The United States Department of Energy, the MH21-S Research Consortium of Japan, and the United States Geological Survey are collaborating to enable gas hydrate scientific drilling and extended-duration reservoir response testing on the Alaska North Slope. To feasibly execute such a test, a location is required that is accessible from existing roads and gravel pads and that can be occupied without disrupting ongoing industry operations. A review of potential locations meeting these criteria determined the likely occurrence of gas hydrate in two fine-grained marginal-marine sands of Tertiary age in the vicinity of the inactive “Kuparuk State 7-11-12” exploration pad in the western Prudhoe Bay Unit (PBU). Existing well and seismic data for that site were insufficient to preclude the potential for free gas occurrence within the deeper (and most prospective) target sand. Therefore, with support from the PBU Working Interest Owners, Alaska Department of Natural Resources, and Petrotechnical Resources Alaska, the Hydrate-01 Stratigraphic Test Well (STW) was drilled in December 2018 to confirm the suitability of the site for future gas hydrate scientific testing. The Hydrate-01 well was successfully drilled to −3290 ft (1003 m) subsea vertical depth at a bottom hole location of approximately 900 ft (∼275 m) east of the surface location. The drilling program featured acquisition of a full suite of logging while drilling data, the collection of side-wall pressure cores, and the installation of distributed temperature and distributed acoustic sensor fiber-optic cables. The log data acquired confirmed the occurrence of gas hydrate at high saturation in two target sands. Integrated evaluation of log and sidewall core data provide petrophysical and geomechanical property information that allow for potential reservoir response to depressurization to be simulated. The deeper “B1 sand” is deemed to be most favorable for reservoir response testing as a result of confirmed gas hydrate occurrence in sediments of high intrinsic permeability, location within 100 ft (30 m) of the base of gas hydrate stability, and minimal risk for direct communication with permeable water-bearing (hydrate-free) zones. The shallower “D1 sand” provides a secondary target that is differentiated by colder in situ temperatures and the interpreted direct hydraulic communication to a lower section of non-hydrate-bearing, water-saturated sand. The Hydrate-01 log data also confirm the occurrence of at least one sub-seismic fault in close proximity to the B1 sand reservoir. To better image the distribution of the gas-hydrate-bearing reservoir sections and associated faults, a three-dimensional (3D) vertical seismic profile was conducted in early 2019 using the distributed acoustic sensors installed as part of the Hydrate-01 STW completion. Detailed two-dimensional (2D) and 3D geologic models have been constructed to enable numerical simulations to inform the planning for potential future scientific tests of reservoir response to depressurization at the site.
Exotic species are often vilified as \"bad\" without consideration of the potential they have for contributing to ecological functions in degraded ecosystems. The red-eared slider turtle (RES) has been disparaged as one of the worst invasive species. Based on this review, we suggest that RES contribute some ecosystem functions in urban wetlands comparable to those provided by the native turtles they sometimes dominate or replace. While we do not advocate for releases outside their native range, or into natural environments, in this review, we examine the case for the RES to be considered potentially beneficial in heavily human-altered and degraded ecosystems where native turtles struggle or fail to persist. After reviewing the ecosystem functions RESs are known to provide, we conclude that in many modified environments the RES is a partial ecological analog to native turtles and removing them may obviate the ecological benefits they provide. We also suggest research avenues to better understand the role of RESs in heavily modified wetlands.
","language":"English","publisher":"Springer","doi":"10.1007/s43621-022-00083-w","usgsCitation":"Dupuis-Desormeaux, M., Lovich, J.E., and Gibbons, J.W., 2022, Re-evaluating invasive species in degraded ecosystems: A case study of red-eared slider turtles as partial ecological analogs: Discover Sustainability, v. 3, 15, 13 p., https://doi.org/10.1007/s43621-022-00083-w.","productDescription":"15, 13 p.","ipdsId":"IP-127491","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s43621-022-00083-w","text":"Publisher Index Page"},{"id":402540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Dupuis-Desormeaux, Marc","contributorId":292578,"corporation":false,"usgs":false,"family":"Dupuis-Desormeaux","given":"Marc","email":"","affiliations":[{"id":62941,"text":"Department of Biology, Glendon College, York University, 2275 Bayview Avenue, Toronto, Ontario, M4N 3M6 CANADA","active":true,"usgs":false}],"preferred":false,"id":845237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":845238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibbons, J. Whitfield","contributorId":198690,"corporation":false,"usgs":false,"family":"Gibbons","given":"J.","email":"","middleInitial":"Whitfield","affiliations":[],"preferred":false,"id":845239,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230882,"text":"cir1494 - 2022 - Yellowstone Volcano Observatory 2021 annual report","interactions":[],"lastModifiedDate":"2026-03-16T19:46:12.182854","indexId":"cir1494","displayToPublicDate":"2022-04-27T13:29:18","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1494","displayTitle":"Yellowstone Volcano Observatory 2021 Annual Report","title":"Yellowstone Volcano Observatory 2021 annual report","docAbstract":"The Yellowstone Volcano Observatory (YVO) monitors volcanic and hydrothermal activity associated with the Yellowstone magmatic system, carries out research into magmatic processes occurring beneath Yellowstone Caldera, and issues timely warnings and guidance related to potential future geologic hazards. This report summarizes the activities and findings of YVO during the year 2021, focusing on the Yellowstone volcanic system. Highlights of YVO research and related activities during 2021 include deployments of seismometers in Norris Geyser Basin and Upper Geyser Basin to investigate geyser plumbing systems, semipermanent Global Positioning System array deployment from May to October, geological studies of post-glacial hydrothermal activity, refining the ages of Yellowstone volcanic units and updating existing maps of geologic deposits, installation of a new continuous gas monitoring station near Mud Volcano, sampling of thermal waters around Yellowstone National Park to monitor water chemistry over space and time, and assessment of thermal output based on satellite imagery and chloride flux in rivers.
Steamboat Geyser, in Norris Geyser Basin, continued the pattern of frequent eruptions that began in 2018 with 20 water eruptions in 2021—a significant decrease from the 48 eruptions that occurred in both 2019 and 2020. Total seismicity—2,773 located earthquakes—was elevated compared to the 1,722 earthquakes located in 2020, but not significantly outside the historical average of about 1,500–2,500 earthquakes per year. Overall subsidence of the caldera floor, ongoing since late 2015 or early 2016, continued at rates of a few centimeters (1–2 inches) per year, whereas deformation in the Norris Geyser Basin area was below detection levels. Satellite deformation measurements indicate the possibility of slight uplift amounting to about 1 centimeter (less than 1 inch) along the north caldera rim, south of Norris Geyser Basin. The deformation is similar to that which occurred in the late 1990s. Throughout 2021, the aviation color code for Yellowstone Caldera remained at “green” and the volcano alert level remained at “normal.”
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1494","usgsCitation":"Yellowstone Volcano Observatory, 2022, Yellowstone Volcano Observatory 2021 annual report: U.S. Geological Survey Circular 1494, 48 p., https://doi.org/10.3133/cir1494.","productDescription":"v, 48 p.","ipdsId":"IP-137750","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":399786,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1494/coverthb.jpg"},{"id":399787,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1494/circ1494.pdf","text":"Report","size":"20.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1494"},{"id":501194,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112956.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.26953125,\n 43.13306116240612\n ],\n [\n -108.73168945312499,\n 43.13306116240612\n ],\n [\n -108.73168945312499,\n 45.10454630976873\n ],\n [\n -111.26953125,\n 45.10454630976873\n ],\n [\n -111.26953125,\n 43.13306116240612\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Yellowstone Volcano Observatory
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","tableOfContents":"The U.S. Geological Survey (USGS) Volcano Hazards Program (VHP) Strategic Science Plan, developed through discussion with scientists-in-charge of the USGS volcano observatories and the director of the USGS Volcano Science Center, specifies six major strategic goals to be pursued over the next 5 years. The purpose of these goals is to help fulfill the USGS VHP mission to enhance public safety and to minimize social and economic disruption caused by volcanic eruptions in the United States and its territories, through delivery of effective forecasts, warnings, and information on volcano hazards based on scientific understanding of volcanic processes. These six major strategic goals are to (1) continue—and when possible, accelerate—implementation of the National Volcano Early Warning System (NVEWS); (2) improve community preparedness for volcanic hazards by updating and standardizing essential components of volcano hazard assessments and providing training to land managers, emergency responders, and State and local communities; (3) develop the next generation of volcano hazard assessments using geographic information systems and other digital tools; (4) make observations with new instrumentation and take advantage of advances in real-time gas sensors; (5) rebuild the Hawaiian Volcano Observatory and its monitoring capabilities; and (6) form new partnerships and strengthen existing partnerships with other government agencies and with academia and industry, to advance volcano monitoring, increase understanding of volcanic processes, and disseminate USGS information.
In its effort to advance volcano science and monitoring techniques, the VHP has identified six scientific targets to pursue over the next 5 years, including: (1) increased understanding of volcano seismicity; (2) improved probabilistic forecasting; (3) deepened grasp of volcano eruption histories and geochronology; (4) newly developed and refined physical models of magmatic systems, leading to better situational awareness and accuracy of eruption forecasts; (5) improved warnings and forecasts of volcanic ash and gas clouds and characterization of volcanic smog sources; and (6) refined lava-flow modeling and forecasting of lava-flow paths.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1492","usgsCitation":"Mandeville, C.W., Cervelli, P.F., Avery, V.F., and Wilkins, A.M., 2022, The Volcano Hazards Program — Strategic Science Plan for 2022–2026: U.S. Geological Survey Circular 1492, 50 p., https://doi.org/10.3133/cir1492.","productDescription":"vi, 50 p.","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-122901","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":399598,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1492/coverthb.jpg"},{"id":399599,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1492/cir1492.pdf","text":"Report","size":"7.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1492"}],"country":"United 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This site is the location of continuous seafloor monitoring as part of the Ocean Networks Canada (ONC) cabled observatory off the west coast off Vancouver Island, British Columbia, Canada. We combine repeat remotely operated vehicle (ROV) seafloor video observations, mapping with an autonomous underwater vehicle (AUV), ship-, ROV-, and AUV-based identification of gas flares, as well as seismic and Chirp data to investigate the distribution of fluid migration pathways. Geologically, the site with the prominent gas hydrate mounds and associated fluid seepage is covering an area of ∼0.15 km2 and is situated on a remnant of a rotated fault block that had slipped off the steep flanks of the north-east facing canyon wall. The gas hydrate mounds, nearly constant in dimension over the entire observation period, are associated with gas and oil seepage and surrounded by debris of chemosynthetic communities and authigenic carbonate. The formation of gas hydrate at and near the seafloor requires additional accommodation space created by forming blisters at the seafloor that displace the regular sediments. An additional zone located centrally on the rotated fault block with more diffuse seepage (∼0.02 km2 in extent) has been identified with no visible mounds, but with bacterial mats, small carbonate concretions, and clam beds. Gas venting is seen acoustically in the water column up to a depth of ∼300 m. However, acoustic water-column imaging during coring and ROV dives showed rising gas bubbles to much shallower depth, even <50 m, likely a result of degassing of rising oil droplets, which themselves cannot be seen acoustically. Combining all observations, the location of the gas hydrate mounds is controlled by a combination of fault-focused fluid migration from a deeper reservoir and fluid seepage along more permeable strata within the rotated slope block. Fluids must be provided continuously to allow the sustained presence of the gas hydrate mounds at the seafloor.
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Macroinvertebrate investigations in research and monitoring require consistent and reliable field and laboratory procedures. Comprehensive standard operating procedures for sampling macroinvertebrates from depressional wetlands, which can range from riverine floodplain lakes to wetlands of any size and hydrologic regime, remain relatively sparse. This report provides step-by-step protocols for efficient use of time and resources while collecting and processing aquatic macroinvertebrate samples; for example, a single wetland can typically be field surveyed in less than 1 hour, and the samples can be processed in the laboratory in less than 2 hours. Samples can be collected from inside a motorboat or canoe or while wading. This procedures manual describes dip netting to collect macroinvertebrates from the wetland bottom and water column separately to facilitate investigations of habitat use by species occupying different areas of the wetland. This report also provides descriptive supplemental materials and data sheets to assist with the preparation of survey maps, the acquisition of field and laboratory equipment, and the calculation of macroinvertebrate densities from the wetland bottom and water column. These procedures can be applied to most macroinvertebrate species and communities that inhabit a variety of wetland sizes and types. Uses and applications can range from elementary and secondary environmental education to rigorous scientific evaluations of community abundance, diversity, distribution, or species-habitat relations.
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U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Utah’s list of notable features runs long, but scenery rises to the top. The Colorado River does not simply run through southeastern Utah; it meanders through steep canyons of the eroded sedimentary rock that colors the sweeping vistas of the Colorado Plateau. Stone arches, spires, hoodoos, cliffs, and bridges in hues of red enchant residents and tourists. Mountain ranges extending through the State add dynamic views—and skiing opportunities.
The Great Salt Lake in northern Utah is the largest saltwater lake in the Western Hemisphere. The western part of Utah, including the Great Salt Lake, lies in the Great Basin, a multi-State drainage area with no outlet. Because the lake has no outlet to flush out any salt, evaporation produces a higher concentration of salts in the water or soils, called salinity. The lake lacks fish but supports algae and brine shrimp, and extensive wetlands around the lake attract millions of migratory birds.
Landsat imagery is useful for showing surface changes, such as the fluctuating water levels of the shallow Great Salt Lake. The lake flooded in the 1980s, but the southern part dropped to its lowest level in recorded history in 2021. Landsat data also can take a much deeper look at land and water conditions. Here are several ways Landsat benefits Utah.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The Big River is a tributary to the Meramec River in south-central Missouri. It drains an area that has been historically one of the largest lead producers in the world, and associated mine wastes have contaminated sediments in much of the river corridor. This study investigated hydraulic conditions in four study reaches to evaluate the potential contribution of physical habitat dynamics to mechanical and physiological stress on native mussel populations. We quantified hydraulic conditions and relative bed stability in previously identified and delineated mussel habitats (MHs) and in the surrounding reaches to refine understanding of the reach-scale (about 1 kilometer) hydraulic characteristics that affect the distribution of mussel aggregations in the river. Two-dimensional hydrodynamic models were compiled for discharge scenarios from base flow (90-percent flow exceedance) to the approximate bankfull discharge (2-year mean return interval peak flow) for the reaches. Discharge, velocity, and water-surface elevation data were collected at all four study reaches at various discharges to calibrate the models across a range of discharges. Shields values to predict incipient motion of the substrate were computed for the MHs and surrounding reaches using bed-surface sediment data collected during this study and previous studies.
The distributions of hydraulic values at the range of simulated discharge scenarios were significantly different among the MHs. Depth values in the MHs ranged from 0.03 to 5.7 meters, with parts remaining dry at some lower flow scenarios (for example, 90- and 50-percent flow exceedance). MH velocities and bed shear stresses (shear stresses) reached 3.1 meters per second and 31 newtons per square meter, respectively. Through the range of simulated discharges, velocity and shear stress within the MHs were limited by reach-scale hydraulic behavior.
Our calculations predicted sand mobility within at least 50 percent of the wetted area of all four MHs for discharges from the 50-percent exceedance flow to the approximate bankfull discharge, whereas 50th-percentile (median) particle size fraction mobility was only predicted within a small area of one of the MHs at the 2-year peak discharge. These results indicate that finer size fractions are mobile within the four MHs, but the larger framework grains of the substrate are predominantly stable at the most frequent discharges.
Our results indicate that suitable mussel habitat on the Big River cannot be identified within a narrow range of velocities, depths, and shear stresses. However, the consistent patterns of sediment mobility and the slow increase of hydraulic forces with increasing discharge within all the MHs indicate that flushing flows at low discharges and coarse sediment stability at higher discharges are important for habitat suitability in the Big River. These patterns of sediment mobility are comparable among the robust and depauperate MHs, indicating that the depauperate beds are likely not impaired by bed instability or siltation. Coarse sediment stability up to bankfull discharges further indicates that bed instability is not widespread in these modeled reaches and is likely not related to the spatial distribution of mussels in these locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225002","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Roberts, M.O., Jacobson, R.B., and Erwin, S.O., 2022, Hydraulics of freshwater mussel habitat in select reaches of the Big River, Missouri: U.S. Geological Survey Scientific Investigations Report 2022–5002, 49 p., https://doi.org/10.3133/sir20225002.","productDescription":"Report: viii, 49 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-122009","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":399191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5002/coverthb.jpg"},{"id":399688,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5002"},{"id":399192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5002/sir20225002.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5002"},{"id":399193,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5002/sir20225002.XML"},{"id":399194,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5002/images"},{"id":399195,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K3ENAX","text":"USGS data release","linkHelpText":"Hydraulic measurements from select reaches of the Big River, Missouri"},{"id":399196,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":502289,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112957.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25244140624999,\n 37.63163475580645\n ],\n [\n -90.32958984375,\n 37.63163475580645\n ],\n [\n -90.32958984375,\n 38.53097889440026\n ],\n [\n -91.25244140624999,\n 38.53097889440026\n ],\n [\n -91.25244140624999,\n 37.63163475580645\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
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The North Brawley Geothermal Field, located within the Brawley Seismic Zone of Southern California, presents a case study for understanding seismic hazards linked to fluid injection and geothermal energy extraction. An earthquake swarm near the geothermal field in 2012 included two earthquakes with magnitudes greater than 5 and was potentially preceded by a years-long aseismic slip transient. To better understand ground deformation around the geothermal field, including its evolution with time and its physical mechanisms, we analyze deformation before, during, and after the swarm using ground- and satellite-based geodetic techniques between 2009 and 2019. We integrate observations from GNSS, Sentinel-1, TerraSAR-X, UAVSAR, and leveling surveys into a single deformation history. Modeling of this new collection of observations at the North Brawley Geothermal Field provides evidence for 80% more pre-swarm aseismic slip than previously recognized from 2009 to 2012. During the 2012 Brawley swarm, our geodetic slip inversions closely match the results of seismic waveform inversions from the swarm events. After the 2012 swarm, surface deformation is dominated by poroelastic deformation of a shallow fluid reservoir at <1 km depth rather than fault slip. The deformation history and seismicity catalogs at North Brawley suggest a cessation of fault-related slip during the ∼7 years after the 2012 earthquake swarm.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB023335","usgsCitation":"Materna, K.Z., Barbour, A.J., Jiang, J., and Eneva, M., 2022, Detection of aseismic slip and poroelastic reservoir deformation at the North Brawley Geothermal Field from 2009 to 2019: Journal of Geophysical Research Solid Earth, v. 127, no. 5, e2021JB023335, 19 p., https://doi.org/10.1029/2021JB023335.","productDescription":"e2021JB023335, 19 p.","ipdsId":"IP-125755","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":406832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"North Brawley Geothermal Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.875,\n 32.875\n ],\n [\n -115.25,\n 32.875\n ],\n [\n -115.25,\n 33.25\n ],\n [\n -115.875,\n 33.25\n ],\n [\n -115.875,\n 32.875\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Materna, Kathryn Zerbe 0000-0002-6687-980X","orcid":"https://orcid.org/0000-0002-6687-980X","contributorId":261337,"corporation":false,"usgs":true,"family":"Materna","given":"Kathryn","email":"","middleInitial":"Zerbe","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":851918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":851919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jiang, Junle","contributorId":206383,"corporation":false,"usgs":false,"family":"Jiang","given":"Junle","email":"","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":851920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eneva, Mariana","contributorId":167022,"corporation":false,"usgs":false,"family":"Eneva","given":"Mariana","email":"","affiliations":[{"id":24596,"text":"Imageair Inc.","active":true,"usgs":false}],"preferred":false,"id":851921,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230855,"text":"70230855 - 2022 - Susceptibility of beavers to chronic wasting disease","interactions":[],"lastModifiedDate":"2022-04-27T11:45:45.443783","indexId":"70230855","displayToPublicDate":"2022-04-26T06:43:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1026,"text":"Biology","active":true,"publicationSubtype":{"id":10}},"title":"Susceptibility of beavers to chronic wasting disease","docAbstract":"Coastal tidal wetlands are highly altered ecosystems exposed to substantial risk due to widespread and frequent land-use change coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes, is important for coastal communities and natural resource management. Large-scale mapping of coastal tidal wetland changes is extremely difficult due to their inherent dynamic nature. To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. DECODE consists of three elements, including spectral break detection, land cover classification and change characterization. DECODE assembles all available Landsat observations and introduces a water level regressor for each pixel to flag the spectral breaks and estimate harmonic time-series models for the divided temporal segments. Each temporal segment is classified (e.g., vegetated wetlands, open water, and others – including unvegetated areas and uplands) based on the phenological characteristics and the synthetic surface reflectance values calculated from the harmonic model coefficients, as well as a generic rule-based classification system. This harmonic model-based approach has the advantage of not needing the acquisition of satellite images at optimal conditions (i.e., low tide status) to avoid underestimating coastal vegetation caused by the tidal fluctuation. At the same time, DECODE can also characterize different kinds of changes including land cover change and condition change (i.e., land cover modification without conversion). We used DECODE to track status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximately 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with user's accuracy of 94.6% and 99.0%, and producer's accuracy of 98.1% and 93.5%, respectively. The cover change and condition change were mapped with user's accuracy of 68.0% and 80.0%, and producer's accuracy of 80.5% and 97.1%, respectively. Approximately 3283 km2 of the coastal landscape within our study area in the northeastern United States changed at least once (12% of the study area), and condition changes were the dominant change type (84.3%). Vegetated coastal tidal wetland decreased consistently (~2.6 km2 per year) in the past 35 years, largely due to conversion to open water in the context of sea-level rise.
The Okaloosa darter (Etheostoma okaloosae) is a diminutive, perch-like, benthic fish that inhabits only six small, clear, and shallow creek systems that flow almost entirely within Eglin Air Force Base in the panhandle of northwest Florida. Listed as Endangered by the U.S. Fish and Wildlife Service (USFWS) in 1973, improvements in erosion control and habitat restoration led to the Okaloosa darter being downlisted from Endangered to Threatened in 2011. However, the long-term management of the species is hampered by the lack of knowledge of the spatial extent of the recharge areas that ultimately support creek flow through groundwater discharge. To address this lack of data, we collected groundwater samples from the sand and gravel aquifer beneath 11 headwater and 11 downgradient sites across six creek basins during February and December 2020. The groundwater samples were collected from 1 to 1.2 m beneath the creek bottom. Concentrations of sulfur hexafluoride (SF6) were analyzed and used to calculate groundwater age (residence time), and indicated that at the 11 headwater sites, recharge occurred between 11 and 28 years ago. Groundwater ages in downgradient parts of the same creeks indicated that recharge occurred between 5 and 25 years ago. When combined with representative values of hydraulic conductivity for the sand and gravel aquifer, the ages reveal that the extent of the maximum recharge distance from the sampling sites ranged from about 222 to 2011 m from the creeks. This new information can be used by natural resource managers as additional evidence to support the USFWS Recovery Plan and proposed delisting of the Okaloosa darter from the Endangered Species List. Moreover, these results may also be useful to fisheries biologists to incorporate groundwater inputs to facilitate fisheries management.
","language":"English","publisher":"MDPI","doi":"10.3390/hydrology9050069","usgsCitation":"Landmeyer, J.E., McBride, W.S., and Tate, W., 2022, Determination of recharge areas that supply decades old groundwater to creeks inhabited by the threatened Okaloosa darter: Hydrology, v. 9, no. 5, 69, 24 p., https://doi.org/10.3390/hydrology9050069.","productDescription":"69, 24 p.","ipdsId":"IP-137426","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":448016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology9050069","text":"Publisher Index Page"},{"id":401642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Elgin Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.59561157226562,\n 30.484183951487754\n ],\n [\n -86.23443603515625,\n 30.484183951487754\n ],\n [\n -86.23443603515625,\n 30.681620845933267\n ],\n [\n -86.59561157226562,\n 30.681620845933267\n ],\n [\n -86.59561157226562,\n 30.484183951487754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Landmeyer, James E. 0000-0002-5640-3816","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":216137,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBride, W. Scott 0000-0003-1828-2838","orcid":"https://orcid.org/0000-0003-1828-2838","contributorId":201573,"corporation":false,"usgs":true,"family":"McBride","given":"W.","email":"","middleInitial":"Scott","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":844083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, William B.","contributorId":55538,"corporation":false,"usgs":true,"family":"Tate","given":"William B.","affiliations":[],"preferred":false,"id":844084,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230801,"text":"70230801 - 2022 - Rock-to-metal ratio: A foundational metric for understanding mine wastes","interactions":[],"lastModifiedDate":"2022-06-01T15:22:04.367002","indexId":"70230801","displayToPublicDate":"2022-04-25T09:50:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Rock-to-metal ratio: A foundational metric for understanding mine wastes","docAbstract":"The quantity of ore mined and waste rock (i.e., overburden or barren rock) removed to produce a refined unit of a mineral commodity, its rock-to-metal ratio (RMR), is an important metric for understanding mine wastes and environmental burdens. In this analysis, we provide a comprehensive examination of RMRs for 25 commodities for 2018. The results indicate significant variability across commodities. Precious metals like gold have RMRs in the range of 105–106, while iron ore and aluminum are on the order of 101. The results also indicate significant variability across operations for a single commodity. The interquartile range of RMRs for individual cobalt operations, for example, varies from 465 to 2157, with a global RMR of 859. RMR variability is mainly driven by ore grades and revenue contribution. The total attributable ore mined and waste rock removed in the production of these 25 commodities sums to 37.6 billion metric tons, 83% of which is attributable to iron ore, copper, and gold. RMRs provide an additional dimension for evaluating the impact of materials and material choice trade-offs. The results can enhance life cycle inventories and be extended to evaluate areas of surface disturbances, mine tailings, energy requirements, and associated greenhouse gas emissions.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.1c07875","usgsCitation":"Nassar, N.T., Lederer, G.W., Brainard, J.L., Padilla, A.J., and Lessard, J.D., 2022, Rock-to-metal ratio: A foundational metric for understanding mine wastes: Environmental Science & Technology, v. 56, no. 10, p. 6710-6721, https://doi.org/10.1021/acs.est.1c07875.","productDescription":"12 p.","startPage":"6710","endPage":"6721","ipdsId":"IP-133695","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":448020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.1c07875","text":"Publisher Index Page"},{"id":399668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":841376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":841377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brainard, Jamie L. 0000-0002-1712-0821","orcid":"https://orcid.org/0000-0002-1712-0821","contributorId":201465,"corporation":false,"usgs":true,"family":"Brainard","given":"Jamie","middleInitial":"L.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":841378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Padilla, Abraham J. 0000-0002-8371-533X","orcid":"https://orcid.org/0000-0002-8371-533X","contributorId":290608,"corporation":false,"usgs":true,"family":"Padilla","given":"Abraham","email":"","middleInitial":"J.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":841379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lessard, Joseph D.","contributorId":290609,"corporation":false,"usgs":false,"family":"Lessard","given":"Joseph","email":"","middleInitial":"D.","affiliations":[{"id":62455,"text":"Apple Inc","active":true,"usgs":false}],"preferred":false,"id":841380,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230832,"text":"70230832 - 2022 - Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology","interactions":[],"lastModifiedDate":"2022-04-26T14:13:49.664763","indexId":"70230832","displayToPublicDate":"2022-04-25T09:08:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology","docAbstract":"National and global greenhouse gas (GHG) budgets are continually being refined as data become available. Primary sources of the potent GHG nitrous oxide (N2O) include agricultural soil management and burning of fossil fuels, but comprehensive N2O budgets also incorporate less prominent factors such as wetlands. Freshwater wetland GHG flux estimates, however, have high uncertainty, and wetlands have been identified as both sources and sinks. Here, we analyzed a regional database of >26,000 N2O chamber flux measurements sampled across >150 wetlands from the Prairie Pothole Region (PPR) in the Great Plains of North America. Our goal was to identify important land use and hydrologic drivers of N2O flux to help reduce uncertainty in N2O models, and to incorporate these drivers into an upscaled estimate of wetland N2O emissions from the U.S. portion of the PPR. Within individual wetlands, exposed soils with no standing water, such as along wetland edges, were hotspots that accounted for greater than 90% of wetland N2O emissions. In contrast wet (i.e., ponded) areas had minimal or negative N2O flux. N2O flux from wetlands nested within croplands (16.3–17.3 μg N2O m−2 hr−1) was, in some instances, nearly double that from wetlands within grasslands (9.2–14.4 μg N2O m−2 h−1). We estimated that seasonal N2O flux from PPR wetlands equated to roughly 0.2% (1.04 Tg CO2 equivalents) of the U.S. N2O budget (c. 2019). Overall, even though PPR wetlands are a small net source of N2O to the atmosphere, their emissions are negligible relative to agricultural soil management. Policy and management to restore wetland hydrology and surrounding uplands from cropland to grasslands can reduce landscape N2O fluxes. Future activities focused on wetland N2O flux would benefit from inclusion of adjacent land use and hydrologic factors, as well as from incorporation of temporally dynamic ponded wetland areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2022.108968","usgsCitation":"Tangen, B., and Bansal, S., 2022, Prairie wetlands as sources or sinks of nitrous oxide: Effects of land use and hydrology: Agricultural and Forest Meteorology, v. 320, 108968, 10 p., https://doi.org/10.1016/j.agrformet.2022.108968.","productDescription":"108968, 10 p.","ipdsId":"IP-134939","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":399665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, Montana, North Dakota, South Dakota","otherGeospatial":"Prairie Potholes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.9296875,\n 48.86471476180277\n ],\n [\n -101.162109375,\n 47.57652571374621\n ],\n [\n -100.283203125,\n 45.706179285330855\n ],\n [\n -100.72265625,\n 44.653024159812\n ],\n [\n -99.755859375,\n 43.83452678223682\n ],\n [\n -97.119140625,\n 43.068887774169625\n ],\n [\n -96.767578125,\n 43.96119063892024\n ],\n [\n -95.625,\n 43.32517767999296\n ],\n [\n -94.306640625,\n 41.77131167976407\n ],\n [\n -92.724609375,\n 42.293564192170095\n ],\n [\n -93.07617187499999,\n 44.213709909702054\n ],\n [\n -97.20703125,\n 48.22467264956519\n ],\n [\n -98.7890625,\n 48.980216985374994\n ],\n [\n -107.9296875,\n 48.86471476180277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"320","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":841430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":841431,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236256,"text":"70236256 - 2022 - Assessing placement bias of the global river gauge network","interactions":[],"lastModifiedDate":"2022-08-31T13:33:17.808542","indexId":"70236256","displayToPublicDate":"2022-04-25T08:20:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5791,"text":"Nature Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Assessing placement bias of the global river gauge network","docAbstract":"Knowing where and when rivers flow is paramount to managing freshwater ecosystems. Yet stream gauging stations are distributed sparsely across rivers globally and may not capture the diversity of fluvial network properties and anthropogenic influences. Here we evaluate the placement bias of a global stream gauge dataset on its representation of socioecological, hydrologic, climatic and physiographic diversity of rivers. We find that gauges are located disproportionally in large, perennial rivers draining more human-occupied watersheds. Gauges are sparsely distributed in protected areas and rivers characterized by non-perennial flow regimes, both of which are critical to freshwater conservation and water security concerns. Disparities between the geography of the global gauging network and the broad diversity of streams and rivers weakens our ability to understand critical hydrologic processes and make informed water-management and policy decisions. Our findings underscore the need to address current gauge placement biases by investing in and prioritizing the installation of new gauging stations, embracing alternative water-monitoring strategies, advancing innovation in hydrologic modelling, and increasing accessibility of local and regional gauging data to support human responses to water challenges, both today and in the future.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41893-022-00873-0","usgsCitation":"Krabbenhoft, C., Allen, G.H., Lin, P., Godsey, S., Allen, D., Burrows, R., DelVecchia, A., Fritz, K.M., Shanafield, M., Burgin, A.J., Zimmer, M., Datry, T., Dodds, W., Jones, C., Mimms, M., Franklin, C., Hammond, J., Zipper, S., Ward, A.S., Costigan, K., Beck, H., and Olden, J., 2022, Assessing placement bias of the global river gauge network: Nature Sustainability, v. 5, p. 586-592, https://doi.org/10.1038/s41893-022-00873-0.","productDescription":"7 p.","startPage":"586","endPage":"592","ipdsId":"IP-130183","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":448023,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/s41893-022-00873-0","text":"External Repository"},{"id":405992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Krabbenhoft, Corey 0000-0002-2630-8287","orcid":"https://orcid.org/0000-0002-2630-8287","contributorId":225163,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Corey","email":"","affiliations":[{"id":41059,"text":"College of Arts and Sciences and Research and Education in Energy, Environment and Water (RENEW) Institute, University at Buffalo, Buffalo, NY 14228","active":true,"usgs":false}],"preferred":false,"id":850339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, George H. 0000-0001-8301-5301","orcid":"https://orcid.org/0000-0001-8301-5301","contributorId":225161,"corporation":false,"usgs":false,"family":"Allen","given":"George","middleInitial":"H.","affiliations":[{"id":41057,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843","active":true,"usgs":false}],"preferred":false,"id":850340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lin, Peirong","contributorId":295975,"corporation":false,"usgs":false,"family":"Lin","given":"Peirong","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":850342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godsey, Sarah E","contributorId":223120,"corporation":false,"usgs":false,"family":"Godsey","given":"Sarah E","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":850343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Daniel C. 0000-0002-0451-0564","orcid":"https://orcid.org/0000-0002-0451-0564","contributorId":225169,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","middleInitial":"C.","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":850351,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burrows, Ryan","contributorId":295995,"corporation":false,"usgs":false,"family":"Burrows","given":"Ryan","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":850357,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DelVecchia, Amanda 0000-0003-4252-5991","orcid":"https://orcid.org/0000-0003-4252-5991","contributorId":225165,"corporation":false,"usgs":false,"family":"DelVecchia","given":"Amanda","email":"","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":850361,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":850345,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shanafield, Margaret","contributorId":106772,"corporation":false,"usgs":true,"family":"Shanafield","given":"Margaret","affiliations":[],"preferred":false,"id":850344,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burgin, Amy J. 0000-0001-8489-4002","orcid":"https://orcid.org/0000-0001-8489-4002","contributorId":296009,"corporation":false,"usgs":false,"family":"Burgin","given":"Amy","email":"","middleInitial":"J.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":850356,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zimmer, Margaret","contributorId":295996,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":850358,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Datry, Thibault 0000-0003-1390-6736","orcid":"https://orcid.org/0000-0003-1390-6736","contributorId":225166,"corporation":false,"usgs":false,"family":"Datry","given":"Thibault","email":"","affiliations":[{"id":41062,"text":"Centre de Lyon-Villeurbanne, 69626 Villeurbanne CEDEX, France","active":true,"usgs":false}],"preferred":false,"id":850354,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dodds, Walter K.","contributorId":19419,"corporation":false,"usgs":true,"family":"Dodds","given":"Walter K.","affiliations":[],"preferred":false,"id":850347,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Jones, C. Nathan","contributorId":295982,"corporation":false,"usgs":false,"family":"Jones","given":"C. Nathan","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":850346,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mimms, Meryl","contributorId":295998,"corporation":false,"usgs":false,"family":"Mimms","given":"Meryl","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":850360,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Franklin, Catherin","contributorId":295985,"corporation":false,"usgs":false,"family":"Franklin","given":"Catherin","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":850348,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":850353,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":850350,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ward, Adam S","contributorId":191363,"corporation":false,"usgs":false,"family":"Ward","given":"Adam","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":850352,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Costigan, Katie H.","contributorId":166700,"corporation":false,"usgs":false,"family":"Costigan","given":"Katie H.","affiliations":[],"preferred":false,"id":850359,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Beck, Hylke","contributorId":295993,"corporation":false,"usgs":false,"family":"Beck","given":"Hylke","affiliations":[{"id":37958,"text":"University of Amsterdam","active":true,"usgs":false}],"preferred":false,"id":850355,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":850341,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70230940,"text":"70230940 - 2022 - Plant community context controls short- vs. medium-term effects of pre-emergent herbicides on target and non-target species after fire","interactions":[],"lastModifiedDate":"2022-06-01T15:26:15.677087","indexId":"70230940","displayToPublicDate":"2022-04-25T07:19:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Plant community context controls short- vs. medium-term effects of pre-emergent herbicides on target and non-target species after fire","docAbstract":"Questions: Selective herbicide application is a common restoration strategy to control exotic invaders that interfere with native plant recovery after wildfire. Whether spraying with preemergent or bioherbicides releases native plants from competition with exotics (“spray-and-release” strategy) and can make communities resistant to re-invasion by exotic annual grasses (e.g., cheatgrass, medusahead), without risks to non-target native plants or secondary invasion, is a major question for land managers of semiarid plant communities.
Location: Sagebrush steppe of southwest Idaho, USA
We applied chemical herbicides (imazapic, rimsulfuron) and weed-suppressive bacteria (Pseudomonas fluorescens strains MB906 and D7) to three sagebrush-steppe communities after fire.We measured plant cover prior to burning and for four years (five for exotic annual grasses) post-treatment.
Both chemical herbicides significantly reduced exotic annual grass cover in all communities in the first post-spraying year, but rimsulfuron plots were re-invaded after 1-2 years, while imazapic plots continued to resist re-invasion 4 and even 5 years post-spraying, well after the herbicide should have degraded. We did not detect any increase in native perennial grass cover with either herbicide, and herbicides had both positive and negative effects on individual bunchgrass basal diameter, depending on species and plant community. Rimsulfuron was more damaging than imazapic to shallow-rooted perennial bunchgrasses. Moss and lichen cover, key components of soil integrity, increased with chemical herbicide treatments in some communities. Both herbicides increased secondary invaders (exotic forbs or grasses), which varied by plant community and herbicide. Weed-suppressive bacteria treatments had no significant effects on cover of any functional group.
While short-term effects of chemical herbicides that target exotic annual grasses were relatively consistent and predictable, longer-term effects were specific to the herbicide and plant community. The “spray and release” strategy may confer resistance to re-invasion by exotic annual grasses if herbicides prevent re-invasion for an extended period.
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Washington’s diverse landscapes also change in various ways over time. Some are relatively steady, like urban expansion in the populous Puget Sound region. Others can be sudden, like the Mount Saint Helens eruption in 1980—one of the largest volcanic eruptions that caused the largest landslide in U.S. history. Although landscape change may be hard to detect at any one time, the Landsat program provides an objective view of it over decades. Landsat not only allows one to see what Mount Saint Helens looked like before and after the eruption, but also how the area has evolved since.
Here are a few examples of how Landsat benefits Washington.
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\"}}]}","edition":"Version 1.0: April 25, 2022; Version 1.1: January 24, 2023","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
In the context of increasing evidence of plate interface coupling variability in subduction zones, there is a need to extend the short time window given by instrumental data and to gather data over multiple time and spatial scales. We hence investigated the long-term topography on Barbuda island, located in the northern part of the Lesser Antilles, west of the Caribbean subduction zone. Following pioneering work using a set of marine terraces on the eastern side of the island, we performed the first U-Th dating on 10 corals in growth position from the lowest terrace, for which the highest relative sea-level (RSL) indicator is found at 9 ± 1 m above the mean sea level. We find that this terrace corresponds to the Last Interglacial (LIG) (ages between 122.8 ± 0.3 ka and 128.1 ± 0.3 ka) and we estimate a paleo RSL of 7 ± 2 m above the current mean sea level. The present elevation of the LIG shoreline on Barbuda might imply tectonics as an additional mechanism to eustatic sea level, mantle dynamic topography and glacial isostatic adjustment. East-west morphological asymmetry of Barbuda and difference in LIG shoreline elevation between Barbuda and Antigua suggest a regional tectonic process. As with the proposed westward tilting from the forearc to the volcanic arc of the Guadeloupe archipelago, vertical deformation on Barbuda could be related to plate-scale subduction processes. Long-term uplift of Barbuda might be related to the accumulation of residual coseismic deformation not fully recovered by interseismic subsidence and the corresponding seismogenic segment would extend below the Moho.
Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics.
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However, accurately sampling drift across a wide range of invertebrate sizes is difficult because small invertebrates slip through coarse-mesh drift nets, and fine mesh clogs more easily, which reduces filtration efficiency and measurement accuracy. To avoid this limiting tradeoff, we developed a gas-powered drift pump which pours 20 m3/hour of river water through nested 80- and 750-m nets suspended in the air, and we tested it against a conventional 250-m drift net during low and high flows in a clearwater Alaskan river. The drift pump detected a geometric mean drift concentration of 467 invertebrates m-3 and maximum of 5637 m-3, eleven times the mean concentration of 42 m-3 from the drift net. Invertebrates 3 mm length, primarily chironomids, comprised the entire difference. Studies in which the drift of 0.5 – 3 mm invertebrates might be relevant, such as foraging models investigating the growth of juvenile drift-feeding fishes, should consider using similar methods to quantify small invertebrate drift, lest they underestimate it by an order of magnitude.","language":"English","publisher":"Springer","doi":"10.1007/s10750-022-04849-1","usgsCitation":"Neuswanger, J., Schoen, E.R., Wipfli, M.S., Volk, C.J., and Savereide, J.W., 2022, A suction pump sampler for invertebrate drift detects exceptionally high concentrations of small invertebrates that drift nets miss: Hydrobiologia, v. 849, p. 2077-2089, https://doi.org/10.1007/s10750-022-04849-1.","productDescription":"13 p.","startPage":"2077","endPage":"2089","ipdsId":"IP-132981","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Neuswanger, Jason R.","contributorId":337745,"corporation":false,"usgs":false,"family":"Neuswanger","given":"Jason R.","affiliations":[{"id":81040,"text":"South Fork Research, Inc","active":true,"usgs":false}],"preferred":false,"id":902649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoen, Erik R.","contributorId":184107,"corporation":false,"usgs":false,"family":"Schoen","given":"Erik","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":902650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Volk, Carol J.","contributorId":337746,"corporation":false,"usgs":false,"family":"Volk","given":"Carol","email":"","middleInitial":"J.","affiliations":[{"id":81040,"text":"South Fork Research, Inc","active":true,"usgs":false}],"preferred":false,"id":902651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":902652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232543,"text":"70232543 - 2022 - A framework to integrate innovations in invasion science for proactive management","interactions":[],"lastModifiedDate":"2022-07-06T18:10:52.919742","indexId":"70232543","displayToPublicDate":"2022-04-22T14:10:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A framework to integrate innovations in invasion science for proactive management","docAbstract":"Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.
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Station, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":845914,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wilcox, Taylor","contributorId":152363,"corporation":false,"usgs":false,"family":"Wilcox","given":"Taylor","email":"","affiliations":[{"id":18916,"text":"U.S. Department of Agriculture, Forest Service, National Genomics Center for Wildlife and Fish Conservation, Rocky Mountain Research Station, Missoula, MT 59801 USA","active":true,"usgs":false}],"preferred":false,"id":845915,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Kimball, John S. 0000-0002-5493-5878","orcid":"https://orcid.org/0000-0002-5493-5878","contributorId":244377,"corporation":false,"usgs":false,"family":"Kimball","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":48908,"text":"U 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In Louisiana, USA, development of restored reefs, and off-bottom aquaculture would benefit from the identification of locations supportive of sustainable oyster populations (i.e., metapopulations) and high consistent production. This study defines four oyster resource zones across coastal Louisiana based on environmental conditions known to affect oyster survival, growth, and reproduction. Daily data from 2015 to 2019 were interpolated to generate salinity and temperature profiles across Louisiana's estuaries, which were then used to classify zones based on monthly and annual salinity mean and variance. Zones were classified as supportive of (1) broodstock sanctuary reefs (i.e., support reproductive populations), (2) productive reefs during dry (salty) years, (3) productive reefs during wet (fresh) years, and (4) off-bottom aquaculture development. Of the 38,000 km2 investigated, over 11,000 km2 of potential oyster zone area was identified across the Louisiana coast. The Broodstock Sanctuary Zone was the smallest (∼540 km2), as salinity variance limited this zone in many areas, as it is driven largely by riverine inputs across many estuaries. Located up-estuary (Dry Restoration Zone) and down-estuary (Wet Restoration Zone) of the Broodstock Sanctuary Zone, Dry and Wet Restoration Zone areas covered ∼2400 km2 and ∼3900 km2, respectively. Mapped reefs in Louisiana currently exist largely within the Dry Restoration zones, suggesting a potential strategy to focus reef development in Wet Restoration zones to ensure reef network sustainability through years with high precipitation and river inflow. The off-bottom Aquaculture Zone was the largest (∼6400 km2) zone identified, with much of this area located more down-estuary and off-shore. Accounting for variable water quality conditions enables the development of a network of reefs resilient to environmental variability, and more stable areas for consistent off-bottom aquaculture production. Spatial planning and identification of oyster resource zones reduces focus on individual reef success and supports management of oyster metapopulation outcomes, while identifying zones supportive of off-bottom aquaculture.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2022.106178","usgsCitation":"Swam, L.M., Couvillion, B., Callam, B., La Peyre, J., and La Peyre, M., 2022, Defining oyster resource zones across coastal Louisiana for restoration and aquaculture: Ocean and Coastal Management, v. 225, 106178, 11 p., https://doi.org/10.1016/j.ocecoaman.2022.106178.","productDescription":"106178, 11 p.","ipdsId":"IP-134836","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499824,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/animalsciences_pubs/2261","text":"External Repository"},{"id":433380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.28531382800476,\n 30.084673161811594\n ],\n [\n -89.8627113518053,\n 30.384080583724042\n ],\n [\n -90.30515265860349,\n 30.512183704575193\n ],\n [\n -90.81872980801528,\n 30.23163703531037\n ],\n [\n -91.21166619938886,\n 30.068757329434987\n ],\n [\n -93.742248457641,\n 30.376322644227812\n ],\n [\n -93.94164092204788,\n 29.613593061579024\n ],\n [\n -92.27979250199853,\n 29.44209715796825\n ],\n [\n -91.10243386209395,\n 29.085644613779976\n ],\n [\n -89.98832868271369,\n 28.980943971169282\n ],\n [\n -88.89450433276538,\n 28.983731357632564\n ],\n [\n -89.28531382800476,\n 30.084673161811594\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren M.","contributorId":341585,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":908656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callam, Brian","contributorId":341586,"corporation":false,"usgs":false,"family":"Callam","given":"Brian","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":341587,"corporation":false,"usgs":false,"family":"La Peyre","given":"Jerome F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908655,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232211,"text":"70232211 - 2022 - Golden Eagle (Aquila chysaetos)","interactions":[],"lastModifiedDate":"2022-06-28T16:02:50.008235","indexId":"70232211","displayToPublicDate":"2022-04-22T10:56:50","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","displayTitle":"Golden Eagle (Aquila chysaetos)","title":"Golden Eagle (Aquila chysaetos)","docAbstract":"The golden eagle (Aquila chrysaetos) is commonly recognized as an indicator of ecosystem health and was selected as an important indicator species for the ecological health of lands owned and managed by East Bay Stewardship Network (Network) partner agencies within the area of focus for this project (See map, Chapter 1). Based on national conservation goals and past and current golden eagle research in the area of focus, the desired condition and trend for this indicator species are to: (1) maintain or improve site occupancy by territorial pairs (i.e., the proportion of sites surveyed with at least 1 pair of eagles), (2) maximize reproductive rate (i.e., the proportion of sites surveyed with at least 1 pair of productive eagles), and (3) minimize the occurrence of territorial subadults in the local breeding population. The condition and trend in these three primary metrics were assessed for golden eagles in the area of focus using data from a large-scale demographic study conducted in 2014–2021 by the U.S. Geological Survey (USGS) and others. Overall, we found a condition of “caution” and an “unchanging” trend for golden eagles in the area of focus. Analyses of site occupancy and reproductive rate indicated that the local breeding population was unchanging (i.e., no evidence of increasing or decreasing time trends in these metrics during 2014–2021). However, a consistently high occurrence of territorial subadults (22%–35%) has been observed at breeding territories near the Altamont Pass Wind Resource Area (APWRA) relative to occupied territories monitored in surrounding regions (~3%). The heightened occurrence of territorial subadults suggested a possible increase in the adult mortality rate of territorial eagles occupying the Mt. Diablo Range and Mt. Hamilton subregions in the area of focus. Thus, although no trends were detected in site occupancy or reproductive rate, caution is warranted given the high observed frequency of territorial subadults, which was predominately associated with pairs monitored near the APWRA. The USGS golden eagle study was conducted during a period of prolonged and severe drought in the area of focus, which has been shown elsewhere to reduce the reproductive rate of golden eagles. Although we detected no trends in reproductive rate, we identified a condition of “caution” for this metric in the area of focus given that annual estimates were relatively low during the study period, which primarily included years of severe drought conditions in west-central California. A primary goal of the analysis was to provide a benchmark against which managers can measure future changes and understand the likely trajectory of this species. Baseline data and analyses provided here can be used to identify projects that could help support golden eagle conservation. Given the constraint of using only existing and available data, this evaluation also identified areas where not enough was known to draw meaningful conclusions. Gaps in our understanding include the long-term effects of repeated, extreme climate events (e.g., drought and wildfire) on golden eagle demographics and population sustainability, refined estimates of eagle survivorship and sources of mortality, and whether the APWRA represents a population sink for golden eagles within the northern Diablo Range and surrounding regions. These are described as data gaps at the end of this chapter and may be areas to focus on for future research and collaborations among land managers.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"NatureCheck: Understanding wildlife health on East Bay lands in Alameda and Contra Costa Counties","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"East Bay Stewardship Network","usgsCitation":"Wiens, D., Kolar, P., and Bell, D.A., 2022, Golden Eagle (Aquila chysaetos), chap. 8 of NatureCheck: Understanding wildlife health on East Bay lands in Alameda and Contra Costa Counties, p. 211-244.","productDescription":"34 p.","startPage":"211","endPage":"244","ipdsId":"IP-137929","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":402603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":402602,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.ebparks.org/natural-resources/biodiversity/wildlife"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wiens, David 0000-0002-2020-038X","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":267230,"corporation":false,"usgs":true,"family":"Wiens","given":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":844658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolar, Patrick 0000-0002-0076-7565 pkolar@usgs.gov","orcid":"https://orcid.org/0000-0002-0076-7565","contributorId":189512,"corporation":false,"usgs":true,"family":"Kolar","given":"Patrick","email":"pkolar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Douglas A.","contributorId":292466,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":844660,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241565,"text":"70241565 - 2022 - A novel herpesvirus detected in 3 different species of chelonians","interactions":[],"lastModifiedDate":"2023-03-23T14:57:45.866739","indexId":"70241565","displayToPublicDate":"2022-04-22T09:52:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2492,"text":"Journal of Veterinary Diagnostic Investigation","active":true,"publicationSubtype":{"id":10}},"title":"A novel herpesvirus detected in 3 different species of chelonians","docAbstract":"Herpesviruses are found in free-living and captive chelonian populations, often in association with morbidity and mortality. To date, all known chelonian herpesviruses fall within the subfamily Alphaherpesvirinae. We detected a novel herpesvirus in 3 species of chelonians: a captive leopard tortoise (Stigmochelys pardalis) in western TX, USA; a steppe tortoise (Testudo [Agrionemys] horsfieldii) found near Fort Irwin, CA, USA; and 2 free-living, three-toed box turtles (Terrapene mexicana triunguis) found in Forest Park, St. Louis, MO. The leopard tortoise was coinfected with the tortoise intranuclear coccidian and had clinical signs of upper respiratory tract disease. The steppe tortoise had mucopurulent nasal discharge and lethargy. One of the three-toed box turtles had no clinical signs; the other was found dead with signs of trauma after being observed with blepharedema, tympanic membrane swelling, cervical edema, and other clinical signs several weeks prior to death. Generally, the branching order of the turtle herpesviruses mirrors the divergence patterns of their hosts, consistent with codivergence. Based on phylogenetic analysis, this novel herpesvirus clusters with a clade of viruses that infect emydid hosts and is likely of box turtle origin. Therefore, we suggest the name terrapene alphaherpesvirus 3 (TerAHV3) for the novel virus. This virus also has the ability to host-jump to tortoises, and previously documented herpesviral morbidity tends to be more common in aberrant hosts. The relationship between clinical signs and infection with TerAHV3 in these animals is unclear, and further investigation is merited.
","language":"English","publisher":"American Association of Veterinary Laboratory Diagnosticians","doi":"10.1177/10406387221092048","usgsCitation":"Winter, J.M., Wellehan, J., Apakupakul, K., Palmer, J., Brenn-White, M., Standorf, K., Berry, K.H., Childress, A.L., Koplos, P., Garner, M.M., and Deem, S.L., 2022, A novel herpesvirus detected in 3 different species of chelonians: Journal of Veterinary Diagnostic Investigation, v. 34, no. 4, p. 594-601, https://doi.org/10.1177/10406387221092048.","productDescription":"8 p.","startPage":"594","endPage":"601","ipdsId":"IP-133654","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9266504","text":"Publisher Index Page"},{"id":414617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Winter, John M.","contributorId":303355,"corporation":false,"usgs":false,"family":"Winter","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":867331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wellehan, James F. X.","contributorId":303357,"corporation":false,"usgs":false,"family":"Wellehan","given":"James F. X.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":867332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Apakupakul, Kathleen","contributorId":303360,"corporation":false,"usgs":false,"family":"Apakupakul","given":"Kathleen","email":"","affiliations":[{"id":65777,"text":"Saint Louis Zoo","active":true,"usgs":false}],"preferred":false,"id":867333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmer, Jamie","contributorId":303362,"corporation":false,"usgs":false,"family":"Palmer","given":"Jamie","email":"","affiliations":[{"id":65777,"text":"Saint Louis Zoo","active":true,"usgs":false}],"preferred":false,"id":867334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenn-White, Maris","contributorId":302101,"corporation":false,"usgs":false,"family":"Brenn-White","given":"Maris","email":"","affiliations":[{"id":65410,"text":"University of California, Karen C. Drayer Wildlife Health Center, School of Veterinary Medicine, 1 Shields Avenue, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":867335,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Standorf, Kali","contributorId":303363,"corporation":false,"usgs":false,"family":"Standorf","given":"Kali","email":"","affiliations":[{"id":65780,"text":"THRIVE Affordable Vet Care, Jacksonville, FL","active":true,"usgs":false}],"preferred":false,"id":867336,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867337,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Childress, April L.","contributorId":220005,"corporation":false,"usgs":false,"family":"Childress","given":"April","email":"","middleInitial":"L.","affiliations":[{"id":40111,"text":"Department of Comparative, Diagnostic, and Population Medicine, College of Veterinary Medicine University of Florida, Gainesville, FL, USA","active":true,"usgs":false}],"preferred":false,"id":867338,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koplos, Pete","contributorId":303364,"corporation":false,"usgs":false,"family":"Koplos","given":"Pete","email":"","affiliations":[{"id":65781,"text":"El Paso Veterinary Specialty Center El Paso, TX","active":true,"usgs":false}],"preferred":false,"id":867339,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Garner, Michael M.","contributorId":303365,"corporation":false,"usgs":false,"family":"Garner","given":"Michael","email":"","middleInitial":"M.","affiliations":[{"id":65782,"text":"Northwest ZooPath, Monroe, WA","active":true,"usgs":false}],"preferred":false,"id":867340,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Deem, Sharon L.","contributorId":139277,"corporation":false,"usgs":false,"family":"Deem","given":"Sharon","email":"","middleInitial":"L.","affiliations":[{"id":12719,"text":"Whitney R. Harris, World Ecology Center, Uni. of Missouri St. Louis","active":true,"usgs":false}],"preferred":false,"id":867341,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ]}