cost approaches that are infrequently used, in part, because their uncertainty is not well known. In this work, we evaluated the accuracy and suitability of three low-cost velocity measurement methods (surface float [SF], velocity head rod [VR], and rising body [RB]) and three conventional current meters (acoustic Doppler velocimeter, and mechanical Price type AA and Price Pygmy meters) relative to discharge calculated from stable artificial hydraulic controls. A total of 231 measurements were made by 20 individuals during 88 site visits to 24 sites in eight states. Accuracies were assessed for all methods and precision was evaluated for the low-cost methods. The median percent error was below 5% for conventional methods, and below 20% for the low-cost methods. The SF was the most accurate (median absolute percent error 14%) and precise (mean percent precision of 11%) low-cost method. The RB and VR, respectively, had 15% and 20% median absolute percent error and 29% and 12% mean percent precision. Results suggest that low-cost methods, when used appropriately, can be used to estimate discharge data under low flow conditions when measurements with conventional methods are not feasible and the associated accuracies meet end-user measurement objectives.
We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California, in 2021. Surveys were completed at four locations: three downstream from Lake Henshaw, where surveys occurred from 2015 to 2020 (Rey River Ranch [RRR], Cleveland National Forest [CNF], Vista Irrigation District [VID]), and one at VID Lake Henshaw (VLH) that has been surveyed annually since 2018. There were 78 territorial flycatchers detected at 3 locations (RRR, CNF, VLH), and 1 transient flycatcher of unknown subspecies was detected at VID. Downstream from Lake Henshaw, five flycatchers, including three males and two females, were detected at RRR and CNF. In total, three territories were established, consisting of two pairs and one male of undetermined breeding status. At VLH, we detected 73 flycatchers, including 32 males, 38 females, and 3 flycatchers of unknown sex. In total, 43 territories were established, containing 38 pairs (22 monogamous pairings, 7 confirmed polygynous groups consisting of 7 males each pairing with 2 different females, and 1 suspected polygynous group consisting of 1 male and 2 females), and 5 flycatchers of undetermined breeding status (2 males and 3 flycatchers of unknown sex). Brown-headed cowbirds (Molothrus ater; cowbird) were detected at all four survey locations.
Flycatchers used five habitat types in the survey area: (1) mixed willow riparian, (2) willow-cottonwood, (3) willow-oak, (4) willow-ash, and (5) sycamore-oak. Eighty-seven percent of the flycatchers were detected in habitat characterized as mixed willow riparian, and 94 percent of the flycatchers were detected in habitat with greater than 95-percent native plant cover. Exotic vegetation was not prevalent in the survey area.
There were 15 nests incidentally located during surveys: 1 was successful, 2 were seen with eggs or nestlings on the last visit, 9 failed, and the outcome of the remaining 3 nests was unknown. Three of these nests were parasitized by cowbirds. There were 13 juveniles detected at VLH during surveys; no juveniles were detected at RRR or CNF.
Of the 10 banded flycatchers detected during surveys, 7 were resighted and confirmed to be adults that held territories in previous years. Three flycatchers with a single dark blue federal band, indicating that they were banded as nestlings in the former demographic study area downstream from Lake Henshaw, were resighted during surveys.
In 2021, we documented both adult and natal flycatchers moving from the former demographic study area downstream from Lake Henshaw upstream to the habitat surrounding Lake Henshaw. Three natal flycatchers that were originally banded as nestlings and three adults that previously held territories downstream dispersed to Lake Henshaw in 2021.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1158","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2022, Distribution and abundance of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Upper San Luis Rey River, San Diego County, California—2021 data summary: Data Report 1158, 11p., https://doi.org/10.3133/dr1158.","productDescription":"Report: viii, 11 p.; Data Release","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-136841","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":406717,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1158/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1158"},{"id":405654,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1158/dr1158.xml"},{"id":405655,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1158/images"},{"id":405652,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1158/dr1158.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":405651,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1158/covrthb.jpg"},{"id":405649,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California","description":"Howell, S.L., and Kus, B.E., 2022, Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California: U.S. Geological Survey data release, available at https://doi.org/10.5066/P96VC5Y4."}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.86363220214844,\n 33.18641002415405\n ],\n [\n -116.69677734375,\n 33.18641002415405\n ],\n [\n -116.69677734375,\n 33.30585555262747\n ],\n [\n -116.86363220214844,\n 33.30585555262747\n ],\n [\n -116.86363220214844,\n 33.18641002415405\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819