The Great Basin in the western United States hosts various hydrothermal systems, including both active geothermal systems and ancient systems preserved as mineral deposits. New magnetotelluric and structural geologic data were collected in the Gabbs Valley area of western Nevada to demonstrate the advantage of imaging the full crustal column below known hydrothermal systems. Three-dimensional models are developed and jointly interpreted where the key findings are bottom-up and top-down controls on hydrothermal systems. Bottom-up control is dictated by weaknesses in the brittle-ductile transition that allow hydrothermal fluids to propagate into the crust; these are often collocated with Miocene volcanic structures. Top-down control is dominated by modern Walker Lane and Basin and Range tectonics that control fluid transport through the middle and upper crust. This study demonstrates that the characterization of regional mineral and geothermal resources is better informed by imaging lower crustal structures and preferential pathways to the surface.
Artificial neural networks (ANNs) are adaptable systems that can solve problems that are difficult to describe with a mathematical relationship. They seek relationships between different types of datasets with their abilities to learn either with supervision or without. ANNs recognize patterns between input and output space and generalize solutions, in a way simulating the human brain’s learning experience with many relatively simple individual processing elements, called neurons. Neurons are networked (network topology) in a number of ways depending on the problem type and complexity. One of the most widely used ANN learning techniques is supervised learning coupled with a multilayer perceptron (MLP) topology due to its flexible applicability to a wide range of modeling problems involving both general classification and regression. ANNs, due to this flexibility, have been applied to many fields since the 1990s and their theory, types (such as radial basis functions, random...
Anas acuta (Northern pintail; hereafter pintail) was selected as a model species on which to base a decision-support framework linking regional actions to continental-scale population and harvest objectives. This framework was then used to engage stakeholders, such as Landscape Conservation Cooperatives’ (LCCs’) habitat management partners within areas of importance to pintails, while maximizing cross-taxa effects from the framework. The mathematical framework for the model had been previously developed for pintails. A key assumption incorporated into the model is that density dependence in survival occurs during the post-hunting (winter) period, where resources are hypothesized to be limiting. Because few data are available to directly inform this process, the approach used was to build a hierarchical Bayesian integrated population model (IPM) that simultaneously uses data from bird-band recoveries, breeding population counts, and harvest surveys to estimate values of parameters of an annual population projection model, including population size, survival rate, reproductive rate, and process and observation error variances, that are logically consistent with each other, given the mathematical structure imposed through the IPM.
The main accomplishments of this study are (1) development of an IPM for pintail to guide harvest and habitat management, (2) development of a Prairie Parkland Region breeding submodel to predict pintail productivity, (3) development of statistical methodology to estimate pintail productivity (as measured by the ratio of juvenile to adults in hunter-collected wing samples) and winter survival and to relate these estimates to covariates, and (4) illustration of how to use a model and estimated parameter values to predict pintail population size and sustainable harvest as a function of habitat.
Estimation of pintail survival from bird-banding data shows that there has been relatively little variation in survival over the period 1960–2013. A productivity model showed strong effects of breeding ground conditions, wintering-ground precipitation, and density dependence on pintail productivity. Thus, most temporal variation in pintail demographic rates has been due to effects on reproduction and not survival, including effects of breeding or wintering-ground habitat. These results indicate that habitat conservation efforts may be most effective if they focus on maintaining or increasing breeding and wintering-ground habitat to increase pintail productivity rather than pintail survival. Environmental perturbations in excess of historical experience, such as what could occur under climate change, might have meaningful effects on survival but cannot be estimated with current data. Direct effects of climate, land use, or management are likely to be greater on productivity than survival, but substantial uncertainty remains about predictions of equilibrium population size and sustainable yield.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201084","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Osnas, E.E., Boomer, G.S., Devries, J.H., and Runge, M.C., 2021, Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species: U.S. Geological Survey Open-File Report 2020–1084, 31 p., https://doi.org/10.3133/ofr20201084.","productDescription":"Report: vi, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083951","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":391433,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93YTR3X","text":"USGS data release","linkHelpText":"Data release—Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species"},{"id":391431,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1084/coverthb.jpg"},{"id":391432,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1084/ofr20201084.pdf","text":"Report","size":"6.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1084"}],"contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
The Digital Shoreline Analysis System version 5 software is an add-in to Esri ArcGIS Desktop version 10.4–10.7 that enables a user to calculate rate-of-change statistics from a time series of vector shoreline positions. The Digital Shoreline Analysis System provides an automated method for establishing measurement locations, performs rate calculations, provides the statistical data necessary to assess the reliability of the rates, and includes a beta model for forecasting shoreline position. The Digital Shoreline Analysis System version 5.1 includes updates to the interface and the application of proxy-datum bias. This in-depth user guide provides comprehensive instruction on the installation and use of the program, including how to create a reference baseline for measurements, steps needed to generate measurement transects and metadata, guidelines on how to manually add or edit existing transects, and an explanation of the visualization options to display calculated rates of shoreline change.
Note: As of May 2024, the current version of the Digital Shoreline Analysis System (DSAS), version 6.0, is a standalone desktop application for calculating shoreline or boundary change over time. The user guide for DSAS version 5.1 is applicable to many aspects of version 6.0. The user guide provides relevant information on the DSAS workflow, including how to define a reference baseline for measurements, attribute requirements for baselines and shorelines, and supporting information on rate calculations and statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211091","usgsCitation":"Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2021, Digital Shoreline Analysis System (DSAS) version 5.1 user guide: U.S. Geological Survey Open-File Report 2021–1091, 104 p., https://doi.org/10.3133/ofr20211091.","productDescription":"Report: xi, 104 p.; Software Release","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123671","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":390774,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas","text":"Digital Shoreline Analysis System (DSAS)"},{"id":390775,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P13WIZ8M","text":"Digital Shoreline Analysis System version 6.0"},{"id":390767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1091/ofr20211091.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1091"},{"id":390766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1091/coverthb.jpg"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Wildfire-induced changes to soil and vegetation promote runoff-generated debris flows in steep watersheds. Postfire debris flows are most commonly observed in steep watersheds during the first wet season following a wildfire, but it is unclear how long the elevated threat of debris flow persists and why debris-flow potential changes in recovering burned areas. This work quantifies how rainfall intensity-duration (ID) thresholds for debris-flow initiation change with time since burning and provides a mechanistic explanation for these changes. We constrained a hydrologic model using field and remotely sensed measurements of soil-infiltration capacity, vegetation cover, runoff, and debris-flow activity. We applied this model to estimate rainfall ID thresholds for debris-flow initiation within three burned areas in the southwestern United States over a postfire recovery period of three to four years. Modeling suggests ID thresholds are lowest immediately following the fire (below a one-year recurrence interval [RI] storm) and increase with time, such that a 10- to 25-year RI storm would be required to generate a debris flow after three years of recovery. Modeled changes in rainfall ID thresholds result from increases in soil infiltration capacity, canopy interception, hydraulic roughness, and median grain size of sediment entrained in an incipient debris flow. The relative importance of each of these factors varied among our three sites. Results improve our ability to assess temporal changes in postfire debris-flow potential, highlight how site-specific factors may alter the persistence of postfire debris-flow hazards, and provide additional constraints on the timescale of recovery following wildfire.
During September and October 2019, the U.S. Geological Survey mapped the shoreface and inner continental shelf offshore of the Rockaway Peninsula in New York using high-resolution chirp seismic reflection and single-beam bathymetry geophysical techniques. The results from this study are important for assessing the Quaternary evolution of the Rockaway Peninsula and determining coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles and maps of shoreface and Holocene sediment thickness from the shoreline to about 2 kilometers offshore. The results indicate that shoreface and Holocene sediment thickness demonstrates zonal variability because of underlying geology and sediment availability. Based on geomorphic features and underlying stratigraphy, the study area is separated into west, west-central, east-central, and east zones. Holocene sediment, which includes the shoreface and seafloor features with positive morphology (for example, nearshore bars, ebb-tide deltas, and sorted bedforms), thickens to the west and may be related to accommodation and westward dip of the regional unconformity. Shoreface units, which are thought to represent the active volume of littoral sediment, are thickest in the west-central peninsula where the geologic base of the shoreface is deeper. Shoreface units with moderate thickness are in the western and eastern peninsula where there are positive morphological features (for example, deposits accumulating updrift from the jetty, ebb-tide deltas, and so on). The thinnest shorefaces are in the east-central Rockaway Peninsula because of less accommodation caused by the shoaling regional unconformity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211100","collaboration":"Prepared in cooperation with the National Fish and Wildlife Foundation","usgsCitation":"Wei, E.A., Miselis, J.L., and Forde, A.S., 2021, Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York: U.S. Geological Survey Open-File Report 2021–1100, 14 p., https://doi.org/10.3133/ofr20211100.","productDescription":"Report: iv, 14 p.; 2 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125818","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391426,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211100/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1100/images/"},{"id":391343,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZO8QKJ","linkHelpText":"Archive of chirp subbottom profile data collected in 2019 from Rockaway Peninsula, New York"},{"id":391346,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.XML"},{"id":391344,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WNJSFN","linkHelpText":"Coastal bathymetry and backscatter data collected in September and October 2019 from Rockaway Peninsula, New York"},{"id":391342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1100"},{"id":391341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1100/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Rockaway Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.76152038574219,\n 40.57067539946112\n ],\n [\n -73.74229431152344,\n 40.593620934177494\n ],\n [\n -73.76083374023438,\n 40.59414233212419\n ],\n [\n -73.82469177246094,\n 40.58527801407785\n ],\n [\n -73.8885498046875,\n 40.563372896916164\n ],\n [\n -73.92974853515625,\n 40.549287249082035\n ],\n [\n -73.94622802734375,\n 40.53937335015618\n ],\n [\n -73.9441680908203,\n 40.529979881843865\n ],\n [\n -73.92974853515625,\n 40.526326510744006\n ],\n [\n -73.883056640625,\n 40.53311118427234\n ],\n [\n -73.83018493652344,\n 40.54772199417569\n ],\n [\n -73.77388000488281,\n 40.56389453066509\n ],\n [\n -73.76152038574219,\n 40.57067539946112\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The Mojave Desert region is in a critical position for assessing models of Laramide orogenesis, which is hypothesized to have initiated as one or more seamounts subducted beneath the Cretaceous continental margin. Geochronological and geochemical characteristics of Late Cretaceous magmatic products provide the opportunity to test the validity of Laramide orogenic models. Laramide-aged plutons are exposed along a transect across the Cordilleran Mesozoic magmatic system from Joshua Tree National Park in the Eastern Transverse Ranges eastward into the central Mojave Desert. A transect at latitude ∼33.5°N to 34.5°N includes: (1) the large upper-crustal Late Cretaceous Cadiz Valley batholith, (2) a thick section of Proterozoic to Jurassic host rocks, (3) Late Cretaceous stock to pluton-sized bodies at mesozonal depths, and (4) a Jurassic to Late Cretaceous midcrustal sheeted complex emplaced at ∼20 km depth that transitions into a migmatite complex truncated along the San Andreas fault. This magmatic section is structurally correlative with the Big Bear Lake intrusive suite in the San Bernardino Mountains and similar sheeted rocks recovered in the Cajon Pass Deep Scientific Drillhole.
Zircon U-Pb geochronology of 12 samples via secondary ionization mass spectrometry (SIMS) (six from the Cadiz Valley batholith and six from the Cajon Pass Deep Scientific Drillhole) indicates that all Cretaceous igneous units investigated were intruded between 83 and 74 Ma, and Cajon Pass samples include a Jurassic age component. A compilation of new and published SIMS geochronological data demonstrates that voluminous magmatism in the Eastern Transverse Ranges and central Mojave Desert was continuous throughout the period suggested for the intersection and flat-slab subduction of the Shatsky Rise conjugate deep into the interior of western North America.
Whole-rock major-element, trace-element, and isotope geochemistry data from samples from a suite of 106 igneous rocks represent the breadth of Late Cretaceous units in the transect. Geochemistry indicates an origin in a subduction environment and intrusion into a crust thick enough to generate residual garnet. The lack of significant deflections of compositional characteristics and isotopic ratios in igneous products through space and time argues against a delamination event prior to 74 Ma.
We argue that Late Cretaceous plutonism from the Eastern Transverse Ranges to the central Mojave Desert represents subduction zone arc magmatism that persisted until ca. 74 Ma. This interpretation is inconsistent with the proposed timing of the docking of the Shatsky Rise conjugate with the margin of western North America, particularly models in which the leading edge of the Shatsky Rise was beneath Wyoming at 74 Ma. Alternatively, the timing of cessation of plutonism precedes the timing of the passage of the Hess Rise conjugate beneath western North America at ca. 70–65 Ma. The presence, geochemical composition, and age of arc products in the Eastern Transverse Ranges and central Mojave Desert region must be accounted for in any tectonic model of the transition from Sevier to Laramide orogenesis.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02225.1","usgsCitation":"Economos, R., Barth, A.P., Wooden, J., Paterson, S.R., Friesenhahn, B., Weigand, B., Anderson, J., Roell, J., Palmer, E., Ianno, A., and Howard, K.A., 2021, Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc: Geosphere, v. 17, no. 6, p. 2042-2061, https://doi.org/10.1130/GES02225.1.","productDescription":"20 p.","startPage":"2042","endPage":"2061","ipdsId":"IP-114848","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02225.1","text":"Publisher Index Page"},{"id":392846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.597412109375,\n 32.98102014898148\n ],\n [\n -114.5599365234375,\n 32.98102014898148\n ],\n [\n -114.5599365234375,\n 35.074964853989556\n ],\n [\n -118.597412109375,\n 35.074964853989556\n ],\n [\n -118.597412109375,\n 32.98102014898148\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Economos, R.C","contributorId":270083,"corporation":false,"usgs":false,"family":"Economos","given":"R.C","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Andrew P.","contributorId":214136,"corporation":false,"usgs":false,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":38983,"text":"Indiana University - Purdue University","active":true,"usgs":false}],"preferred":false,"id":828385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wooden, J.L.","contributorId":192664,"corporation":false,"usgs":false,"family":"Wooden","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":828386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, S. R","contributorId":270084,"corporation":false,"usgs":false,"family":"Paterson","given":"S.","email":"","middleInitial":"R","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":828387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friesenhahn, Brody","contributorId":270085,"corporation":false,"usgs":false,"family":"Friesenhahn","given":"Brody","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828388,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weigand, B.A","contributorId":270086,"corporation":false,"usgs":false,"family":"Weigand","given":"B.A","email":"","affiliations":[{"id":56075,"text":"University of Göttingen","active":true,"usgs":false}],"preferred":false,"id":828389,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, J.L.","contributorId":270087,"corporation":false,"usgs":false,"family":"Anderson","given":"J.L.","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":828390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roell, J.L.","contributorId":270088,"corporation":false,"usgs":false,"family":"Roell","given":"J.L.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828391,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palmer, E.F.","contributorId":270089,"corporation":false,"usgs":false,"family":"Palmer","given":"E.F.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828392,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ianno, A.J.","contributorId":270090,"corporation":false,"usgs":false,"family":"Ianno","given":"A.J.","affiliations":[{"id":39566,"text":"Juniata College","active":true,"usgs":false}],"preferred":false,"id":828393,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828394,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231396,"text":"70231396 - 2021 - The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","interactions":[],"lastModifiedDate":"2022-05-10T11:50:54.064361","indexId":"70231396","displayToPublicDate":"2021-11-05T06:47:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","docAbstract":"Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-13-5127-2021","usgsCitation":"Olefeldt, D., Hovemyr, M., Kuhn, M., Bastviken, D., Bohn, T., Connolly, J., Crill, P., Euskirchen, E., Finkelstein, S., Genet, H., Grosse, G., Harris, L., Heffernan, L., Helbig, M., Hugelium, G., Hutchins, R., Juutinen, S., Lara, M., Malhotra, A., Manies, K.L., McGuire, A., Natali, S., O’Donnell, J.A., Parmentier, F., Rasanen, A., Schaedel, C., Sonnentag, O., Strack, M., Tank, S., Treat, C., Varner, R., Virtanen, T., Watts, J., and Warren, R., 2021, The Boreal-Arctic Wetland and Lake Dataset (BAWLD): Earth System Science Data, v. 13, p. 5127-5149, https://doi.org/10.5194/essd-13-5127-2021.","productDescription":"23 p.","startPage":"5127","endPage":"5149","ipdsId":"IP-129170","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450274,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/essd-13-5127-2021","text":"External Repository"},{"id":400379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":842473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hovemyr, Mikael","contributorId":291509,"corporation":false,"usgs":false,"family":"Hovemyr","given":"Mikael","email":"","affiliations":[],"preferred":false,"id":842474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, M.A.","contributorId":291510,"corporation":false,"usgs":false,"family":"Kuhn","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":842475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastviken, D","contributorId":264953,"corporation":false,"usgs":false,"family":"Bastviken","given":"D","affiliations":[{"id":54595,"text":"Department of Thematic Studies - Environmental Change, Linköping University, Linköping, Sweden","active":true,"usgs":false}],"preferred":false,"id":842476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohn, T.J.","contributorId":291513,"corporation":false,"usgs":false,"family":"Bohn","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":842477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connolly, J.","contributorId":291515,"corporation":false,"usgs":false,"family":"Connolly","given":"J.","email":"","affiliations":[],"preferred":false,"id":842478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Crill, P.M.","contributorId":248742,"corporation":false,"usgs":false,"family":"Crill","given":"P.M.","affiliations":[{"id":49996,"text":"Stockholm University, Department of Geological Sciences and Bolin Centre for Climate Research, Stockholm, Sweden","active":true,"usgs":false}],"preferred":false,"id":842479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Euskirchen, E.S.","contributorId":216778,"corporation":false,"usgs":false,"family":"Euskirchen","given":"E.S.","email":"","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":842480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Finkelstein, S.A.","contributorId":257296,"corporation":false,"usgs":false,"family":"Finkelstein","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":842481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Genet, H.","contributorId":291521,"corporation":false,"usgs":false,"family":"Genet","given":"H.","affiliations":[],"preferred":false,"id":842482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grosse, G.","contributorId":192805,"corporation":false,"usgs":false,"family":"Grosse","given":"G.","email":"","affiliations":[],"preferred":false,"id":842483,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Harris, L.I.","contributorId":291522,"corporation":false,"usgs":false,"family":"Harris","given":"L.I.","email":"","affiliations":[],"preferred":false,"id":842484,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Heffernan, L.","contributorId":291524,"corporation":false,"usgs":false,"family":"Heffernan","given":"L.","email":"","affiliations":[],"preferred":false,"id":842485,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Helbig, M.","contributorId":169378,"corporation":false,"usgs":false,"family":"Helbig","given":"M.","email":"","affiliations":[{"id":25485,"text":"Université de Montréal, Canada","active":true,"usgs":false}],"preferred":false,"id":842486,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hugelium, G.","contributorId":291527,"corporation":false,"usgs":false,"family":"Hugelium","given":"G.","email":"","affiliations":[],"preferred":false,"id":842487,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hutchins, R.","contributorId":291530,"corporation":false,"usgs":false,"family":"Hutchins","given":"R.","email":"","affiliations":[],"preferred":false,"id":842488,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Juutinen, S.","contributorId":257303,"corporation":false,"usgs":false,"family":"Juutinen","given":"S.","affiliations":[],"preferred":false,"id":842489,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lara, M.J.","contributorId":291534,"corporation":false,"usgs":false,"family":"Lara","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":842490,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Malhotra, A.","contributorId":291536,"corporation":false,"usgs":false,"family":"Malhotra","given":"A.","affiliations":[],"preferred":false,"id":842491,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":842492,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"McGuire, A.D.","contributorId":199633,"corporation":false,"usgs":false,"family":"McGuire","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":842493,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Natali, S.M.","contributorId":291541,"corporation":false,"usgs":false,"family":"Natali","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":842494,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"O’Donnell, J. A.","contributorId":195376,"corporation":false,"usgs":false,"family":"O’Donnell","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":842495,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parmentier, F-J.W.","contributorId":291544,"corporation":false,"usgs":false,"family":"Parmentier","given":"F-J.W.","affiliations":[],"preferred":false,"id":842496,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rasanen, A.","contributorId":291546,"corporation":false,"usgs":false,"family":"Rasanen","given":"A.","email":"","affiliations":[],"preferred":false,"id":842497,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Schaedel, C.","contributorId":291547,"corporation":false,"usgs":false,"family":"Schaedel","given":"C.","email":"","affiliations":[],"preferred":false,"id":842498,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Sonnentag, O.","contributorId":257322,"corporation":false,"usgs":false,"family":"Sonnentag","given":"O.","affiliations":[],"preferred":false,"id":842499,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Strack, M.","contributorId":291552,"corporation":false,"usgs":false,"family":"Strack","given":"M.","email":"","affiliations":[],"preferred":false,"id":842500,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Tank, S.E.","contributorId":169370,"corporation":false,"usgs":false,"family":"Tank","given":"S.E.","email":"","affiliations":[{"id":12799,"text":"University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":842501,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Treat, C. C.","contributorId":257236,"corporation":false,"usgs":false,"family":"Treat","given":"C. C.","affiliations":[{"id":51984,"text":"University of Finland","active":true,"usgs":false}],"preferred":false,"id":842502,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Varner, R.K.","contributorId":291557,"corporation":false,"usgs":false,"family":"Varner","given":"R.K.","affiliations":[],"preferred":false,"id":842503,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Virtanen, T.","contributorId":291558,"corporation":false,"usgs":false,"family":"Virtanen","given":"T.","email":"","affiliations":[],"preferred":false,"id":842504,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Watts, J.D.","contributorId":291559,"corporation":false,"usgs":false,"family":"Watts","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":842505,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Warren, R.K.","contributorId":291562,"corporation":false,"usgs":false,"family":"Warren","given":"R.K.","email":"","affiliations":[],"preferred":false,"id":842506,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70225637,"text":"sir20215099 - 2021 - Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","interactions":[],"lastModifiedDate":"2021-11-05T11:03:38.802132","indexId":"sir20215099","displayToPublicDate":"2021-11-04T16:15:00","publicationYear":"2021","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":"2021-5099","displayTitle":"Regression Models for Estimating Sediment, Nutrient Concentrations and Loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","title":"Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","docAbstract":"Sediment and nutrient transport in the School Branch watershed (in central Indiana west of Indianapolis) is considered to be heavily affected by agricultural land use throughout the watershed. In 2015, the U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, deployed continuous water-quality monitors and began collecting discrete water-quality samples at the streamflow-gaging station School Branch at CR750N at Brownsburg, Indiana (U.S. Geological Survey station 03353420). Regression models that estimate concentrations of suspended sediment, total nitrogen, and total phosphorus were developed by relating streamflow and continuously monitored water-quality data to concentrations measured in discrete water-quality samples collected from June 2015 through February 2019. Regression model diagnostics indicated that streamflow and sensor-measured turbidity concentrations explained about 95 percent of the variation in suspended-sediment concentration and 73 percent of the variation in total phosphorus concentration. Similarly, streamflow and sensor-measured nitrate plus nitrite concentrations explained about 97 percent of the variation in total nitrogen concentrations.
Daily loads of suspended sediment, total nitrogen, and total phosphorus were computed from regression model concentrations and instantaneous streamflow. The estimated mean daily suspended-sediment discharge (June 2015 through February 2019) was 1.184 tons per day; the estimated median suspended-sediment discharge was 0.053 tons per day. The estimated mean daily total nitrogen discharge (June 2015 through February 2019) was 127.50 pounds per day; the estimated median total nitrogen discharge was 28.49 pounds per day. The estimated mean daily total phosphorus discharge (June 2015 through February 2019) was 12.08 pounds per day; the estimated median total-phosphorus discharge was 1.208 pounds per day.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215099","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Downhour, M.S., Bunch, A.R., and Lathrop, T.R., 2021, Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019: U.S. Geological Survey Scientific Investigations Report 2021–5099, 15 p., https://doi.org/10.3133/sir20215099.","productDescription":"Report: v, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-119874","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":391136,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":391135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWNBAQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data and regression model for suspended sediment for School Branch at CR750N at Brownsburg, Indiana June 23, 2015, to February 6, 2019"},{"id":391133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5099/coverthb.jpg"},{"id":391134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5099/sir20215099.pdf","text":"Report","size":"1.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5099"}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.44866943359375,\n 39.81170080625297\n ],\n [\n -86.23306274414062,\n 39.81170080625297\n ],\n [\n -86.23306274414062,\n 40.01604611654875\n ],\n [\n -86.44866943359375,\n 40.01604611654875\n ],\n [\n -86.44866943359375,\n 39.81170080625297\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS–415
Denver, CO 80225–0046
The Partridge River Basin (PRB) covers 156 square miles in northeastern Minnesota with headwaters in the Mesabi Iron Range. The basin is characterized by extensive wetlands, lakes, and streams in poorly drained and often thin glacial material overlying Proterozoic bedrock. To better understand the interaction between these extensive surface water features and the groundwater system, a three-dimensional, steady-state, groundwater-flow model of the PRB was developed by the U.S. Geological Survey in cooperation with the Great Lakes Indian Fish & Wildlife Commission using the finite-difference computer code MODFLOW-NWT. The model simulates steady-state base flow in streams and groundwater interactions using the streamflow routing (SFR2) package. Existing mining features including tailings basins, stockpiles, pumped mine pits, and flooded mine pits were simulated using either high hydraulic conductivity zones or the drain (DRN) package. The unsaturated zone flow (UZF) package was used to better represent the groundwater system in areas with a high water table and for wetlands often associated with such areas. UZF typically is used to represent unsaturated zone processes but also can simulate the rejection of recharge and groundwater discharge to the land surface when the water table is near land surface. The steady-state model used data from the 2011 to 2013 period when 2011 high-resolution land surface (light detecting and ranging [lidar]) data were available that reflected land-surface and water elevations from mining activity in the basin. The parameter-estimation software suite PEST_HP was used to obtain a best fit of the modeled to measured groundwater levels, streamflow, pit inflow rates, and mapped peat deposits. The PEST calibration used the target residuals from two models with the same model parameters and targets from two separate periods: (1) a 1995–2015 calibration model, which provided a larger number of calibration targets, and (2) a 2011–2013 mining conditions model, which included calibration targets that reflected conditions consistent with the modeled mine-workings topography.
Calibration of the PRB model resulted in ranges of glacial horizontal hydraulic conductivity parameters that generally agreed with literature values and other models of the region. Horizontal hydraulic conductivity of the bedrock was higher in the upper bedrock layers where numerous and continuous fractures have been observed and lower in the deeper bedrock layers. Average basin-wide calibrated infiltration was 5.3 inches per year. An average of 4.6 inches per year of infiltration crosses the water table and becomes recharge and 0.7 inch per year is rejected by UZF due to saturated conditions at the land surface. Simulated groundwater runoff (the sum of rejected recharge and groundwater seepage to the land surface) can either be routed to streams or removed from the model as evapotranspiration. The calibrated model indicates relatively shallow groundwater-flow paths dominating and approximately 50 percent of the stream base flow coming from groundwater runoff.
The 2011–2013 mining conditions model was then used to develop five model scenarios simulating the response of the groundwater and surface-water system to potential hydrologic stress. The purpose of these mine pit scenarios is to present a possible workflow to quantify a model’s uncertainty for a given model forecast and serve as a possible guide for initial data collection that may improve a future model’s ability to make such a forecast. The scenarios included one scenario with the currently existing Peter Mitchell pit at final buildout and flooded to an elevation of 1,500 feet, and four scenarios with a hypothetical, new mine pit plus the flooded Peter Mitchell at final buildout. The five model scenarios were used to forecast streamflow at six locations in the PRB, pit inflow rates for the new mine pits and the flooded Peter Mitchell pit, and the average depth to water in 12 wetlands. A linear uncertainty analysis was performed using information from the PEST calibration and tools in the PyEMU python package to assess model uncertainty propagation to the model forecasts. Streamflows generally were reduced with future mining and the greatest streamflow reductions occurred from the flooded Peter Mitchell Pit, probably due to its large size. Average depth to groundwater in wetlands was most affected the closer the wetland was to a new mine pit.
Linear uncertainty methods were also used to evaluate data worth, which is the ability for potential new groundwater elevation observations to reduce the uncertainty in scenario forecasts. Data worth was performed for a grid of new hydraulic head observations. Overall, areas with nonnegligible data worth generally corresponded to wetland areas with no groundwater seepage to land surface from UZF. These model behaviors indicated that the land-surface boundary condition simulated by the UZF package was pinning the groundwater elevations to the land surface in areas with groundwater seepage (33 percent of the 2011–2013 base conditions model) such that the sensitivity to new observations in these areas was minimal. Therefore, representing wetlands as boundary conditions minimized the usefulness of data worth calculations because wetland areas were present over a large part of the model domain.
Probabilistic capture zones were estimated for each of the mines in the model scenarios. A capture zone represents the area contributing recharge to a model feature, like a well or a mine pit, and can be calculated by forward tracking particles from the water table. By using Monte Carlo techniques, it is possible to generate estimated capture zones that include the probability of recharge capture given the uncertainty present in the model. Monte Carlo techniques use randomly generated model parameter sets sampled from a plausible parameter range to create many possible realizations. The resulting capture zone arrays were calculated by tallying the total number of realizations in which a particle from a model cell was captured by the feature. Probabilities from the Monte Carlo runs ranged from 1 (captured in 100 percent of the runs) near the pits to 0 (captured in 0 percent of the runs) at the edges of the capture zone. Capture zones were not always spatially continuous; for example, the capture zone for the proposed mine pits south of the flooded Peter Mitchell pit was discontinuous with capture surrounding the proposed mine pit and north of the flooded Peter Mitchell pit. This northern section represents deeper groundwater flow paths that originate in the topographic high, move under the flooded pit, and discharge into the proposed pit. This pattern of capture indicates the possibility of some deeper flow through the upper fractured bedrock when the shallow groundwater flow system is modified. These results underscore that future site-specific applications of the base condition model require the input of site-specific data and recalibration to focus on the site of interest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215038","collaboration":"Prepared in cooperation with the Great Lakes Indian Fish & Wildlife Commission","usgsCitation":"Haserodt, M.J., Hunt, R.J., Fienen, M.N., and Feinstein, D.T., 2021, Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota: U.S. Geological Survey Scientific Investigations Report 2021–5038, 94 p., https://doi.org/10.3133/sir20215038.","productDescription":"Report: ix, 87 p.; Data Release; Dataset","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-123210","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391131,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.xml","text":"Report xml","size":"277 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5038 xml"},{"id":391130,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":391132,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5038/images"},{"id":391129,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VODOU8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT and MODPATH models, capture zones and uncertainty data analysis for the Partridge River Basin, Minnesota"},{"id":391127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5038/coverthb.jpg"},{"id":391128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.pdf","text":"Report","size":"69.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5038"}],"country":"United States","state":"Minnesota","otherGeospatial":"Partridge River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.25,\n 47.4\n ],\n [\n -91.75,\n 47.4\n ],\n [\n -91.75,\n 47.8\n ],\n [\n -92.25,\n 47.8\n ],\n [\n -92.25,\n 47.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive,
Madison, WI 53726
Many aquatic species in the arid USA-Mexico borderlands region are imperiled, but limited information on distributions and threats often hinders management. To provide information on the distribution of the Western Tiger Salamander (Ambystoma mavortium), including the USA-federally endangered Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi), we used traditional (seines, dip-nets) and modern (environmental DNA [eDNA]) methods to sample 91 waterbodies in northern Sonora, Mexico, during 2015-2018. The endemic Sonoran Tiger Salamander is threatened by introgressive hybridization and potential replacement by another sub-species of the Western Tiger Salamander, the non-native Barred Tiger Salamander (A. m. mavortium). Based on occupancy models that accounted for imperfect detection, eDNA sampling provided a similar detection probability (0.82 [95% CI: 0.56-0.94]) as seining (0.83 [0.46-0.96]) and much higher detection than dip-netting (0.09 [0.02-0.23]). Volume of water filtered had little effect on detection, possibly because turbid sites had greater densities of salamanders. Salamanders were estimated to occur at 51 sites in 3 river drainages in Sonora. These results indicate tiger salamanders are much more widespread in northern Sonora than previously documented, perhaps aided by changes in land and water management practices. However, because the two subspecies of salamanders cannot be reliably distinguished based on morphology or eDNA methods that are based on mitochondrial DNA, we are uncertain if we detected only native genotypes or if we documented recent invasion of the area by the non-native sub-species. Thus, there is an urgent need for methods to reliably distinguish the subspecies so managers can identify appropriate interventions.
","language":"English","publisher":"Brill","doi":"10.1163/15685381-bja10072","usgsCitation":"Hossack, B., Lemos-Espinal, J.A., Sigafus, B., Muths, E., Carreon Arroyo, G., Toyos Martinez, D., Hurtado Felix, D., Molina Padilla, G., Goldberg, C., Jones, T.R., Sredl, M.J., Chambert, T., and Rorabaugh, J.C., 2021, Distribution of tiger salamanders in northern Sonora, Mexico: Comparison of sampling methods and possible implications for an endangered subspecies: Amphibia-Reptilia, v. 43, p. 13-23, https://doi.org/10.1163/15685381-bja10072.","productDescription":"11 p.","startPage":"13","endPage":"23","ipdsId":"IP-108340","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450280,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":397935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.8515625,\n 30.524413269923986\n ],\n [\n -108.6328125,\n 30.221101852485987\n ],\n [\n -108.80859375,\n 31.50362930577303\n ],\n [\n -111.181640625,\n 31.39115752282472\n ],\n [\n -114.78515624999999,\n 32.54681317351514\n ],\n [\n -114.9169921875,\n 31.952162238024975\n ],\n [\n -114.3017578125,\n 31.57853542647338\n ],\n [\n -113.8623046875,\n 31.541089879585808\n ],\n [\n -113.15917968749999,\n 31.240985378021307\n ],\n [\n -112.8515625,\n 30.524413269923986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":839312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lemos-Espinal, Julio A.","contributorId":237891,"corporation":false,"usgs":false,"family":"Lemos-Espinal","given":"Julio","email":"","middleInitial":"A.","affiliations":[{"id":47636,"text":"FES Iztacala UNAM","active":true,"usgs":false}],"preferred":false,"id":839313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":839314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":839315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carreon Arroyo, Gerardo","contributorId":289549,"corporation":false,"usgs":false,"family":"Carreon Arroyo","given":"Gerardo","affiliations":[{"id":62189,"text":"Naturalia","active":true,"usgs":false}],"preferred":false,"id":839316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toyos Martinez, Daniel","contributorId":167619,"corporation":false,"usgs":false,"family":"Toyos Martinez","given":"Daniel","email":"","affiliations":[{"id":24783,"text":"Naturalia, A.C., El Cajon # 9 Col., Santa Fe, C.P. 83249, Hermosillo, Sonora 83299, Mexico","active":true,"usgs":false}],"preferred":false,"id":839317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hurtado Felix, David","contributorId":289550,"corporation":false,"usgs":false,"family":"Hurtado Felix","given":"David","affiliations":[],"preferred":false,"id":839318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molina Padilla, Guillermo","contributorId":289551,"corporation":false,"usgs":false,"family":"Molina Padilla","given":"Guillermo","email":"","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":839319,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goldberg, Caren S.","contributorId":289552,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren S.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":839320,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, T. R.","contributorId":289553,"corporation":false,"usgs":false,"family":"Jones","given":"T.","email":"","middleInitial":"R.","affiliations":[{"id":54870,"text":"Arizona Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":839321,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sredl, M. J.","contributorId":289554,"corporation":false,"usgs":false,"family":"Sredl","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":54870,"text":"Arizona Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":839322,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chambert, Thierry 0000-0002-9450-9080 tchambert@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-9080","contributorId":191979,"corporation":false,"usgs":false,"family":"Chambert","given":"Thierry","email":"tchambert@usgs.gov","affiliations":[],"preferred":false,"id":839323,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, J. C.","contributorId":289555,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":839324,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70225716,"text":"70225716 - 2021 - A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA","interactions":[],"lastModifiedDate":"2022-01-25T17:10:28.774338","indexId":"70225716","displayToPublicDate":"2021-11-02T09:09:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA","docAbstract":"The Anza-Cahuilla groundwater basin located mainly in the semi-arid headwaters of the Santa Margarita River watershed in southern California is the principle source of groundwater for a rural disadvantaged community and two Native American Tribes, the Ramona Band of Cahuilla and the Cahuilla. Groundwater in the study area is derived entirely from precipitation and managing groundwater sustainably requires an accurate assessment of the water balance components, yet long-term estimates do not exist. Demand for groundwater in the region has increased and groundwater quality has decreased due to population growth and increased irrigated cropland. To characterize monthly long-term natural recharge and runoff estimates, a physically-based water balance model (Basin Characterization Model) was locally calibrated and validated using nearby streamgages and published estimates of climatic and hydrologic variables. The average modeled annual recharge and runoff from 1981 to 2010 was 5.4 × 106 and 1.2 × 107 m3, respectively, for the study area. Recharge and runoff do not reliably occur in large amounts every year and recharge rarely occurs in the groundwater basin footprint. These long-term estimates can be used by water managers, stakeholders, and Native American Tribes to develop plans for sustainable management of future water resources, and as inputs to a three-dimensional groundwater model.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12971","usgsCitation":"Stern, M.A., Flint, L.E., Flint, A.L., and Christensen, A.H., 2021, A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA: Journal of the American Water Resources Association, v. 57, no. 6, p. 990-1003, https://doi.org/10.1111/1752-1688.12971.","productDescription":"14 p.","startPage":"990","endPage":"1003","ipdsId":"IP-119217","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450287,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12971","text":"Publisher Index Page"},{"id":436125,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BAMCP4","text":"USGS data release","linkHelpText":"Basin Characterization Model (BCMv8) monthly recharge and runoff for the Anza-Cahuilla Groundwater Basin, California"},{"id":391385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Anza-Cahuilla groundwater basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.9166,\n 33.3333\n ],\n [\n -116.25,\n 33.3333\n ],\n [\n -116.25,\n 33.75\n ],\n [\n -116.9166,\n 33.75\n ],\n [\n -116.9166,\n 33.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826395,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225706,"text":"70225706 - 2021 - Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model","interactions":[],"lastModifiedDate":"2021-11-04T13:24:32.427815","indexId":"70225706","displayToPublicDate":"2021-11-02T08:18:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model","docAbstract":"Salt marshes are dynamic biogeomorphic systems that respond to external physical factors, including tides, sediment transport, and waves, as well as internal processes such as autochthonous soil formation. Predicting the fate of marshes requires a modeling framework that accounts for these processes in a coupled fashion. In this study, we implement two new marsh dynamic processes in the 3-D COAWST (coupled-ocean-atmosphere-wave sediment transport) model. The processes added are the erosion of the marsh edge scarp caused by lateral wave thrust from surface waves and vertical accretion driven by organic growth on the marsh platform. The sediment released from the marsh causes a change in bathymetry, thereby modifying the wave-energy reaching the marsh edge. Marsh vertical accretion due to biomass production is considered for a single vegetation species and is determined by the hydroperiod parameters (tidal datums) and the elevation of the marsh cells. Tidal datums are stored at user-defined intervals as a hindcast (on the order of days) and used to update the vertical growth formulation. Idealized domains are utilized to verify the lateral wave thrust formulation and show the dynamics of lateral wave erosion leading to horizontal retreat of marsh edge. The simulations of Reedy and Dinner Creeks within the Barnegat Bay estuary system demonstrate the model capability to account for both lateral wave erosion and vertical accretion due to organic growth in a realistic marsh complex. The simulations show that majority of accretion over the marsh complex occurs due to organic production while most estuarine sediment deposition occurs along the channel edges. The ability of the model to capture the fate of the sediment can be extended to model future storm and relative sea level rise (RSLR) scenarios.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2021.740921","usgsCitation":"Kalra, T., Ganju, N., Aretxabaleta, A., Carr, J., Defne, Z., and Moriarty, J., 2021, Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model: Frontiers in Marine Science, v. 8, 740921, 20 p., https://doi.org/10.3389/fmars.2021.740921.","productDescription":"740921, 20 p.","ipdsId":"IP-131349","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450291,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.740921","text":"Publisher Index Page"},{"id":436127,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QO091Z","text":"USGS data release","linkHelpText":"COAWST model of Barnegat Bay creeks to demonstrate marsh dynamics"},{"id":436126,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94HYOGQ","text":"USGS data release","linkHelpText":"Idealized COAWST numerical model for testing marsh wave thrust and lateral retreat dynamics routines"},{"id":391380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":826399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826356,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moriarty, Julia 0000-0003-1087-6180","orcid":"https://orcid.org/0000-0003-1087-6180","contributorId":261307,"corporation":false,"usgs":false,"family":"Moriarty","given":"Julia","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":826357,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229705,"text":"70229705 - 2021 - Causes, consequences, and conservation of ungulate migration","interactions":[],"lastModifiedDate":"2022-03-16T17:09:05.532326","indexId":"70229705","displayToPublicDate":"2021-11-01T12:01:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":808,"text":"Annual Review of Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"Causes, consequences, and conservation of ungulate migration","docAbstract":"Our understanding of ungulate migration is advancing rapidly due to innovations in modern animal tracking. Herein, we review and synthesize nearly seven decades of work on migration and other long-distance movements of wild ungulates. Although it has long been appreciated that ungulates migrate to enhance access to forage, recent contributions demonstrate that their movements are fine tuned to dynamic landscapes, where forage, snow, and drought change seasonally. Researchers are beginning to understand how ungulates navigate migrations, with the emerging view that animals blend gradient tracking with spatial memory, some of which is socially learned. Although migration often promotes abundant populations—with broad effects on ecosystems—many migrations around the world have been lost or are currently threatened by habitat fragmentation, climate change, and barriers to movement. Fortunately, new efforts that use empirical tracking data to map migrations in detail are facilitating effective conservation measures needed to maintain ungulate migration.","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-ecolsys-012021-011516","usgsCitation":"Kauffman, M., Aikens, E., Esmaeili, S., Kaczensky, P., Middleton, A., Monteith, K., Morrison, T., Mueller, T., Sawyer, H., and Goheen, J., 2021, Causes, consequences, and conservation of ungulate migration: Annual Review of Ecology, Evolution, and Systematics, v. 52, p. 453-478, https://doi.org/10.1146/annurev-ecolsys-012021-011516.","productDescription":"26 p.","startPage":"453","endPage":"478","ipdsId":"IP-128230","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":499856,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.gla.ac.uk/251267/","text":"External Repository"},{"id":397189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aikens, Ellen O.","contributorId":287807,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen O.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":838027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esmaeili, Saeideh","contributorId":287842,"corporation":false,"usgs":false,"family":"Esmaeili","given":"Saeideh","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":838028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaczensky, Petra","contributorId":74623,"corporation":false,"usgs":true,"family":"Kaczensky","given":"Petra","email":"","affiliations":[],"preferred":false,"id":838029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Middleton, Arthur","contributorId":39274,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur","affiliations":[],"preferred":false,"id":838030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Monteith, Kevin L.","contributorId":280167,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin L.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":838204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morrison, Thomas A.","contributorId":272238,"corporation":false,"usgs":false,"family":"Morrison","given":"Thomas A.","affiliations":[{"id":56374,"text":"ug","active":true,"usgs":false}],"preferred":false,"id":838205,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Thomas","contributorId":274278,"corporation":false,"usgs":false,"family":"Mueller","given":"Thomas","affiliations":[{"id":56593,"text":"Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":838206,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":838207,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Goheen, Jacob R.","contributorId":287808,"corporation":false,"usgs":false,"family":"Goheen","given":"Jacob R.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":838208,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70227120,"text":"70227120 - 2021 - PlioMIP: The Pliocene Model Intercomparison Project","interactions":[],"lastModifiedDate":"2022-01-20T16:54:19.278195","indexId":"70227120","displayToPublicDate":"2021-11-01T10:49:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10036,"text":"Past Global Changes Magazine","active":true,"publicationSubtype":{"id":10}},"title":"PlioMIP: The Pliocene Model Intercomparison Project","docAbstract":"PlioMIP is a network of paleoclimate modelers and geoscientists who, through the study of the mid-Pliocene Warm Period (mPWP ~3.3–3.0 million years ago), seek to understand the sensitivity of the climate system to forcings and examine how well models reproduce past climate change.
","language":"English","publisher":"PAGES","doi":"10.22498/pages.29.2.92","usgsCitation":"Haywood, A.M., Dowsett, H.J., and PlioMIP1 and PlioMIP2 participants, 2021, PlioMIP: The Pliocene Model Intercomparison Project: Past Global Changes Magazine, v. 29, no. 2, p. 92-93, https://doi.org/10.22498/pages.29.2.92.","productDescription":"2 p.","startPage":"92","endPage":"93","ipdsId":"IP-129726","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":450301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.22498/pages.29.2.92","text":"Publisher Index Page"},{"id":394590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haywood, A. M.","contributorId":147374,"corporation":false,"usgs":false,"family":"Haywood","given":"A.","email":"","middleInitial":"M.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":829718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":269579,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":829717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"PlioMIP1 and PlioMIP2 participants","contributorId":271731,"corporation":true,"usgs":false,"organization":"PlioMIP1 and PlioMIP2 participants","id":831309,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228783,"text":"70228783 - 2021 - Movement dynamics and survival of stocked Colorado River Cutthroat Trout","interactions":[],"lastModifiedDate":"2022-02-21T16:39:04.205486","indexId":"70228783","displayToPublicDate":"2021-11-01T10:30:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Movement dynamics and survival of stocked Colorado River Cutthroat Trout","docAbstract":"The ability of native fish to establish self-sustaining populations when reintroduced to vacant habitats is variable. We evaluated factors that potentially affect the reintroduction success of juvenile Colorado River Cutthroat Trout Oncorhynchus clarkii pleuriticus that were reintroduced to an isolated watershed and were experiencing suboptimal survival and recruitment. We conducted a 3-year mark–recapture study to model annual apparent survival probability as it related to (1) different ex situ rearing strategies and (2) initial release among different habitat types. The use of PIT tags also enabled the quantification of loss via emigration. Apparent survival was highest for small fish that were minimally exposed to ex situ rearing conditions, stocked in small, headwater stream reaches. However, maximum estimates of apparent survival remained low (≤0.38 ± 0.05 [estimate ± SE]) regardless of rearing treatment, stocking location, or interactive effects between covariates. Emigration of stocked fish (<1%) from the study area did not appear to limit their establishment. Our results suggest that variation in stocking and rearing strategy may have some effect on translocation success and the interaction between rearing and stocking strategy highlights the importance of considering the life history stage of stocked individuals when identifying stocking sites. Consistently low annual survival values may be indicative of a larger issue, requiring in-depth evaluation of adaptive potential within our brood source and other factors that potentially limit population persistence.
","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10322","usgsCitation":"LeCheminant, A.G., Barrile, G.M., Albeke, S., and Walters, A.W., 2021, Movement dynamics and survival of stocked Colorado River Cutthroat Trout: Transactions of the American Fisheries Society, v. 150, no. 6, p. 679-693, https://doi.org/10.1002/tafs.10322.","productDescription":"15 p.","startPage":"679","endPage":"693","ipdsId":"IP-114193","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River, LaBarge Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.48812866210938,\n 42.11248648904184\n ],\n [\n -110.05691528320311,\n 42.11248648904184\n ],\n [\n -110.05691528320311,\n 42.37021284789698\n ],\n [\n -110.48812866210938,\n 42.37021284789698\n ],\n [\n -110.48812866210938,\n 42.11248648904184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"LeCheminant, Alex G.","contributorId":279769,"corporation":false,"usgs":false,"family":"LeCheminant","given":"Alex","email":"","middleInitial":"G.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":835464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barrile, Gabriel M.","contributorId":270694,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel","email":"","middleInitial":"M.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":835465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albeke, Shannon E.","contributorId":244121,"corporation":false,"usgs":false,"family":"Albeke","given":"Shannon E.","affiliations":[{"id":48000,"text":"U Wyoming","active":true,"usgs":false}],"preferred":false,"id":835466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":835463,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231779,"text":"70231779 - 2021 - Numerical simulation of the boundary layer flow generated in Monterey Bay, California by the 2010 Chilean tsunami: Case study","interactions":[],"lastModifiedDate":"2022-05-27T13:46:20.875172","indexId":"70231779","displayToPublicDate":"2021-11-01T08:39:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8957,"text":"Journal of Waterway, Port, Coastal, and Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Numerical simulation of the boundary layer flow generated in Monterey Bay, California by the 2010 Chilean tsunami: Case study","docAbstract":"This work presents a case study involving the numerical simulation of the unsteady boundary layer generated by the 2010 Chilean tsunami, as measured by field equipment in Monterey Bay, California, USA. A one-dimensional vertical (1DV) boundary layer model is utilized, solving Reynolds-averaged Navier–Stokes equations, coupled with two-equation k–ω turbulence closure. Local effects of convective acceleration (converging–diverging effects) on the boundary layer due to the sloping bed are likewise approximated. Four cases are considered involving simulation of: (1) the long tsunami-induced boundary layer flow in isolation, in combination with either (2) convective acceleration effects or (3) energetic short wind waves, and, finally, (4) all effects combined. Reasonable agreement with field measurements is achieved, with model results similarly showing that the tsunami-induced boundary layer in this case only spans a fraction of the local water depth. Systematic comparison of the various cases likewise elucidates the likely significance of both local converging–diverging effects, as well as interaction with the much shorter period wind waves, on the tsunami-generated boundary layer. In the latter case, analogy is drawn to well-known wave–current boundary layer interaction, with the boundary layer turbulence associated with the short wind waves inducing an effective wave roughness felt by the tsunami-induced flow, which effectively plays the role of the current.
","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)WW.1943-5460.0000673","usgsCitation":"Makris, A., Lacy, J.R., and Fuhrman, D.R., 2021, Numerical simulation of the boundary layer flow generated in Monterey Bay, California by the 2010 Chilean tsunami: Case study: Journal of Waterway, Port, Coastal, and Ocean Engineering, v. 147, no. 6, 05021012, 9 p., https://doi.org/10.1061/(ASCE)WW.1943-5460.0000673.","productDescription":"05021012, 9 p.","ipdsId":"IP-124548","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450309,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orbit.dtu.dk/en/publications/820c4abf-2a2e-4005-bb2f-da14b18d53c7","text":"External Repository"},{"id":401297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.89468383789061,\n 36.59347887826919\n ],\n [\n -121.87271118164062,\n 36.589068371399115\n ],\n [\n -121.82052612304688,\n 36.639773979496574\n ],\n [\n -121.79992675781249,\n 36.69264861993992\n ],\n [\n -121.79443359375,\n 36.752089156946326\n ],\n [\n -121.77932739257812,\n 36.79389010047562\n ],\n [\n -121.77932739257812,\n 36.815881441097154\n ],\n [\n -121.82052612304688,\n 36.88511287236025\n ],\n [\n -121.8548583984375,\n 36.9378185354581\n ],\n [\n -121.89056396484375,\n 36.96854668458301\n ],\n [\n -121.93450927734375,\n 36.98939086733937\n ],\n [\n -121.9757080078125,\n 36.96525497589677\n ],\n [\n -122.02239990234375,\n 36.97183825093165\n ],\n [\n -122.05673217773438,\n 36.95757376878687\n ],\n [\n -122.10067749023438,\n 36.96415770803826\n ],\n [\n -122.10891723632812,\n 36.71907231552909\n ],\n [\n -121.96884155273436,\n 36.5736296124793\n ],\n [\n -121.93450927734375,\n 36.62875385775956\n ],\n [\n -121.89468383789061,\n 36.59347887826919\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Makris, Athanasios","contributorId":292114,"corporation":false,"usgs":false,"family":"Makris","given":"Athanasios","email":"","affiliations":[{"id":62831,"text":"Technical University of Denmark, Dept of Mechanical Engr","active":true,"usgs":false}],"preferred":false,"id":843812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuhrman, David R. 0000-0002-2433-6778","orcid":"https://orcid.org/0000-0002-2433-6778","contributorId":292115,"corporation":false,"usgs":false,"family":"Fuhrman","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":62832,"text":"Technical University of Denmark, Dept. of Mechanical Engr","active":true,"usgs":false}],"preferred":false,"id":843814,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225681,"text":"70225681 - 2021 - The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research","interactions":[],"lastModifiedDate":"2021-12-10T17:32:59.24794","indexId":"70225681","displayToPublicDate":"2021-11-01T08:16:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5706,"text":"Limnology and Oceanography Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research","docAbstract":"Following the 2020 “Virtual Summit: Incorporating Data Science and Open Science in Aquatic Research” (DSOS; Meyer and Zwart 2020), a grassroots group of scientists convened the 2nd Virtual DSOS Summit on 22–23 July 2021. DSOS combined forces with the Aquatic Ecosystem MOdeling Network - Junior (AEMON-J; https://github.com/aemon-j) to host a 4-d “Hacking Limnology” Workshop Series prior to the summit (13–16 July 2021). The aim was to focus more deeply on skill development and networking among early career researchers (ECRs), both of which are key to growing a workforce of data-intensive aquatic scientists (López Moreira M et al. in press; Meyer et al. 2021a). To support ECRs further, we hosted a virtual job board, where participants could note if they were either looking for employment or hiring for a position. Like the 2020 summit, there was high enthusiasm for both the summit and the workshops. In total, 686 people from over 50 countries registered for the AEMON-J Workshop Series and the DSOS Summit. Countries with the highest number of registrants included the United States (41%), Nigeria (20%), Canada (6%), Brazil (6%), and Germany (5%) (Fig. 1). To increase accessibility, there were no registration costs for the workshops and summit, and we centralized introductory training materials, coding scripts, and presentation recordings in one community website (https://aquaticdatasciopensci.github.io/; Fig. 2), which we hope will continue to support the AEMON-J and DSOS communities over time.
","language":"English","publisher":"Association of Limnology and Oceanography","doi":"10.1002/lob.10475","usgsCitation":"Meyer, M.F., Ladwig, R., Mesman, J., Oleksy, I., Barbosa, C.C., Cawley, K.M., Cramer, A.N., Feldbauer, J., Tran, P.Q., Zwart, J.A., Lopez Moreira, G.A., Shikhani, M., Gurung, D., Hensley, R.T., Matta, E., McClure, R.P., Petzoldt, T., Sanchez Lopez, N., Soetaert, K., Thomas, M.K., Topp, S.N., and Yang, X., 2021, The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research: Limnology and Oceanography Bulletin, v. 30, no. 4, p. 140-143, https://doi.org/10.1002/lob.10475.","productDescription":"4 p.","startPage":"140","endPage":"143","ipdsId":"IP-132579","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":450311,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/lob.10475","text":"External Repository"},{"id":391317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meyer, Michael F. 0000-0002-8034-9434","orcid":"https://orcid.org/0000-0002-8034-9434","contributorId":244065,"corporation":false,"usgs":false,"family":"Meyer","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":826210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ladwig, Robert 0000-0001-8443-1999","orcid":"https://orcid.org/0000-0001-8443-1999","contributorId":268211,"corporation":false,"usgs":false,"family":"Ladwig","given":"Robert","email":"","affiliations":[],"preferred":false,"id":826211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mesman, Jorrit 0000-0002-4319-260X","orcid":"https://orcid.org/0000-0002-4319-260X","contributorId":268212,"corporation":false,"usgs":false,"family":"Mesman","given":"Jorrit","email":"","affiliations":[{"id":25472,"text":"University of Geneva","active":true,"usgs":false}],"preferred":false,"id":826212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oleksy, Isabella 0000-0003-2572-5457","orcid":"https://orcid.org/0000-0003-2572-5457","contributorId":268213,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":826213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barbosa, Carolina C. 0000-0002-6393-5730","orcid":"https://orcid.org/0000-0002-6393-5730","contributorId":268214,"corporation":false,"usgs":false,"family":"Barbosa","given":"Carolina","email":"","middleInitial":"C.","affiliations":[{"id":55596,"text":"São Carlos School of Engineering, Hydraulics and Sanitation Department","active":true,"usgs":false}],"preferred":false,"id":826214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cawley, Kaelin M. 0000-0002-0443-0070","orcid":"https://orcid.org/0000-0002-0443-0070","contributorId":268215,"corporation":false,"usgs":false,"family":"Cawley","given":"Kaelin","email":"","middleInitial":"M.","affiliations":[{"id":55597,"text":"National Ecological Observatory Network","active":true,"usgs":false}],"preferred":false,"id":826215,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cramer, Alli N. 0000-0002-0356-5782","orcid":"https://orcid.org/0000-0002-0356-5782","contributorId":268216,"corporation":false,"usgs":false,"family":"Cramer","given":"Alli","email":"","middleInitial":"N.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":826216,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Feldbauer, Johannes 0000-0002-8238-5375","orcid":"https://orcid.org/0000-0002-8238-5375","contributorId":268217,"corporation":false,"usgs":false,"family":"Feldbauer","given":"Johannes","email":"","affiliations":[{"id":55600,"text":"Technische Universität Dresden","active":true,"usgs":false}],"preferred":false,"id":826217,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tran, Patricia Q. 0000-0003-3948-3938","orcid":"https://orcid.org/0000-0003-3948-3938","contributorId":268218,"corporation":false,"usgs":false,"family":"Tran","given":"Patricia","email":"","middleInitial":"Q.","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":826218,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - 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It is especially contentious with regards to the Delta Smelt (Hypomesus transpacificus), a species endemic to the SFE that has been listed as threatened under the Federal Endangered Species Act and endangered by the State of California. Early studies of Delta Smelt distribution within the SFE suggested that Delta Smelt habitat is determined largely by freshwater flow; however, the exact mechanisms and processes producing such benefits remained unclear. In the summer of 2017, the Flow Alteration Management, Analysis, and Synthesis Team (FLOAT-MAST) was established to analyze, synthesize, and summarize the data collected from the various flow-related monitoring and special studies occurring in 2017(see Table Intro 4). This report will focus on the 2017 summer-fall status of Delta Smelt and its habitat following a record wet year.
There has been a long-term decline in the abundance of Delta Smelt associated with a decline in other pelagic fishes. Investigators concluded that the decline has likely been caused by the interactive effects of several causes, including changes in both physical and biotic habitats, many of which are tied to amount and timing of freshwater flow. For this report, we formulated a number of basic predictions about the likely effects of high flows in 2017 on Delta Smelt and their habitat (Table 3). We use a qualitative weight of evidence approach to evaluate whether these predictions were supported by available data. Data sources included a variety of long-term monitoring surveys conducted by Interagency Ecological Program (IEP) agencies, as well as model outputs.
Delta Smelt population, health, and life history metrics rarely responded as predicted. Water temperature appears to have a stronger effect on Delta Smelt growth rate and some metrics of life history diversity than outflow or X2 position. Other life history diversity attributes varied but did not appear to be driven by outflow or temperature. Health status was difficult to interpret. Low prevalence of lesions and improved nutritional condition during the drought was contradicted by declining overall population levels. Because of the sparse catches of Delta Smelt in the post-POD years, we consider the data insufficient to reach firm conclusions about the predictions concerning range and distribution of Delta Smelt, especially in the fall. The prediction of high survival was not supported. The 2017 Delta Smelt year class began with poor recruitment in spring of 2017 and below average survival for spring to summer and summer to fall. Thus, low production and low survival led to low abundance of all life stages. During the fall to winter period survival improved, yet the resulting adults were low in number. Foraging success of the fish captured, as measured by stomach fullness, was high for juveniles and adults in 2017 relative to recent years associated with the higher densities of common zooplankton prey that occurred in 2017.
This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2 Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2 is a medium-resolution satellite launched in 2011 on the Polar Satellite Launch Vehicle-C16. Resourcesat-2 carries the same sensing elements as Resourcesat-1 (launched in October 2003) and provides continuity for the mission. The objectives of the Resourcesat mission are to provide remote sensing data services to global users, focusing on data for integrated land and water resources management.
Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 launch vehicle for continuity of data and improved temporal resolution. The two satellites operating in tandem improved the revisit capability from 5 days to 2–3 days. The Resourcesat-2 platform is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that AWiFS has an interior geometric performance in the range of −16.080 (−0.268 pixel) to 35.520 meters (m; 0.592 pixel) in easting and −25.680 (−0.428 pixel) to 23.400 m (0.390 pixel) in northing in band-to-band registration, an exterior geometric error of −64.262 (−1.071 pixels) to −19.059 m (−0.318 pixel) in easting and −29.028 (−0.484 pixel) to 41.249 m (0.687 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 2.29–2.36 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.030–0.035.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030G","usgsCitation":"Ramaseri Chandra, S.N., Kim, M., Christopherson, J., Stensaas, G.L., and Anderson, C., 2021, System characterization report on Resourcesat-2 Advanced Wide Field Sensor, chap. G of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors (ver. 1.2, August 2024): U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030G.","productDescription":"Report: iv, 17 p.; Version History","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126658","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":392291,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/g/versionHist.txt","text":"Version History","size":"1.8 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2021–1030G Version History"},{"id":391064,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/g/images"},{"id":391063,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.xml","text":"Report","size":"79.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1030G xml"},{"id":433255,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/g/ofr20211030g.pdf","text":"Report","size":"2.2 MB","description":"OFR 2021–1030G"},{"id":391061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/g/coverthb3.jpg"}],"edition":"Version 1.0: September 28, 2021; Version 1.1: November 30, 2021; Version 1.2: August 29, 2024","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Northern bobwhite Colinus virginianus populations have been rapidly declining in the eastern, central, and southern United States for decades. Land use change and an incompatibility between northern bobwhite resource needs and human land use practices have driven declines. Here, we applied occupancy analyses on two spatial scales (state level and ecoregion level) to more than 5,000 northern bobwhite surveys conducted over 6 y across the entire state of Arkansas to explore patterns in occupancy and land use variables, and to identify priority areas for management and conservation. At the state level, northern bobwhite occupied 29% of sites and northern bobwhite were most likely to occur in areas with a high percentage of early successional habitat (grassland, pasture, and shrubland). The statewide model predicted that northern bobwhite were likely to occur (≥ 75% predicted occupancy) in < 20% of the state. Arkansas is comprised of five distinct ecoregions, and analyses at the ecoregion spatial scale showed that habitat associations of northern bobwhite could vary between ecoregions. For example, early successional habitat best predicted northern bobwhite occupancy in both the Arkansas River Valley and Ozark Mountains ecoregions, and other habitat associations such as the proportion of herbaceous habitat and hay-pasture habitat, respectively, further refined predictions. Contrastingly, richness of land cover classes alone best predicted northern bobwhite occupancy in the Ouachita Mountains ecoregion. Ecoregion-level models were thus more discerning than the state-level model and should be more helpful to managers in identifying priority conservation areas. However, in two of five ecoregions, surveys too rarely encountered northern bobwhite to accurately predict their occurrence. We found that likely occupied northern bobwhite habitat lay primarily on private properties (95%), but that numerous public entities own and manage land identified as suitable or likely occupied. We conclude that management of northern bobwhite in Arkansas could benefit from cooperation among state, federal, and military partners, as well as surrounding private landowners and that ecoregion-specific models may be more useful in identifying priority areas for management. Our approach incorporates multiple landscape scales when using remote sensing technology in conjunction with monitoring data and could have important application for the management of northern bobwhite and other grassland bird species.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-002","usgsCitation":"Lassiter, E.V., Asher, M., Christie, G., Gale, C., Massey, A., Massery, C., MIddaugh, C., Veon, J., and DeGregorio, B.A., 2021, Northern bobwhite occupancy patterns on multiple spatial scales across Arkansas: Journal of Fish and Wildlife Management, v. 12, no. 2, p. 502-512, https://doi.org/10.3996/JFWM-21-002.","productDescription":"11 p.","startPage":"502","endPage":"512","ipdsId":"IP-125981","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-002","text":"Publisher Index Page"},{"id":396907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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R.","contributorId":288241,"corporation":false,"usgs":false,"family":"MIddaugh","given":"C. R.","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":837584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veon, J.","contributorId":288245,"corporation":false,"usgs":false,"family":"Veon","given":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":837585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837586,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70225682,"text":"70225682 - 2021 - Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing","interactions":[],"lastModifiedDate":"2021-11-03T13:14:26.474395","indexId":"70225682","displayToPublicDate":"2021-10-28T08:13:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing","docAbstract":"Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies.
Identifying the physical habitat characteristics associated with riverine freshwater mussel assemblages is challenging but crucial for understanding the causes of mussel declines. The occurrence of mussels in multispecies beds suggests that common physical factors influence or limit their occurrence. Fine-scale geomorphic and hydraulic factors (e.g., scour, bed stability) are predictive of mussel-bed occurrence, but they are computationally challenging to represent at intermediate or riverscape scales. We used maximum entropy (MaxEnt) modeling to evaluate associations between riverscape-scale hydrogeomorphic variables and mussel-bed presence along 530 river km of the Meramec River basin, USA, to identify river reaches that are fundamentally suitable for mussels as well as those that are not. We obtained the locations of mussel beds from an existing, multiyear dataset, and we derived river variables from high-resolution, open-source datasets of aerial imagery and topography. Mussel beds occurred almost exclusively in reaches identified by our model as suitable; these were characterized by laterally stable channels, absence of adjacent bluffs, proximity to gravel bars, higher stream power, and larger areas of contiguous water (a proxy for drought vulnerability). We validated our model findings based on model sensitivity using a set of mussel-bed locations not used in model development. These findings can inform how resource managers allocate survey, monitoring, and conservation efforts.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc-d-20-00002","usgsCitation":"Keymanesh, K., Rosenberger, A.E., Lindner, G., Bouska, K.L., and McMurray, S.E., 2021, Riverscape-scale modeling of fundamentally suitable habitat for mussel assemblages in an Ozark River system, Missouri: Freshwater Mollusk Biology and Conservation, v. 24, no. 2, p. 43-58, https://doi.org/10.31931/fmbc-d-20-00002.","productDescription":"16 p.","startPage":"43","endPage":"58","ipdsId":"IP-113472","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450336,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-20-00002","text":"Publisher Index Page"},{"id":433559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Meramec River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.23145192205784,\n 38.57316922340365\n ],\n [\n -91.80686253958456,\n 38.57316922340365\n ],\n [\n -91.80686253958456,\n 37.62945983446684\n ],\n [\n -90.23145192205784,\n 37.62945983446684\n ],\n [\n -90.23145192205784,\n 38.57316922340365\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Keymanesh, K.","contributorId":317234,"corporation":false,"usgs":false,"family":"Keymanesh","given":"K.","email":"","affiliations":[],"preferred":false,"id":908903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindner, G.","contributorId":341798,"corporation":false,"usgs":false,"family":"Lindner","given":"G.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":908906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMurray, Stephen E.","contributorId":206918,"corporation":false,"usgs":false,"family":"McMurray","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":908907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225582,"text":"sir20215020 - 2021 - Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","interactions":[],"lastModifiedDate":"2022-06-16T19:45:30.631881","indexId":"sir20215020","displayToPublicDate":"2021-10-27T10:00:17","publicationYear":"2021","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":"2021-5020","displayTitle":"Geologic and Hydrogeologic Characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, Northern Greater Denver Basin, Southeastern Laramie County, Wyoming","title":"Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming","docAbstract":"In cooperation with the Wyoming State Engineer’s Office, the U.S. Geological Survey studied the geologic and hydrogeologic characteristics of Cenozoic and Upper Cretaceous strata at a location in southeastern Laramie County within the Wyoming part of the Cheyenne Basin, the northern subbasin of the greater Denver Basin. The study aimed to improve understanding of the aquifers/aquifer systems in these strata, motivated in part by declining groundwater levels and interest in exploring future groundwater supplies. Based on detailed geologic characterization using information obtained by drilling and coring a 960-foot-(ft) deep exploratory borehole, and comparisons with previously published descriptions, identified Cenozoic lithostratigraphic units included 40 ft of Quaternary older alluvial fan deposits consisting of an unconsolidated mixture of sand and gravel with lesser quantities of silt and clay in varying proportions and the underlying 407.3-ft-thick White River Formation of late Eocene-Oligocene age consisting largely of mudrocks with sparse thin beds of sandstone, muddy gravel, and conglomeratic mudrocks. Identified Upper Cretaceous lithostratigraphic units included the 351.6-ft-thick Lance Formation, consisting of terrestrial sedimentary rocks including mudrocks (muddy shale and silty and sandy shale, siltstone, claystone, and mudstone) interbedded with much smaller quantities of very fine- to medium-grained muddy and silty sandstone and coal; the 79.6-ft-thick Fox Hills Sandstone, consisting of a transitional marine sequence of muddy or silty sandstone present in five individual beds; and 86.7 ft of the upper transition member of the Pierre Shale, consisting largely of marine sedimentary rocks such as muddy shale. Beds of the upper and lower Fox Hills Sandstone were separated by tongues of the Lance Formation and upper transition member of the Pierre Shale, respectively.
The White River hydrogeologic unit, consisting of the entire White River Formation or Group at the study site, did not contain any substantial secondary permeability features in the mudrocks that composed almost all the unit. A monitoring well (BR–1) was completed in the White River aquifer with the well screen open to the only coarse-grained unit (muddy sandstone) that had sufficient thickness and permeability to be considered as an aquifer. Sampling of the well for a broad suite of constituents indicated groundwater generally was of excellent quality except dissolved arsenic was detected at a concentration greater than the U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level, and dissolved sodium was measured at a concentration greater than several EPA Drinking Water Advisory Levels (DWAs) for the constituent. Well development, well purging for groundwater sampling, and calculated aquifer properties indicated the sandstone aquifer screened by monitoring well BR–1 was not very productive. Analysis of the well water-level responses in BR–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response with wellbore-storage effects. Hydraulic properties estimated based on these responses yielded values of hydraulic conductivity (K, 0.057 foot per day [ft/d]), specific storage (Ss, 1.6×10−6 per foot [ft−1]) and porosity (n, 0.43). Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated an upward trend (+1.13 foot per year [ft/yr]) during the period analyzed, September 5, 2014, to September 30, 2017.
Lithologic characteristics of the Lance hydrogeologic unit, consisting of the entire Lance Formation at the study site, indicated a potential aquifer in a “sandy” interval in the upper part of the unit. Most of the Lance hydrogeologic unit below the “sandy” interval consisted of various low-permeability lithologies unlikely to yield substantial quantities of water. This lower part of the hydrogeologic unit likely functions as a confining unit separating the underlying Lance-Fox Hills aquifer. A geologic cross section constructed for this study indicated fine-grained sediments composed most of the Lance Formation/hydrogeologic unit not only at the study location, but also throughout southern Laramie County along the line of section and throughout the Wyoming and Colorado parts of the Cheyenne Basin. A monitoring well (LN–1) completed in a sandstone bed in the “sandy” interval of the Lance hydrogeologic unit produced a mean of about 23 gallons per minute (gal/min) during well development, indicating sandstone beds can form moderately productive confined subaquifers in this part of the hydrogeologic unit. Analysis of the well water-level responses in well LN–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties estimated based on these responses yielded values for a lower bounding K of 0.60 ft/d, Ss of 1.6×10−6 ft−1, and n of 0.38. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−0.86 ft/yr) during the period analyzed (November 8, 2014, to September 30, 2017). Analyses for a broad suite of constituents in samples from well LN–1 indicated groundwater quality generally was excellent, although dissolved sodium was measured at a concentration greater than two EPA DWA levels for the constituent.
Because of the absence of any overlying or intertonguing sandstone beds belonging to the lower/basal part of the Lance Formation, the Lance-Fox Hills aquifer at the study site consisted only of the five sandstone beds of the Fox Hills Sandstone. The cross section constructed for this study illustrated how the Fox Hills Sandstone, and thus, most of the Lance-Fox Hills aquifer, consists of a series of sandstone bodies that overlap (shingle) upward to the east across southern Laramie County. These bodies collectively form a fairly continuous body of sandstone, thus potentially forming an areally extensive aquifer across southern Laramie County, and by extension, throughout most of the formation’s extent in the Wyoming part of the Cheyenne Basin, as is the case in the Colorado part of the basin. A monitoring well (FH–1) completed in part of the thickest sandstone bed of the Lance-Fox Hills aquifer was moderately to highly productive and easily produced 25 to 30 gal/min after development. Substantially larger water production rates likely could be obtained by penetrating the full thickness of this bed and by completing a well open to the other overlying and underlying sandstone beds of the aquifer. Analysis of the water-level responses in well FH–1 to atmospheric loading and Earth tides indicated the responses were consistent with a confined-aquifer response. Hydraulic properties computed based on these responses yielded values for a lower bounding estimate for K of 0.26 ft/d, for Ss of 1.0×10−6 ft−1, and for n of 0.41. Water levels filtered to remove the effects of atmospheric loading and Earth tides indicated a downward trend (−1.74 ft/yr) during the period analyzed, December 19, 2014, to September 30, 2017. Sampling of monitoring well FH–1 and two production wells completed in the Fox Hills Sandstone in other parts of Laramie County indicated groundwater quality generally is excellent, although pH exceeded a recommended EPA aesthetic drinking-water standard (Secondary Maximum Contaminant Level) in two of three sampled wells, total dissolved solids concentrations exceeded the Secondary Maximum Contaminant Level in one of the two sampled production wells, and dissolved sodium was measured in all three sampled wells at a concentration greater than two EPA DWA levels for the constituent. The Wyoming Class II agricultural (irrigation) sodium adsorption ratio standard of 8 was exceeded in all three sampled wells, indicating these waters are not suitable for irrigation use.
Computed vertical hydraulic gradients indicated a strong potential for downward flow throughout the groundwater system at the study site, including from the low-yielding aquifer in the upper White River Formation/hydrogeologic unit (monitoring well BR–1) to the sandstone subaquifer in the Lance Formation/hydrogeologic unit (monitoring well LN–1), and from the Lance subaquifer (monitoring well LN–1) to the sandstone bed/aquifer that composes much of the Lance-Fox Hills aquifer thickness at the study site (monitoring well FH–1). However, large hydraulic-head differences between wells indicated high resistance to vertical flow attributable to the low vertical hydraulic conductivity of intervening strata, which consisted almost entirely of low-permeability mudrocks. The confined nature of the sandstone aquifers monitored by the various wells coupled with dissimilarities between groundwater-level fluctuations and trends in groundwater levels indicated downward flow through the intervening strata (primarily mudrocks in the various lithostratigraphic/hydrogeologic units) between the examined sets of wells likely was small.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215020","collaboration":"Prepared in cooperation with the Wyoming State Engineer’s Office","usgsCitation":"Bartos, T.T., Galloway, D.L., Hallberg, L.L., Dechesne, M., Diehl, S.F., and Davidson, S.L., 2021, Geologic and hydrogeologic characteristics of the White River Formation, Lance Formation, and Fox Hills Sandstone, northern greater Denver Basin, southeastern Laramie County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2021–5020, 219 p., 1 pl., https://doi.org/10.3133/sir20215020.","productDescription":"Report: xvii, 219 p.; Appendix Table; Plate: 42.00 x 63.00 inches; Data Release; Dataset","numberOfPages":"242","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110049","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":390939,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS groundwater data for Wyoming, in USGS water data for the Nation"},{"id":390938,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPLA74","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Atmospheric-loading frequency response functions and groundwater levels filtered for the effects of atmospheric loading and solid Earth tides for three USGS monitoring wells, southeastern Laramie County, Wyoming, 2014–2017"},{"id":390936,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_plate.pdf","text":"Plate","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Plate","linkHelpText":"— Construction of monitoring wells BR–1, LN–1, and FH–1, and geophysical logs, generalized lithology, and interpreted lithostratigraphy for exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390937,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020_table1.1.pdf","text":"Table 1.1","size":"500 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020 Appendix Table","linkHelpText":"— Description of core collected from exploratory borehole LC–F1, southeastern Laramie County, Wyoming"},{"id":390934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5020/coverthb.jpg"},{"id":390935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5020/sir20215020.pdf","text":"Report","size":"26.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5020"}],"country":"United States","state":"Wyoming","county":"Laramie County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.6506,41.651],[-104.6491,41.5656],[-104.0521,41.5654],[-104.052,41.3949],[-104.0526,41.0236],[-104.0528,41.0017],[-104.1399,41.0019],[-104.4725,41.0027],[-104.4875,41.0027],[-104.5606,41.0028],[-104.5679,41.0028],[-104.6087,41.0046],[-104.6134,41.0048],[-104.6337,41.0056],[-104.6648,41.0047],[-104.6837,41.0041],[-104.7013,41.0035],[-104.83,40.9996],[-104.8341,40.9996],[-104.9385,40.9995],[-104.9425,40.9995],[-105.1109,40.9993],[-105.2763,40.9998],[-105.2774,41.6567],[-105.1706,41.6535],[-105.0575,41.6537],[-104.9419,41.6537],[-104.6506,41.651]]]},\"properties\":{\"name\":\"Laramie\",\"state\":\"WY\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601