White sturgeon (Acipenser transmontanus) are long-lived, late-maturing, benthic-feeding fish that are ideal candidates for assessing the bioaccumulation of persistent chemicals. In this study, composite tissue samples of brain, liver, gonad, and fillet were collected from white sturgeon in 2009 from five sites in the Hanford Reach of the Columbia River near Hanford, Washington. The composite tissue samples at each site were analyzed for the concentrations of individual chemicals as well as the total concentrations of four chemical classes: (1) organochlorine (OC) pesticides, (2) industrial or personal care products, (3) polybrominated diphenyl ether (PBDE) congeners, and (4) polychlorinated biphenyl (PCB) congeners. The results showed that chemicals from all four classes were present in the fish, and that OC pesticides and degradation products (such as oxychlordane, fipronil sulfide, and dichlorodiphenyltrichloroethane (DDT) degradates, PBDE congeners, and PCB congeners) often were present in all tissues and at all sites. Gonad tissues generally had the highest total concentration of each chemical class, followed by brains, livers, and fillets. The concentrations of several chemicals or chemical classes exceeded many of the human health benchmarks for two different populations (general/recreational consumers and subsistence/Tribal consumers), and this was especially true for the total concentrations of DDT degradation products and PCB congeners. These results suggest that continued monitoring of resident fish in the Hanford Reach, as well as assessments of the health impacts on consumers of those fish, are warranted.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225020","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Payne, S.E., Wise, D.R., Davis, J.W., and Nilsen, E.B., 2022, Assessment of persistent chemicals of concern in white sturgeon (Acipenser transmontanus) in the Hanford Reach of the Columbia River, southeastern Washington, 2009: U.S. Geological Survey Scientific Investigations Report 2022–5020, 25 p., https://doi.org/10.3133/sir20225020.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-113471","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":402577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5020/coverthb.jpg"},{"id":402579,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5020/images"},{"id":402580,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5020/sir20225020.XML"},{"id":402578,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5020/sir20225020.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5020"},{"id":402624,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225020/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5020"},{"id":502374,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113220.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.05859375,\n 46.13417004624326\n ],\n [\n -118.89404296875,\n 46.13417004624326\n ],\n [\n -118.89404296875,\n 46.95776134668866\n ],\n [\n -120.05859375,\n 46.95776134668866\n ],\n [\n -120.05859375,\n 46.13417004624326\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
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Portland, Oregon 97201
In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass (Zostera marina L.) and surf smelt (Hypomesus pretiosus) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221054","usgsCitation":"Smith, C.D., and Liedtke, T.L., 2022, Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington: U.S. Geological Survey Open-File Report 2022–1054, 17 p., https://doi.org/10.3133/ofr20221054.","productDescription":"Report: v, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-117971","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":402574,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGJ3ZH","text":"USGS data release","description":"USGS Data Release.","linkHelpText":"Data collected in 2010 to evaluate habitat availability for surf smelt and eelgrass in response to sea level rise on Bainbridge Island, Puget Sound, Washington State, USA"},{"id":402572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1054/coverthb.jpg"},{"id":402573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1054"},{"id":402619,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221054/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1054"},{"id":402575,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1054/images"},{"id":402576,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1054/ofr20221054.XML"},{"id":501780,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113219.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6678466796875,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.487513008956554\n ],\n [\n -122.23937988281251,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.964180715412276\n ],\n [\n -122.6678466796875,\n 47.487513008956554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2022.894571","usgsCitation":"Friedl, M.A., Woodcock, C.E., Olofsson, P., Zhu, Z., Loveland, T., Stanimirova, R., Arevalo, P., Bullock, E.L., Hu, K., Zhang, Y., Turlej, K., Tarrio, K., Kristina, M., Gorelick, N., Wang, J.A., Barber, C., and Souza Jr., C., 2022, Medium spatial resolution mapping of global land cover and land cover change across multiple decades from Landsat: Frontiers in Remote Sensing, v. 3, 894571, 15 p., https://doi.org/10.3389/frsen.2022.894571.","productDescription":"894571, 15 p.","ipdsId":"IP-142442","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":447282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2022.894571","text":"Publisher Index 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Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":901844,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hu, Kai-Ting","contributorId":337047,"corporation":false,"usgs":false,"family":"Hu","given":"Kai-Ting","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901845,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhang, Yingtong","contributorId":337048,"corporation":false,"usgs":false,"family":"Zhang","given":"Yingtong","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901846,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Turlej, Konrad","contributorId":337049,"corporation":false,"usgs":false,"family":"Turlej","given":"Konrad","email":"","affiliations":[{"id":78943,"text":"Jagiellonian University","active":true,"usgs":false}],"preferred":false,"id":901847,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tarrio, Katelyn","contributorId":337050,"corporation":false,"usgs":false,"family":"Tarrio","given":"Katelyn","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901848,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kristina, McAvoy","contributorId":337051,"corporation":false,"usgs":false,"family":"Kristina","given":"McAvoy","email":"","affiliations":[{"id":80956,"text":"University of Boston","active":true,"usgs":false}],"preferred":false,"id":901849,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gorelick, Noel","contributorId":294417,"corporation":false,"usgs":false,"family":"Gorelick","given":"Noel","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":901850,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Jonathan A.","contributorId":337052,"corporation":false,"usgs":false,"family":"Wang","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":901851,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Barber, Christopher P. 0000-0003-0570-1140","orcid":"https://orcid.org/0000-0003-0570-1140","contributorId":223102,"corporation":false,"usgs":true,"family":"Barber","given":"Christopher","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901852,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Souza Jr., Carlos","contributorId":337053,"corporation":false,"usgs":false,"family":"Souza Jr.","given":"Carlos","affiliations":[{"id":80958,"text":"IMAZON","active":true,"usgs":false}],"preferred":false,"id":901853,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70232344,"text":"70232344 - 2022 - Biofilms in the Critical Zone: Distribution and mediation of processes","interactions":[],"lastModifiedDate":"2022-06-28T13:30:54.444935","indexId":"70232344","displayToPublicDate":"2022-06-28T08:24:40","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Biofilms in the Critical Zone: Distribution and mediation of processes","docAbstract":"Microbial biofilms occur in all levels of the Critical Zone (CZ); they are on and in the vegetation, throughout the soil-saprolite zone, and along fractures in deep subsurface. Here we discuss biofilms in each level of the CZ with a focus in the soil-saprolite continuum. We show how scanning electron microscope (SEM) images provide an appropriate scale to explore microbe mineral interactions in the CZ and can be used without extensive sample preparation. Through SEM imaging, we show that biofilms weather primary minerals, that macropores and fractures are hotspots of biofilm development, that biologic precipitation of short-range-order minerals (SROs) occurs in biofilms, and that biofilms are important in the process of organic matter stabilization.","largerWorkTitle":"Biogeochemistry of the Critical Zone","language":"English","publisher":"Springer","doi":"10.1007/978-3-030-95921-0_4","usgsCitation":"Schulz, M., and Manies, K.L., 2022, Biofilms in the Critical Zone: Distribution and mediation of processes, chap. 4 of Biogeochemistry of the Critical Zone, p. 89-119, https://doi.org/10.1007/978-3-030-95921-0_4.","productDescription":"31 p.","startPage":"89","endPage":"119","ipdsId":"IP-105346","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":402593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Critical Zone, Earth","noUsgsAuthors":false,"publicationDate":"2022-05-17","publicationStatus":"PW","contributors":{"editors":[{"text":"Wymore, Adam S.","contributorId":243438,"corporation":false,"usgs":false,"family":"Wymore","given":"Adam","email":"","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":845300,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Yang, Wendy H.","contributorId":292622,"corporation":false,"usgs":false,"family":"Yang","given":"Wendy","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":845301,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Silver, Whendee L.","contributorId":80998,"corporation":false,"usgs":true,"family":"Silver","given":"Whendee L.","affiliations":[],"preferred":false,"id":845302,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"McDowell, William H.","contributorId":97233,"corporation":false,"usgs":true,"family":"McDowell","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":845303,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Chorover, Jon 0000-0001-9497-0195","orcid":"https://orcid.org/0000-0001-9497-0195","contributorId":139472,"corporation":false,"usgs":false,"family":"Chorover","given":"Jon","email":"","affiliations":[],"preferred":false,"id":845304,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":845290,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232351,"text":"70232351 - 2022 - Asking nicely: Best practices for requesting data","interactions":[],"lastModifiedDate":"2022-06-29T12:37:39.400674","indexId":"70232351","displayToPublicDate":"2022-06-28T07:35:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Asking nicely: Best practices for requesting data","docAbstract":"Compiling disparate datasets into publicly available composite databases helps natural resource communities explore ecological trends and effectively manage across spatiotemporal scales. Though some studies have reported on the database construction phase, fewer have evaluated the data acquisition and distribution process. To facilitate future data sharing collaborations, Louisiana State University surveyed data providers and requestors to understand the characteristics of effective data requests and sharing. Data providers were largely U.S. natural resource agency personnel, and they reported that unclear data requests, privacy issues, and rigid timelines and formats were the greatest barriers toward providing data, but that they were motivated by improving science and collaboration. Data requestors identified challenges such as evolving needs, standardization issues, and insufficient resources (time and funding) as barriers to compiling data for these types of efforts. In a time of big data, open access, and collaboration, significant scientific advances can be made with effective requests and inclusion of data sets into larger and more powerful databases.
The range of 187Re/188Os values measured from samples of five organic-rich lacustrine mudstones units in the Eocene Green River Formation in the easternmost Uinta Basin covaries with organic matter diversity driven by changing water column conditions. A set of samples from the Douglas Creek Member has the highest pristane/phytane ratio and lowest β-carotane/n-C30 ratio compared to overlying units, indicating deposition in an oxic-anoxic environment with low salinity that would have allowed for the accumulation of a diverse assemblage of aquatic organisms. These samples define the broadest 187Re/188Os range of 1504. In contrast, samples from the R6 and Mahogany zones possess lower pristane/phytane ratios and higher β-carotane/n-C30 ratios indicating deposition in a more restricted lacustrine environment with elevated salinities and alkalinities that would have limited aquatic organic matter diversity. The R6 and Mahogany zones have the narrowest range of 187Re/188Os values measured in this study of 254.9 and 154.6, respectively. As noted by previous workers, these results suggest that organic matter diversity plays a primary role in determining the range of 187Re/188Os ratios in a sample set, and in turn the uncertainty of Re-Os age determinations from organic-rich sedimentary rocks.
The Re-Os data from the R3 zone and R6 zone yield ages of 49.7 ± 3.4 Ma and 42.0 ± 18 Ma, respectively, which are statistically indistinguishable based on 2σ uncertainty from three previously reported Re-Os age determinations and those provided by 40Ar/39Ar geochronology of interbedded volcanic ash beds. Although the age uncertainty is high, these findings further highlight the importance of Re-Os geochronology in lacustrine basins, particularly those with thick mudstone successions that lack volcanic ash layers, reliable biostratigraphy, or magnetostratigraphic control. In these cases, even ages with large uncertainties can be useful to constrain burial history and thermal history models.
Together, the initial 187Os/188Os ratios of five sets of samples analyzed from the Uinta Basin define the largest Os isotope stratigraphic record from any lacustrine basin compiled to date and record a shift from a value of 1.40 to 1.48 between the R3 and R4 zones in the lower part of the Parachute Creek Member. This small shift may signify a change in the chemical weathering products that entered the lake preserved 20 to 50 m above the contact between the Douglas Creek and the lower Parachute Creek members during a period when the basin transitioned from a shallow lake with mostly open hydrology to an alkaline lake with more frequent basin restrictions.
The need to balance economic development with impacts to Arctic wildlife has been a prominent subject since petroleum exploration began on the North Slope of Alaska, USA, in the late 1950s. The North Slope region includes polar bears (Ursus maritimus) of the southern Beaufort Sea subpopulation, which has experienced a long-term decline in abundance. Pregnant polar bears dig dens in snow drifts during winter and are vulnerable to disturbance, as den abandonment and mortality of neonates may result. Maternal denning coincides with the peak season of petroleum exploration and construction, raising concerns that human activities may disrupt denning. To minimize disturbance of denning polar bears, aerial infrared (AIR) surveys are routinely used to search for dens within planned industry activity areas and that information is used to implement mitigation. Aerial infrared surveys target the heat signature emanating from dens. Despite use by industry for >15 years, the efficacy of AIR and the factors that impact its ability to detect dens remains uncertain. Here, we evaluate AIR using artificial dens and observers naïve to locations to estimate detection probability and its relationship with covariates including weather variables, den characteristics, infrared sensor and altitude, and survey order to identify potential evidence of in-flight observer learning occurring between surveys. In December 2019 we constructed 14 dens (each with an artificial heat source), and 11 control sites (disturbed sites without dens). Between December 2019 and January 2020, 3 survey crews flew 6 independent AIR surveys within the vicinity of dens and control sites and video-recorded AIR imagery. Observers identified putative dens either in flight or during post-flight review of recordings. We assessed detection probability with a simple Bayesian model using 3 subsets of data: 1) all detection/non-detection data; 2) detection/non-detection data restricted to instances where sample sites were confirmed to have been properly scanned by AIR during post-study verification (i.e., when den locations were known); and 3) all dens visible on the recorded imagery during post-study verification, even if they were not seen during the survey or during post-flight review. Subsets 1 and 2 most closely resembled den surveys flown for oil and gas industry and had detection probabilities of 0.15 (95% CI = 0.08–0.23) and 0.24 (95% CI = 0.13–0.37), respectively. Detection probability was 0.41 (95% CI = 0.25–0.58) for subset 3. Higher wind speeds and larger den volume negatively influenced detection probability. Our low detection rate compared to previous studies could partially be the result of differences in study design, such as survey flight patterns. Our results suggest that AIR, as it is currently used, is unlikely to detect most polar bear dens in surveyed areas. Resource managers who use AIR should consider a suite of additional methods (e.g., habitat mapping, probabilistic den distribution, AIR methodology improvements) for minimizing impacts of industry on denning polar bears.
An analysis of the potential for deposits of critical minerals and elements in Maine presented here includes data and discussions for antimony, beryllium, cesium, chromium, cobalt, graphite, lithium, manganese, niobium, platinum group elements, rhenium, rare earth elements, tin, tantalum, tellurium, titanium, uranium, vanadium, tungsten, and zirconium. Deposits are divided into two groups based on geological settings and common ore-deposit terminology. One group consists of known deposits (sediment-hosted manganese, volcanogenic massive sulphide, porphyry copper-molybdenum, mafic- and ultramafic-hosted nickel-copper [-cobalt-platinum group elements], pegmatitic lithium-cesium-tantalum) that are in most cases relatively large, well-documented, and have been explored extensively in the past. The second, and much larger group of different minerals and elements, comprises small deposits, prospects, and occurrences that are minimally explored or unexplored. The qualitative assessment used in this study relies on three key criteria: (1) the presence of known deposits, prospects, or mineral occurrences; (2) favourable geologic settings for having certain deposit types based on current ore deposit models; and (3) geochemical anomalies in rocks or stream sediments, including panned concentrates. Among 20 different deposit types considered herein, a high resource potential is assigned only to three: (1) sediment-hosted manganese, (2) mafic- and ultramafic-hosted nickel-copper(-cobalt-platinum group elements), and (3) pegmatitic lithium-cesium-tantalum. Moderate potential is assigned to 11 other deposit types, including: (1) porphyry copper-molybdenum (-rhenium, selenium, tellurium, bismuth, platinum group elements); (2) chromium in ophiolites; (3) platinum group elements in ophiolitic ultramafic rocks; (4) granite-hosted uranium-thorium; (5) tin in granitic plutons and veins; (6) niobium, tantalum, and rare earth elements in alkaline intrusions; (7) tungsten and bismuth in polymetallic veins; (8) vanadium in black shales; (9) antimony in orogenic veins and replacements; (10) tellurium in epithermal deposits; and (11) uranium in peat.
","language":"English","publisher":"Atlantic Geology","doi":"10.4138/atlgeo.2022.007","usgsCitation":"Slack, J.F., Beck, F., Bradley, D., Felch, M.M., Marvinney, R.G., and Whittaker, A., 2022, Potential for critical mineral deposits in Maine, USA: Atlantic Geoscience, v. 58, p. 155-191, https://doi.org/10.4138/atlgeo.2022.007.","productDescription":"37 p.","startPage":"155","endPage":"191","ipdsId":"IP-138621","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":447292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.4138/atlgeo.2022.007","text":"External Repository"},{"id":418503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Their populations have declined for over a century due to many factors including coastal development, nest predation, pet trade and drowning in crab traps. Without action, terrapin populations will continue to decline. 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The success of littoral spawning fishes depends on the timing and variability of water levels. The onset of drought between 2017 and 2018 provided an opportunity to evaluate the timing of hatch dates and relative abundance of young-of-year Largemouth Bass Micropterus salmoides across two water years of varying water temperatures and water levels in a southwestern U.S. reservoir. A retrospective analysis of otoliths in young-of-year Largemouth Bass revealed similar hatch dates in 2017 (14 April–29 May) and 2018 (13 April–28 May) despite differences in water temperature and water level rate of change. Median water temperature during hatch dates was greater in 2017 (median 19.0°C, range 14.3–24.4°C) than 2018 (17.6°C, range 13.5–21.7°C). Water level rate of change during hatch dates in 2017 was positive (+3.1 to +13.1 cm/d), which reflected reservoir filling. In contrast, water level rate of change during hatch dates in 2018 was negative (−8.5 to −0.6 cm/d), which reflected reservoir receding. Relative abundance of young-of-year fish was greater in 2017 (21.7 fish/h) when the reservoir was filling compared with relative abundance in 2018 (6.8 fish/h) when the reservoir was receding. The median growth rate was greater in 2017 (1.02 mm/d) when the reservoir was filling than in 2018 (0.82 mm/d) when the reservoir was receding. Despite differences in water temperature and contrasting reservoir levels between the two water years, the Largemouth Bass population in a southwest U.S. reservoir exhibited similar hatch dates reported for the species in southeastern and northeastern U.S. reservoirs. While water demand in the 21st century may exceed availability, the opportunity exists to collaborate with water managers to benefit Largemouth Bass populations in southwestern reservoirs.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-071","usgsCitation":"Vaisvil, A., Caldwell, C.A., and Frey, E., 2022, Water-level fluctuations and water temperature effects on young-of-year Largemouth Bass in a southwest irrigation reservoir: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 534-543, https://doi.org/10.3996/JFWM-21-071.","productDescription":"10 p.","startPage":"534","endPage":"543","ipdsId":"IP-133206","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-071","text":"Publisher Index Page"},{"id":429779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Sierra County","otherGeospatial":"Elephant Butte Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.12656805641583,\n 33.33034159767031\n ],\n [\n -107.22643051078117,\n 33.33034159767031\n ],\n [\n -107.22643051078117,\n 33.13668854992092\n ],\n [\n -107.12656805641583,\n 33.13668854992092\n ],\n [\n -107.12656805641583,\n 33.33034159767031\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Vaisvil, Alexander","contributorId":337757,"corporation":false,"usgs":false,"family":"Vaisvil","given":"Alexander","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":902658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frey, Eric","contributorId":337759,"corporation":false,"usgs":false,"family":"Frey","given":"Eric","email":"","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":902659,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232315,"text":"fs20223043 - 2022 - Comparison of water year 2021 streamflow to historical data at selected sites in the Snake River Basin, Wyoming","interactions":[],"lastModifiedDate":"2026-03-24T21:26:39.539224","indexId":"fs20223043","displayToPublicDate":"2022-06-27T11:35:47","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3043","displayTitle":"Comparison of Water Year 2021 Streamflow to Historical Data at Selected Sites in the Snake River Basin, Wyoming","title":"Comparison of water year 2021 streamflow to historical data at selected sites in the Snake River Basin, Wyoming","docAbstract":"The headwaters of the Snake River are in the mountains of northwestern Wyoming on lands primarily administered by the National Park Service and the Bridger-Teton National Forest. Streamflow from the Snake River Basin has been measured at some sites for more than 100 years. Water from this drainage basin is used for recreational, agricultural, and municipal uses and power generation. Because of the many uses of the water and the ongoing drought in the Western United States, there is interest in how streamflow in water year 2021 compared to the historical data. Historical streamflow data are defined as the operational period of the streamgage through water year 2020. A water year is named for the year in which it ends; therefore, water year 2021 is October 1, 2020, through September 30, 2021.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223043","usgsCitation":"Law, R.M., Campbell, J.R., Wheeler, J.D., and Eddy-Miller, C.E., 2022, Comparison of water year 2021 streamflow to historical data at selected sites in the Snake River Basin, Wyoming: U.S. Geological Survey Fact Sheet 2022–3043, 5 p., https://doi.org/10.3133/fs20223043.","productDescription":"5 p.","numberOfPages":"5","onlineOnly":"Y","ipdsId":"IP-136663","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":402526,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223043/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402508,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3043/images"},{"id":402505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3043/coverthb.jpg"},{"id":402506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3043/fs20223043.pdf","text":"Report","size":"6.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3043"},{"id":402507,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3043/fs20223043.XML"},{"id":501494,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113217.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Snake River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.02508544921875,\n 43.21118152841771\n ],\n [\n -110.45928955078125,\n 43.21118152841771\n ],\n [\n -110.45928955078125,\n 44.09744824027576\n ],\n [\n -111.02508544921875,\n 44.09744824027576\n ],\n [\n -111.02508544921875,\n 43.21118152841771\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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521 Progress Circle, Suite 6
Cheyenne, WY 82007
The RESTORE Council Monitoring and Assessment Program (CMAP), administered by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), spatially and temporally inventoried programs in the Gulf of Mexico focused on water quality and habitat monitoring and mapping.
","language":"English","publisher":"National Oceanic and Atmospheric Administration, United States Geological Survey","usgsCitation":"RESTORE Council Monitoring and Assessment Program, 2022, Exploring CMAP products: Mapping, 2 p.","productDescription":"2 p.","ipdsId":"IP-122532","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":402512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402511,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://cdn.coastalscience.noaa.gov/projects-attachments/343/CMAP_Mapping_One-pager.pdf","size":"1272 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":402501,"type":{"id":15,"text":"Index Page"},"url":"https://coastalscience.noaa.gov/project/restore-council-monitoring-and-assessment-program-building-a-comprehensive-monitoring-network/"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.140625,\n 26.509904531413927\n ],\n [\n -98.37158203125,\n 25.97779895546436\n ],\n [\n -97.80029296875,\n 25.859223554761407\n ],\n [\n -97.40478515625,\n 25.780107118422244\n ],\n [\n -97.27294921875,\n 25.859223554761407\n ],\n [\n -80.26611328125,\n 25.145284610685064\n ],\n [\n -80.04638671875,\n 25.780107118422244\n ],\n [\n -79.91455078125,\n 26.60817437403311\n ],\n [\n -80.04638671875,\n 27.0982539061379\n ],\n [\n -80.22216796875,\n 27.430289738862594\n ],\n [\n -80.48583984375,\n 28.459033019728043\n ],\n [\n -81.18896484375,\n 29.82158272057499\n ],\n [\n -81.36474609375,\n 30.4297295750316\n ],\n [\n -81.45263671875,\n 30.826780904779774\n ],\n [\n -81.18896484375,\n 31.55981453201843\n ],\n [\n -91.34033203125,\n 31.98944183792288\n ],\n [\n -91.669921875,\n 31.316101383495624\n ],\n [\n -98.59130859375,\n 29.649868677972304\n ],\n [\n -99.140625,\n 26.509904531413927\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"RESTORE Council Monitoring and Assessment Program","contributorId":292577,"corporation":true,"usgs":false,"organization":"RESTORE Council Monitoring and Assessment Program","id":845233,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70232313,"text":"70232313 - 2022 - Statistical consideration of nonrandom treatment applications reveal region-wide benefits of widespread post-fire restoration action","interactions":[],"lastModifiedDate":"2022-06-27T15:35:04.472666","indexId":"70232313","displayToPublicDate":"2022-06-27T10:25:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Statistical consideration of nonrandom treatment applications reveal region-wide benefits of widespread post-fire restoration action","docAbstract":"Accurate predictions of ecological restoration outcomes are needed across the increasingly large landscapes requiring treatment following disturbances. However, observational studies often fail to account for nonrandom treatment application, which can result in invalid inference. Examining a spatiotemporally extensive management treatment-- post-fire seeding of declining sagebrush shrubs across the semiarid U.S. over two decades -- we quantify drivers and consequences of selection biases in restoration, using remotely sensed data. Treatments were disproportionately applied in more stressful, degraded ecological conditions. Failure to incorporate nonrandom treatment allocation led to the conclusion that costly, widespread seedings were unsuccessful; however, after considering biases, restoration positively affected sagebrush recovery. Treatment effect sizes varied with climate, indicating possible prioritization criteria for interventions. Our findings revise the perspective that widespread post-fire sagebrush seedings have been broadly “unsuccessful” and demonstrate how selection biases can pose substantive inferential hazards in observational studies of restoration efficacy and development of restoration theory.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-022-31102-z","usgsCitation":"Simler-Williamson, A., and Germino, M., 2022, Statistical consideration of nonrandom treatment applications reveal region-wide benefits of widespread post-fire restoration action: Nature Communications, v. 13, 3472, 14 p., https://doi.org/10.1038/s41467-022-31102-z.","productDescription":"3472, 14 p.","ipdsId":"IP-130034","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-022-31102-z","text":"Publisher Index Page"},{"id":402510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Nevada, Oregon, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1240234375,\n 37.020098201368114\n ],\n [\n -105.64453124999999,\n 37.020098201368114\n ],\n [\n -105.64453124999999,\n 44.87144275016589\n ],\n [\n -122.1240234375,\n 44.87144275016589\n ],\n [\n -122.1240234375,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Simler-Williamson, Allison B. 0000-0003-1358-1919","orcid":"https://orcid.org/0000-0003-1358-1919","contributorId":292572,"corporation":false,"usgs":false,"family":"Simler-Williamson","given":"Allison B.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":845221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":845222,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232282,"text":"70232282 - 2022 - A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels","interactions":[],"lastModifiedDate":"2022-06-27T15:24:43.923098","indexId":"70232282","displayToPublicDate":"2022-06-27T10:16:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels","docAbstract":"Many populated, tropical coastlines fronted by fringing coral reefs are exposed to wave-driven marine flooding that is exacerbated by sea-level rise. Most fringing coral reef are not alongshore uniform, but bisected by shore-normal channels; however, little is known about the influence of such channels on alongshore variations on runup and flooding of the adjacent coastline. We con-ducted a parametric study using the numeric model XBeach that demonstrates that a shore-normal channel results in substantial alongshore variations in waves, wave-driven water levels, and the resulting runup. Depending on the geometry and forcing, runup is greater either on the coastline adjacent to the channel terminus or at locations near the alongshore extent of the channel. The impact of channels on runup increases for higher incident waves, lower incident wave steepness, wider channels, a narrower reef, and shorter channel spacing. Alongshore varia-tion of infragravity waves is predominantly responsible for large-scale variations in runup out-side the channel, whereas setup, sea-swell waves, and very-low frequency waves mainly increase runup inside the channel. These results provide insight into which coastal locations adjacent to shore-normal channels are most vulnerable to high runup events, using only widely available data such as reef geometry and offshore wave conditions.","language":"English","publisher":"MDPI","doi":"10.3390/jmse10060828","usgsCitation":"Storlazzi, C.D., Rey, A., and van Dongeren, A., 2022, A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels: Journal of Marine Science and Engineering, v. 10, no. 6, 828, 13 p., https://doi.org/10.3390/jmse10060828.","productDescription":"828, 13 p.","ipdsId":"IP-140197","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447301,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse10060828","text":"Publisher Index Page"},{"id":435793,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A0HFKV","text":"USGS data release","linkHelpText":"Model parameter input files to compare the influence of channels in fringing coral reefs on alongshore variations in wave-driven runup along the shoreline"},{"id":402509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8075-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8075-4490","contributorId":292540,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":845005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rey, Annouk","contributorId":292541,"corporation":false,"usgs":false,"family":"Rey","given":"Annouk","email":"","affiliations":[{"id":27619,"text":"TU Delft","active":true,"usgs":false}],"preferred":false,"id":845006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dongeren, Ap","contributorId":149002,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":845007,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232393,"text":"70232393 - 2022 - 21st-century stagnation in unvegetated sand-sea activity","interactions":[],"lastModifiedDate":"2022-07-01T12:05:08.833034","indexId":"70232393","displayToPublicDate":"2022-06-27T07:02:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"21st-century stagnation in unvegetated sand-sea activity","docAbstract":"Sand seas are vast expanses of Earth’s surface containing large areas of aeolian dunes—topographic patterns manifest from above-threshold winds and a supply of loose sand. Predictions of the role of future climate change for sand-sea activity are sparse and contradictory. Here we examine the impact of climate on all of Earth’s presently-unvegetated sand seas, using ensemble runs of an Earth System Model for historical and future Shared Socioeconomic Pathway (SSP) scenarios. We find that almost all of the sand seas decrease in activity relative to present-day and industrial-onset for all future SSP scenarios, largely due to more intermittent sand-transport events. An increase in event wait-times and decrease in sand transport is conducive to vegetation growth. We expect dune-forming winds will become more unimodal, and produce larger incipient wavelengths, due to weaker and more seasonal winds. Our results indicate that these qualitative changes in Earth’s deserts cannot be mitigated.
Restoring the health of urban streams has many of the characteristics of a wicked problem. Addressing a wicked problem requires managers, academics, practitioners, and community members to make negotiated tradeoffs and compromises to satisfy the values and perspectives of diverse stakeholders involved in setting restoration project goals and objectives. We conducted a gap analysis on 11 urban stream restoration projects to identify disconnections, underperformance issues, and missing processes in the project structures used to develop restoration project goals and objectives. We examined the gap analysis results to investigate whether managers appropriately identified problem statements and met stated objectives. Projects that aimed to restore overall stream health commonly fell short for various reasons, including limited stakeholder and community input and buy-in, revealing potential limitations in the breadth of objectives, values, and stakeholder perspectives and knowledge types. Projects that emphasized integrating community values and diverse knowledge types tended to meet the expected outcomes of restoring stream processes through incremental solutions. Managers implementing more holistic solutions and values-driven approaches are more likely to consider diverse viewpoints from a variety of community local institutions. Based on these and other results, we propose a conceptual framework that integrates diverse perspectives and knowledge to enhance social and ecological outcomes of urban stream restoration. The framework also emphasizes the importance of setting objectives that support incremental solutions to foster more realistic expectations amongst stakeholders.
In low-permeability systems, groundwater may be accompanied by separate-phase fluids, and measured pore water pressures may deviate from those expected in steady-state, single-phase systems. These same systems may be of interest for storage of nuclear waste in Deep Geologic Repositories. Therefore, it is important to understand the relationship between the presence of a separate phase and anomalous pressure development. At the Bruce site in Southern Ontario, a significant underpressure was observed, and there is evidence for the presence of gas-phase methane in situ. This study used a one-dimensional (vertical) numerical model of the subsurface down to a depth of 844 m beneath the Bruce site to evaluate possible effects of hydromechanical coupling with multiphase flow on pressure evolution during glacial loading and unloading. The simulated pressure conditions were affected strongly by the amount of methane initially present in the system, and the maximum simulated underpressure varied nonmonotonically with increasing initial methane content. When the initial methane content was below the solubility limit, exsolution led to underpressures that briefly exceeded those that formed in the single-phase case. At intermediate initial methane contents (sufficient to produce an immobile gas phase), the gas phase dampened the hydromechanical effects of the glacial cycle. At large initial methane contents (when a mobile gas phase was present), gas migration caused a large decrease in relative liquid permeability, which further contributed to underpressure development in the pore water. Multiple scenarios that spanned a range of initial methane contents yielded underpressures like those observed at the Bruce site.
One of the risks faced by habitat restoration practitioners is whether habitats included in restoration planning will be used by the target species or, conversely, whether habitats excluded from restoration planning would have benefited the target species. With the goal of providing a quantitative decision-making approach that represented varying levels of risk tolerance, we used multiple probability decision thresholds (PDT) to predict the range of occurrence for three anadromous fishes (Oncorhynchus spp.) in a watershed in southwestern Washington, USA. For each species, we compared the predicted range of occurrence to the distribution used for restoration planning and quantified the amount of habitat blocked by anthropogenic barriers. Coho salmon (O. kisutch) had the broadest predicted range of occurrence (3061.6–6357.9 km; 0.75–0.25 PDT), followed by steelhead trout (O. mykiss; 1828.8–2836.8 km) and chum salmon (O. keta; 1373.9–1629.1 km). For each species, the predicted range of occurrence was similar or greater than the distribution used for restoration planning, suggesting that the current plan may exclude habitats that would benefit each species. Coho salmon had the greatest percentage of habitat blocked by anthropogenic barriers, followed by steelhead trout and chum salmon, respectively. Modeling species distributions at multiple risk-tolerance scenarios acknowledges uncertainty in restoration planning and allows practitioners to weigh the ecological benefits and budgetary constraints when considering locations for restoration. To effectively communicate restoration science to support practitioners in decision-making, we developed an R Shiny application online user interface available at: https://shiny.wdfw-fish.us/ChehalisRiverBasinSalmonidRangeOfOccurence/.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2701","usgsCitation":"Walther, E.J., Zimmerman, M.S., Falke, J.A., and Westley, P.A., 2022, Species distributions and the recognition of risk in restoration planning: A case study of salmonid fishes: Ecological Applications, v. 32, no. 8, e2701, 19 p., https://doi.org/10.1002/eap.2701.","productDescription":"e2701, 19 p.","ipdsId":"IP-128611","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488400,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/6574277","text":"External Repository"},{"id":485841,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.31462582290652,\n 47.16367632863228\n ],\n [\n -124.14097393881218,\n 46.79579869451868\n ],\n [\n -123.88483362600141,\n 46.651693783856416\n ],\n [\n -123.23597795419923,\n 46.701853931300036\n ],\n [\n -123.28154994900483,\n 46.393856749600275\n ],\n [\n -123.12616728626703,\n 45.9636124965416\n ],\n [\n -122.6145461794788,\n 45.84907194087441\n ],\n [\n -122.25792770553518,\n 46.632856722316745\n ],\n [\n -123.85738372444928,\n 47.34970602480141\n ],\n [\n -124.31462582290652,\n 47.16367632863228\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Walther, Eric J.","contributorId":304288,"corporation":false,"usgs":false,"family":"Walther","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":936771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Mara S.","contributorId":152687,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Mara","email":"","middleInitial":"S.","affiliations":[{"id":13269,"text":"Washington Department of Fish & Wildlife","active":true,"usgs":false}],"preferred":false,"id":936772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westley, Peter A. H.","contributorId":190530,"corporation":false,"usgs":false,"family":"Westley","given":"Peter","email":"","middleInitial":"A. H.","affiliations":[],"preferred":false,"id":936774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255205,"text":"70255205 - 2022 - Hybridization decreases native cutthroat trout reproductive fitness","interactions":[],"lastModifiedDate":"2024-06-13T15:00:22.858853","indexId":"70255205","displayToPublicDate":"2022-06-25T09:56:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hybridization decreases native cutthroat trout reproductive fitness","docAbstract":"Examining natural selection in wild populations is challenging, but crucial to understanding many ecological and evolutionary processes. Additionally, in hybridizing populations, natural selection may be an important determinant of the eventual outcome of hybridization. We characterized several components of relative fitness in hybridizing populations of Yellowstone cutthroat trout and rainbow trout in an effort to better understand the prolonged persistence of both parental species despite predictions of extirpation. Thousands of genomic loci enabled precise quantification of hybrid status in adult and subsequent juvenile generations; a subset of those data also identified parent–offspring relationships. We used linear models and simulations to assess the effects of ancestry on reproductive output and mate choice decisions. We found a relatively low number of late-stage (F3+) hybrids and an excess of F2 juveniles relative to the adult generation in one location, which suggests the presence of hybrid breakdown decreasing the fitness of F2+ hybrids later in life. Assessments of reproductive output showed that Yellowstone cutthroat trout are more likely to successfully reproduce and produce slightly more offspring than their rainbow trout and hybrid counterparts. Mate choice appeared to be largely random, though we did find statistical support for slight female preference for males of similar ancestry. Together, these results show that native Yellowstone cutthroat trout are able to outperform rainbow trout in terms of reproduction and suggest that management action to exclude rainbow trout from spawning locations may bolster the now-rare Yellowstone cutthroat trout.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.16578","collaboration":"Wyoming Game and Fish Department","usgsCitation":"Rosenthal, W.C., Fennell, J.M., Mandeville, E., Burckhardt, J., Walters, A.W., and Wagner, C., 2022, Hybridization decreases native cutthroat trout reproductive fitness: Molecular Ecology, v. 31, no. 16, p. 4224-4241, https://doi.org/10.1111/mec.16578.","productDescription":"18 p.","startPage":"4224","endPage":"4241","ipdsId":"IP-134904","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenthal, William C.","contributorId":337368,"corporation":false,"usgs":false,"family":"Rosenthal","given":"William","email":"","middleInitial":"C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fennell, John M.","contributorId":337830,"corporation":false,"usgs":false,"family":"Fennell","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mandeville, Elizabeth G.","contributorId":270691,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth G.","affiliations":[{"id":56198,"text":"uwyo","active":true,"usgs":false}],"preferred":false,"id":903732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burckhardt, Jason C.","contributorId":338996,"corporation":false,"usgs":false,"family":"Burckhardt","given":"Jason C.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":903733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":903729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Catherine E.","contributorId":337377,"corporation":false,"usgs":false,"family":"Wagner","given":"Catherine E.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903734,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232345,"text":"70232345 - 2022 - Experimental reductions in sub-daily flow fluctuations increased gross primary productivity for 425 river kilometers downstream","interactions":[],"lastModifiedDate":"2023-03-24T16:52:14.658494","indexId":"70232345","displayToPublicDate":"2022-06-25T07:30:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10942,"text":"PNAS Nexus","active":true,"publicationSubtype":{"id":10}},"title":"Experimental reductions in sub-daily flow fluctuations increased gross primary productivity for 425 river kilometers downstream","docAbstract":"Aquatic primary production is the foundation of many river food webs. Dams change the physical template of rivers, often driving food webs toward greater reliance on aquatic primary production. Nonetheless, the effects of regulated flow regimes on primary production are poorly understood. Load following is a common dam flow management strategy that involves sub-daily changes in water releases proportional to fluctuations in electrical power demand. This flow regime causes an artificial tide, wetting and drying channel margins and altering river depth and water clarity, all processes that are likely to affect primary production. In collaboration with dam operators, we designed an experimental flow regime whose goal was to mitigate negative effects of load following on ecosystem processes. The experimental flow contrasted steady-low flows on weekends with load following flows on weekdays. Here, we quantify the effect of this experimental flow on springtime gross primary production (GPP) 90-to-425 km downstream of Glen Canyon Dam on the Colorado River, AZ, USA. GPP during steady-low flows was 41% higher than during load following flows, mostly owing to non-linear reductions in sediment-driven turbidity. The experimental flow increased weekly GPP even after controlling for variation in weekly mean discharge, demonstrating a negative effect of load following on GPP. We estimate that this environmental flow increased springtime carbon fixation by 0.27 g C m–2 d–1, which is ecologically meaningful considering median C fixation in 356 U.S. rivers of 0.44 g C m–2 d–1 and the fact that native fish populations in this river are food-limited.
","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1093/pnasnexus/pgac094","usgsCitation":"Deemer, B., Yackulic, C., Hall Jr., R., Dodrill, M., Kennedy, T., Muehlbauer, J., Topping, D.J., Voichick, N., and Yard, M.D., 2022, Experimental reductions in sub-daily flow fluctuations increased gross primary productivity for 425 river kilometers downstream: PNAS Nexus, v. 1, no. 3, pgsc094, 12 p., https://doi.org/10.1093/pnasnexus/pgac094.","productDescription":"pgsc094, 12 p.","ipdsId":"IP-134337","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447313,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/pnasnexus/pgac094","text":"Publisher Index Page"},{"id":435795,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZS6YLV","text":"USGS data release","linkHelpText":"Gross primary production estimates and associated light, sediment, and water quality data from the Colorado River below Glen Canyon Dam"},{"id":402590,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall Jr., Robert O","contributorId":292567,"corporation":false,"usgs":false,"family":"Hall Jr.","given":"Robert O","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":845293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845294,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845295,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muehlbauer, Jeffrey 0000-0003-1808-580X","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":221739,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845296,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845297,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Voichick, Nicholas 0000-0002-9716-5906 nvoichick@usgs.gov","orcid":"https://orcid.org/0000-0002-9716-5906","contributorId":203632,"corporation":false,"usgs":true,"family":"Voichick","given":"Nicholas","email":"nvoichick@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845298,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":169281,"corporation":false,"usgs":true,"family":"Yard","given":"Michael","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845299,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70233942,"text":"70233942 - 2022 - Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries","interactions":[],"lastModifiedDate":"2022-10-17T15:43:31.657314","indexId":"70233942","displayToPublicDate":"2022-06-25T07:13:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries","docAbstract":"Environmental DNA (eDNA) detection methods can complement traditional biomonitoring to yield new ecological insights in aquatic systems. However, the conceptual and methodological frameworks for aquatic eDNA detection and interpretation were developed primarily in freshwater environments and have not been well established for estuaries and marine environments that are by nature dynamic, turbid, and hydrologically complex. Environmental context and species life history are critical for successful application of eDNA methods, and the challenges associated with eDNA detection in estuaries were the subject of a symposium held at the University of California Davis on January 29, 2020 (https://marinescience.ucdavis.edu/engagement/past-events/edna). Here, we elaborate upon topics addressed in the symposium to evaluate eDNA methods in the context of monitoring and biodiversity studies in estuaries. We first provide a concise overview of eDNA science and methods, and then examine the San Francisco Estuary (SFE) as a case study to illustrate how eDNA detection can complement traditional monitoring programs and provide regional guidance on future potential eDNA applications. Additionally, we offer recommendations for enhancing communication between eDNA scientists and natural resource managers, which is essential for integrating eDNA methods into existing monitoring programs. Our intent is to create a resource that is accessible to those outside the field of eDNA, especially managers, without oversimplifying the challenges or advantages of these methods.
Understanding the evolution of plumes emanating from residual hydrocarbon contaminant sources requires evaluating how changes in source compositions over time cause changes in dissolved plume chemistry as residual sources age. This study investigates such changes at the site of a 1979 crude-oil pipeline spill and is the first comprehensive look at groundwater chemistry associated with a residual hydrocarbon source zones in different stages of aging. The data show a direct relationship between concentrations of benzene and naphthalene in the residual oil and those measured in water samples collected below the oil. Groundwater associated with oil near the spill site had different chemical composition compared with water associated with oil that had spread downgradient from the spill zone, indicating a shift in biodegradation reactions. These results emphasize that source zone processes are spatially and temporally heterogeneous and should be accounted for in natural attenuation studies where residual source zones persist.