Wilderness areas in the Mojave Desert, California, are remote and rugged terrain, but they contain important geology for understanding faults of the eastern California shear zone (ECSZ), and remote sensing offers techniques that can optimize mapping. The Bristol–Granite Mountain fault zone (BGMFZ) is the easternmost fault of the ECSZ with the Marble, Bristol, and Old Dad mountains on either side of the fault, as are the Trilobite and Bristol Mountain Wildernesses. In the northern Marble Mountains, a west-trending Miocene paleovalley has been proposed to have a correlative in the Old Dad Mountains and provides a constraint for right-lateral separation across the BGMFZ; however, this correlation is based on the premise that there was a unique paleovalley with a well defined geometry. In the northern Marble Mountains, a paleovalley was mapped by the distribution of (1) thickness and facies within the Lost Marble gravel (LMg) and 18.8 Ma Peach Spring Tuff (PST), and (2) adjacent highlands where the PST was deposited on basalt and dacite lava flows. Whether this paleovalley is unique, or there are other paleovalleys farther south in the Marble Mountains, requires mapping of the entire 5 by 28 km area of Miocene volcanic rocks. In the south Bristol and Old Dad mountains, there is a similar 12 by 22 km area of Miocene basalt and dacite with deposits of PST and local sedimentary rocks, including the proposed offset Lost Marble paleovalley, but the entire range needs to be mapped to establish a unique correlate. The mountains are in the Mojave Trails National Monument, and the Trilobite and Bristol Mountains wilderness areas, so access is limited. Remote sensing data, including aerial photography and hyperspectral images, are important for identification and characterization of rocks. Airborne hyperspectral Mako data can distinguish the distinctive spectral characteristics of the PST as well as several more map units identified by detailed field mapping in the Bristol Mountains. Reconnaissance maps derived from high spatial resolution Mako data can guide the detailed mapping needed to identify paleovalley or paleohighland deposits and can be used to optimize field time.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Volcanoes in the Mojave: 2022 Desert symposium field guide and proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Desert Symposium Inc","usgsCitation":"Buesch, D.C., and Harvey, J., 2022, Remote sensing and mapping Miocene paleovalleys of the Marble, Bristol, and Old Dad Mountains in the Trilobite and Bristol Mountain Wildernesses, California, in Volcanoes in the Mojave: 2022 Desert symposium field guide and proceedings, p. 94-102.","productDescription":"9 p.","startPage":"94","endPage":"102","ipdsId":"IP-132116","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":406452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406435,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertsymposium.org/History.html"}],"country":"United States","state":"California","otherGeospatial":"Trilobite and Bristol Mountain Wildernesses","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.05270385742188,\n 34.48957975202644\n ],\n [\n -115.41824340820312,\n 34.48957975202644\n ],\n [\n -115.41824340820312,\n 35\n ],\n [\n -116.05270385742188,\n 35\n ],\n [\n -116.05270385742188,\n 34.48957975202644\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buesch, David C. 0000-0002-4978-5027 dbuesch@usgs.gov","orcid":"https://orcid.org/0000-0002-4978-5027","contributorId":1154,"corporation":false,"usgs":true,"family":"Buesch","given":"David","email":"dbuesch@usgs.gov","middleInitial":"C.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":851358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Janet","contributorId":296385,"corporation":false,"usgs":false,"family":"Harvey","given":"Janet","email":"","affiliations":[{"id":64025,"text":"Heidelberg University Institute of Earth Sciences","active":true,"usgs":false}],"preferred":false,"id":851359,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230869,"text":"cir1493 - 2022 - Ungulate migration in a changing climate—An initial assessment of climate impacts, management priorities, and science needs","interactions":[],"lastModifiedDate":"2022-09-27T13:54:08.561993","indexId":"cir1493","displayToPublicDate":"2022-04-28T10:40:00","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":"1493","displayTitle":"Ungulate Migration in a Changing Climate—An Initial Assessment of Climate Impacts, Management Priorities, and Science Needs","title":"Ungulate migration in a changing climate—An initial assessment of climate impacts, management priorities, and science needs","docAbstract":"Migratory behavior among ungulates in the Western United States occurs in response to changing forage quality and quantity, weather patterns, and predation risk. As snow melts and vegetation green-up begins in late spring and early summer, many migratory ungulates leave their winter range and move to higher elevation summer ranges to access high-quality forage and areas with vegetative cover for protection during fawning. Ungulates remain on these ranges until the fall when increasing snowfall and decreasing temperatures trigger them to migrate back to their lower elevation winter ranges. While researchers have begun to assess the effects of physical barriers such as roads and energy infrastructure on migration, less attention has been paid to understanding how changing climate conditions might affect ungulate movements and range habitats. Does earlier spring green-up make ungulates leave their winter ranges sooner? Do persistent drought conditions reduce the carrying capacity of seasonal range habitats or lead to shifts in migration pathways? These and other questions remain largely unanswered but could have cascading effects on ungulate population dynamics and migratory behavior.
In February 2018, the Secretary of the Interior signed Department of the Interior Secretarial Order 3362 (SO3362), “Improving Habitat Quality in Western Big-Game Winter Range and Migration Corridors.” The order, which focuses on elk, mule deer, and pronghorn in 11 Western States, directs the Bureau of Land Management (BLM), the U.S. Fish and Wildlife Service (FWS), the National Park Service (NPS), and the U.S. Geological Survey (USGS) to partner with State wildlife agencies on their priorities and objectives for identifying and conserving ungulate migration corridors and winter-range habitat. The USGS Climate Adaptation Science Centers (CASCs) were established to help managers of the Nation’s fish, wildlife, waters, and lands understand the effects of climate change and adapt to changing conditions. To support the recent Department of the Interior (DOI) emphasis on ungulate migration corridors and winter-range habitat, this report assesses current information on how climate change could affect elk, mule deer, and pronghorn migration. The report synthesizes the drivers of migration, outlines what is known about how climate change might affect these drivers, and summarizes management priorities and science needs related to ungulate migration corridors and range habitat.
A review of the literature on ungulate migration shows that the core drivers of spring migration are the timing of spring green-up and snowmelt, and the core driver of fall migration is winter severity. After exploring what is known about how these drivers affect or could be affected by climate change, several pathways through which ungulate migration could be altered were identified: (1) ungulates alter migration timing to better track plant phenology or in response to changes in winter conditions; (2) ungulates change their migration route or distance traveled during migration to accommodate changes in environmental conditions; and (3) ungulate populations that are currently migratory may begin to demonstrate interannual variability in whether they migrate, depending on environmental conditions and density-dependence, and may remain resident for sets of consecutive years.
Through discussions with managers, physical barriers to movement such as roads and fences were identified as a core concern. In addition, the primary research needs of States are the acquisition and analysis of data on ungulate movements, to refine delineation of winter range, summer range, and corridors, and to support a better understanding of how ungulates use these habitats. When it comes to understanding climate effects, managers were more concerned with understanding the vulnerability of winter- and summer-range habitats than the vulnerability of migration corridors because of the influence of summer and winter forage on ungulate condition and reproductive success. Managers were also concerned about how forage quality and quantity might change because of stressors such as drought, wildfire, and invasive species and how they might need to alter habitat-treatment strategies as a result.
More baseline data are needed before effective projections of ungulate migration, at a West-wide scale under climate change, can be made. These data needs include (1) more clearly defined corridors and seasonal range habitats; (2) a comprehensive understanding of the ecological drivers of migration across ungulate species and populations; and (3) the identification of environmental thresholds for key variables that influence migration, above which ungulates alter migratory behavior.
The CASCs have several opportunities to play a role in addressing these needs. The CASCs could initiate projects to identify past and potential future changes and trends in key variables known to affect ungulate migration, such as plant phenology, forage quality, or winter severity. However, it would be difficult to use this information to determine what those trends mean for ungulate migration due to the lack of knowledge about environmental thresholds for ungulates. Additional projects would be required to compare multiple years of movement data with key variables to define thresholds. Once available, information on environmental thresholds could be integrated with projections of key variables to forecast the likelihood that the migration routes or the distance traveled could change—another area in which the CASCs could contribute.
A more immediate role for the CASCs would be to carry out synthesis projects. One such project could summarize the “state of the science” on the drivers of ungulate migration. Although there are dozens of population- and location-specific studies on this topic, collating this information could help highlight trends in migration drivers that span species and geographies: a necessary first step toward determining the extent to which migration drivers could be affected by climate change. A second project could focus on what is known about how climate variability and change affect ungulate life-histories, population dynamics, and migration in the Western United States. The goal of this effort could be to identify knowledge clusters and information gaps that require further investigation. Together, these synthesized products could focus future scientific activities on the most pressing issues of ungulate migration and climate change in the Western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1493","programNote":"Climate Adaptation Science Center and Land Change Science Program","usgsCitation":"Malpeli, K.C., 2022, Ungulate migration in a changing climate—An initial assessment of climate impacts, management priorities, and science needs: U.S. Geological Survey Circular 1493, 32 p., https://doi.org/10.3133/cir1493.","productDescription":"viii, 32 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119845","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":399812,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1493/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Circular 1493"},{"id":399744,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1493/cir1493.XML"},{"id":399743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1493/cir1493.pdf","text":"Report","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1493"},{"id":399742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1493/coverthb.jpg"},{"id":399745,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1493/images/"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-104.053249,41.001406],[-102.124972,41.002338],[-102.051292,40.749591],[-102.04192,37.035083],[-102.979613,36.998549],[-103.002247,36.911587],[-103.064423,32.000518],[-106.565142,32.000736],[-106.577244,31.810406],[-106.750547,31.783706],[-108.208394,31.783599],[-108.208573,31.333395],[-111.000643,31.332177],[-114.813613,32.494277],[-114.722746,32.713071],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.548194,46.248245],[-124.029924,46.308312],[-124.06842,46.601397],[-123.97083,46.47537],[-123.84621,46.716795],[-124.022413,46.708973],[-124.108078,46.836388],[-123.86018,46.948556],[-124.138035,46.970959],[-124.425195,47.738434],[-124.672427,47.964414],[-124.727022,48.371101],[-123.981032,48.164761],[-122.748911,48.117026],[-122.637425,47.889945],[-123.15598,47.355745],[-122.527593,47.905882],[-122.578211,47.254804],[-122.725738,47.33047],[-122.691771,47.141958],[-122.796646,47.341654],[-122.863732,47.270221],[-122.67813,47.103866],[-122.364168,47.335953],[-122.429841,47.658919],[-122.230046,47.970917],[-122.425572,48.232887],[-122.358375,48.056133],[-122.512031,48.133931],[-122.424102,48.334346],[-122.689121,48.476849],[-122.425271,48.599522],[-122.796887,48.975026],[-104.048736,48.999877],[-104.053249,41.001406]]],[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-122.519535,48.288314],[-122.66921,48.240614],[-122.400628,48.036563],[-122.419274,47.912125],[-122.744612,48.20965],[-122.664928,48.374823],[-122.519535,48.288314]]],[[[-122.800217,48.60169],[-122.883759,48.418793],[-123.173061,48.579086],[-122.949116,48.693398],[-122.743049,48.661991],[-122.800217,48.60169]]]]},\"properties\":{\"name\":\"Arizona\",\"nation\":\"USA \"}}]}","contact":"Director, National Climate Adaptation Science Center (CASC)
U.S. Geological Survey
Mail Stop 516
12201 Sunrise Valley Drive
Reston, VA 20192
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.
Freshwater aquatic macroinvertebrates are key links in food webs and nutrient cycles, and thus often serve as biological indicators of ecosystem health. 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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221029","collaboration":"Prepared in collaboration with Minnesota Department of Natural Resources and Bemidji State University","usgsCitation":"Keith, B.R., Carleen, J.D., Larson, D.M., Anteau, M.J., and Fitzpatrick, M.J., 2022, Protocols for collecting and processing macroinvertebrates from the benthos and water column in depressional wetlands: U.S. Geological Survey Open-File Report 2022–1029, 22 p., https://doi.org/10.3133/ofr20221029.","productDescription":"vi, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-127838","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":399709,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221029/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":399703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1029/ofr20221029.pdf","text":"Report","size":"4.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1029"},{"id":399702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1029/coverthb.jpg"},{"id":399705,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1029/images"},{"id":399704,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1029/ofr20221029.XML"}],"contact":"Director, Northern Prairie Wildlife Research Center
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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\"}}]}","edition":"Version 1.0: April 26, 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
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
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
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":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":70231218,"text":"70231218 - 2022 - Interaction between climate and tectonics in the northern Lesser Antilles inferred from the last interglacial shoreline on Barbuda island","interactions":[],"lastModifiedDate":"2022-05-03T11:41:00.842171","indexId":"70231218","displayToPublicDate":"2022-04-24T06:38:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Interaction between climate and tectonics in the northern Lesser Antilles inferred from the last interglacial shoreline on Barbuda island","docAbstract":"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.
Eastern oysters (Crassostrea virginica) are a critical ecological and commercial resource in the northern Gulf of Mexico facing changing environmental conditions from river management and climate change. 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":70259597,"text":"70259597 - 2022 - Integrating Earth–life systems: A geogenomic approach","interactions":[],"lastModifiedDate":"2024-10-16T12:09:25.931429","indexId":"70259597","displayToPublicDate":"2022-04-22T07:08:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5980,"text":"Trends in Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrating Earth–life systems: A geogenomic approach","docAbstract":"Migratory freshwater fishes are those that must access discrete habitats to complete their life cycles. Freshwater fish migrations occur around the world and provide numerous ecosystem services for humans and natural systems; however, many migratory species are in decline globally. A limiting factor to successfully conserve freshwater migratory fishes is that the migratory life histories of many species are unknown or only partially described. To provide researchers with critical and comprehensive information to conserve migratory fishes, we developed the North American Freshwater Migratory Fish Database (NAFMFD).
Canada, Mexico and the United States.
Freshwater fish.
To develop this database, we assigned migratory status, pattern and behaviour to a comprehensive list of freshwater fish species found throughout North America. We assembled the database which included assignments (i.e. migratory status, pattern and behaviour) as well as the sources used to make the assignments. Researchers and managers from across North America reviewed the database for completeness and accuracy on the migratory life histories of fishes.
The database synthesizes current knowledge of migratory status, pattern and behaviour of native and non-native freshwater fishes throughout North America, including 1250 species representing 79 families and 325 genera. Results showcase the diversity of migratory life histories of freshwater fishes on the continent, including that at least 25% of North American freshwater fishes are migratory, 23% are non-migratory and 44% have undetermined migratory status.
NAFMFD improves the quality of migratory data accessible to researchers, which supports a more holistic understanding of the threats encountered by migratory fishes, including habitat fragmentation. The approach we used in developing NAFMFD can provide guidance for developing similar databases in other regions. Collectively, our work offers new insights into the range of freshwater fish migratory life histories, stimulating a need to better understand this diversity globally.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14367","usgsCitation":"Dean, E., Cooper, A.R., Wang, L., Daniel, W., David, S., Ernzen, C., Gido, K.B., Hale, E., Haxton, T., Kelso, W., Leonard, N., Lido, C., Margraf, J., Porter, M., Pennock, C., Propst, D.L., Ross, J., Staudinger, M., Infante, D.M., and Whelan, G., 2022, The North American Freshwater Migratory Fish Database (NAFMFD): Characterizing the migratory life histories of freshwater fishes of Canada, the United States and Mexico: Journal of Biogeography, v. 49, no. 6, p. 1193-1203, https://doi.org/10.1111/jbi.14367.","productDescription":"11 p.; Data Release","startPage":"1193","endPage":"1203","ipdsId":"IP-135436","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448042,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.14367","text":"Publisher Index 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Wildlife,","active":true,"usgs":false}],"preferred":false,"id":842719,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Whelan, Gary","contributorId":146115,"corporation":false,"usgs":false,"family":"Whelan","given":"Gary","email":"","affiliations":[{"id":16584,"text":"Fisheries Division, Michigan Department of Natural Resources, P.O. Box 30446, Lansing, MI 48909","active":true,"usgs":false}],"preferred":false,"id":842718,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70231525,"text":"70231525 - 2022 - Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability","interactions":[],"lastModifiedDate":"2022-08-02T14:21:41.486398","indexId":"70231525","displayToPublicDate":"2022-04-21T08:43:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability","docAbstract":"Utility-scale solar energy (USSE) has become an efficient and cost-effective form of renewable energy, with an expanding footprint into rangelands that provide important habitat for many wild ungulate populations. Using global positioning system data collected before and after construction, we documented the potential impacts of USSE on pronghorn (Antilocapra americana), including direct habitat loss, indirect habitat loss, and barrier effects to both resident and migratory population segments. Our case study highlights the challenges that USSE poses to ungulate conservation, including (1) impermeable security fencing that blocks access to and reduces connectivity between formerly available habitats, and (2) the lack of guidelines for minimizing USSE impacts on ungulates. Improved siting and ungulate-specific best management practices would help to minimize habitat loss and retain landscape connectivity. Ungulate biodiversity and ecosystem services (for example, services provided by long-distance migratory species) in arid rangelands are important considerations when balancing the global benefits of renewable energy with local wildlife impacts.
Agriculture is a key element of Afghanistan’s economy and plays an essential role supporting the expanding population and urban development of Kabul, the country’s capital. Over the past decades the urban landscape has changed substantially and agricultural land use has shifted in its extent, location, and density. Identifying trends in the amount of agricultural area, as an indication of food production, is important for city planning and humanitarian efforts. While many studies have investigated Afghanistan's agriculture, most are conducted at scales that preclude their use for local-scale decision-making. This study quantifies agricultural extent across 32 years from 1988 to 2020 at local scale using simple and repeatable Landsat multispectral image analysis. The volume of data in time-series analysis complicatesvisualization of key findings and long-term trends. This study also explored visualization methods such as zonal mapping, animations, and the isolation of key themes in a 2D static map.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/17445647.2022.2063079","usgsCitation":"DeWitt, J.D., Boston, K.M., Alessi, M.A., and Chirico, P.G., 2022, Quantifying and visualizing 32 years of agricultural land use change in Kabul, Afghanistan: Journal of Maps, v. 18, no. 2, p. 352-361, https://doi.org/10.1080/17445647.2022.2063079.","productDescription":"10 p.","startPage":"352","endPage":"361","ipdsId":"IP-113897","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":448066,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17445647.2022.2063079","text":"Publisher Index Page"},{"id":435869,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WKTUBI","text":"USGS data release","linkHelpText":"Urban and developed areas indicated by classification of Landsat 2018 multispectral imagery"},{"id":435868,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IC4QFW","text":"USGS data release","linkHelpText":"Agricultural area by year between 1988 and 2000 in Kabul, Afghanistan"},{"id":405389,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Afghanistan","city":"Kabul","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 69,\n 34.347971491244955\n ],\n [\n 69.43771362304686,\n 34.347971491244955\n ],\n [\n 69.43771362304686,\n 34.75\n ],\n [\n 69,\n 34.75\n ],\n [\n 69,\n 34.347971491244955\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"DeWitt, Jessica D. 0000-0002-8281-8134 jdewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-8134","contributorId":5804,"corporation":false,"usgs":true,"family":"DeWitt","given":"Jessica","email":"jdewitt@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":849404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boston, Kathleen M 0000-0003-1301-9651","orcid":"https://orcid.org/0000-0003-1301-9651","contributorId":264351,"corporation":false,"usgs":false,"family":"Boston","given":"Kathleen","email":"","middleInitial":"M","affiliations":[{"id":54446,"text":"Aperture Federal, LLC","active":true,"usgs":false}],"preferred":false,"id":849405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alessi, Marissa Ann 0000-0002-1251-3108","orcid":"https://orcid.org/0000-0002-1251-3108","contributorId":244628,"corporation":false,"usgs":true,"family":"Alessi","given":"Marissa","email":"","middleInitial":"Ann","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":849406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chirico, Peter G. 0000-0001-8375-5342","orcid":"https://orcid.org/0000-0001-8375-5342","contributorId":63838,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":849407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230675,"text":"70230675 - 2022 - The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river","interactions":[],"lastModifiedDate":"2022-04-21T14:11:22.868251","indexId":"70230675","displayToPublicDate":"2022-04-20T09:05:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river","docAbstract":"In near-field remote sensing, noncontact methods (radars) that measure stage and surface water velocity have the potential to supplement traditional bridge scour monitoring tools because they are safer to access and are less likely to be damaged compared with in-stream sensors. The objective of this study was to evaluate the use of radars for monitoring the hydraulic conditions that contribute to bridge–pier scour in gravel-bed channels. Measurements collected with a radar were also leveraged along with minimal field measurements to evaluate whether time-integrated stream power per unit area (Ω) was correlated with observed scour depth at a scour-critical bridge in Colorado. The results of this study showed that (1) there was close agreement between radar-based and U.S. Geological Survey streamgage-based measurements of stage and discharge, indicating that radars may be viable tools for monitoring flow conditions that lead to bridge pier scour; (2) Ω and pier scour depth were correlated, indicating that radar-derived Ω measurements may be used to estimate scour depth in real time and predict scour depth based on the measured trajectory of Ω. The approach presented in this study is intended to supplement, rather than replace, existing high-fidelity scour monitoring techniques and provide data quickly in information-poor areas.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14091978","usgsCitation":"Hempel, L.A., Malenda, H.F., Fulton, J.W., Henneberg, M.F., Cederberg, J., and Moramarco, T., 2022, The applicability of time-integrated unit stream power for estimating bridge pier scour using noncontact methods in a gravel-bed river: Remote Sensing, v. 14, no. 9, 1978, 31 p., https://doi.org/10.3390/rs14091978.","productDescription":"1978, 31 p.","ipdsId":"IP-123910","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":448069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14091978","text":"Publisher Index Page"},{"id":399397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Gunnison River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.52638244628906,\n 38.966082600437986\n ],\n [\n -108.4134292602539,\n 38.966082600437986\n ],\n [\n -108.4134292602539,\n 39.055984163572404\n ],\n [\n -108.52638244628906,\n 39.055984163572404\n ],\n [\n -108.52638244628906,\n 38.966082600437986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malenda, Helen F. 0000-0003-4143-6460","orcid":"https://orcid.org/0000-0003-4143-6460","contributorId":211885,"corporation":false,"usgs":false,"family":"Malenda","given":"Helen","email":"","middleInitial":"F.","affiliations":[{"id":38341,"text":"Colorodo School of Mines","active":true,"usgs":false}],"preferred":true,"id":841125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulton, John W, 0000-0002-5335-0720","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":213630,"corporation":false,"usgs":true,"family":"Fulton","given":"John","middleInitial":"W,","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Henneberg, Mark F. 0000-0002-6991-1211 mfhenneb@usgs.gov","orcid":"https://orcid.org/0000-0002-6991-1211","contributorId":187481,"corporation":false,"usgs":true,"family":"Henneberg","given":"Mark","email":"mfhenneb@usgs.gov","middleInitial":"F.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841127,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cederberg, Jay 0000-0001-6649-7353","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":219724,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moramarco, Tommaso 0000-0002-9870-1694","orcid":"https://orcid.org/0000-0002-9870-1694","contributorId":225686,"corporation":false,"usgs":false,"family":"Moramarco","given":"Tommaso","email":"","affiliations":[{"id":41180,"text":"IRPI-Consiglio Nazionale delle Ricerche","active":true,"usgs":false}],"preferred":false,"id":841129,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231336,"text":"70231336 - 2022 - Evaluating the risk of SARS-CoV-2 transmission to bats in the context of wildlife research, rehabilitation, and control","interactions":[],"lastModifiedDate":"2022-08-02T14:17:08.974597","indexId":"70231336","displayToPublicDate":"2022-04-20T08:49:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the risk of SARS-CoV-2 transmission to bats in the context of wildlife research, rehabilitation, and control","docAbstract":"Preventing wildlife disease outbreaks is a priority for natural resource agencies, and management decisions can be urgent, especially in epidemic circumstances. With the emergence of SARS-CoV-2, wildlife agencies were concerned whether the activities they authorize might increase the risk of viral transmission from humans to North American bats, but had a limited amount of time in which to make decisions. We describe how decision analysis provides a powerful framework to analyze and reanalyze complex natural resource management problems as knowledge evolves. Coupled with expert judgment and avenues for the rapid release of information, risk assessment can provide timely scientific information for evolving decisions. In April 2020, the first rapid risk assessment was conducted to evaluate the risk of transmission of SARS-CoV-2 from humans to North American bats. Based on the best available information and relying heavily on expert judgment, the risk assessment found a small possibility of transmission during summer work activities. Following that assessment, additional knowledge and data emerged, such as bat viral challenge studies, that further elucidated the risks of human-to-bat transmission and culminated in a second risk assessment in the fall of 2020. We updated the first SARS-CoV-2 risk assessment with new management alternatives and new estimates of little brown bat (Myotis lucifugus) susceptibility, using findings from the fall 2020 assessment and other empirical studies. We found that new knowledge led to an 88% decrease in the median number of bats estimated to be infected per 1,000 encountered when compared to earlier results. The use of facemasks during, or a negative COVID-19 test or vaccination prior to, bat encounters further reduced those risks. Using a combination of decision analysis, expert judgment, rapid risk assessment, and efficient modes of information distribution, we provided timely science-based support to decision makers for summer bat work in North America.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1262","usgsCitation":"Cook, J.D., Campbell Grant, E.H., Coleman, J., Sleeman, J.M., and Runge, M.C., 2022, Evaluating the risk of SARS-CoV-2 transmission to bats in the context of wildlife research, rehabilitation, and control: Wildlife Society Bulletin, v. 46, no. 3, e1262, 16 p., https://doi.org/10.1002/wsb.1262.","productDescription":"e1262, 16 p.","ipdsId":"IP-129889","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":489846,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9111074","text":"External Repository"},{"id":400278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Jonathan D. 0000-0001-7000-8727","orcid":"https://orcid.org/0000-0001-7000-8727","contributorId":291411,"corporation":false,"usgs":true,"family":"Cook","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":842321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coleman, Jeremy T. H.","contributorId":291412,"corporation":false,"usgs":false,"family":"Coleman","given":"Jeremy T. H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":842323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":842324,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842325,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230750,"text":"70230750 - 2022 - Integrated hydrologic model development and postprocessing for GSFLOW using pyGSFLOW","interactions":[],"lastModifiedDate":"2022-04-25T11:18:23.466448","indexId":"70230750","displayToPublicDate":"2022-04-20T06:17:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5929,"text":"Journal of Open Source Software","active":true,"publicationSubtype":{"id":10}},"title":"Integrated hydrologic model development and postprocessing for GSFLOW using pyGSFLOW","docAbstract":"pyGSFLOW is a python package designed to create new GSFLOW integrated hydrologic models, read existing models, edit model input data, run GSFLOW models, process output, and visualize model data.
","language":"English","publisher":"Journal of Open Source Software","doi":"10.21105/joss.03852","usgsCitation":"Larsen, J., Alzraiee, A.H., and Niswonger, R.G., 2022, Integrated hydrologic model development and postprocessing for GSFLOW using pyGSFLOW: Journal of Open Source Software, v. 7, no. 7, 3852, 5 p., https://doi.org/10.21105/joss.03852.","productDescription":"3852, 5 p.","ipdsId":"IP-128406","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":448080,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21105/joss.03852","text":"Publisher Index Page"},{"id":435870,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NPZ5AD","text":"USGS data release","linkHelpText":"pyGSFLOW v1.0.0"},{"id":399570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Larsen, Joshua 0000-0002-1218-800X jlarsen@usgs.gov","orcid":"https://orcid.org/0000-0002-1218-800X","contributorId":272403,"corporation":false,"usgs":true,"family":"Larsen","given":"Joshua","email":"jlarsen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":841284,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242812,"text":"70242812 - 2022 - Improving the Development Pipelines for USGS Earthquake Hazards Program Real-Time and Scenario Products","interactions":[],"lastModifiedDate":"2023-04-19T11:58:50.843572","indexId":"70242812","displayToPublicDate":"2022-04-19T06:57:59","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Improving the Development Pipelines for USGS Earthquake Hazards Program Real-Time and Scenario Products","docAbstract":"The real-time and scenario products of the U.S. Geological Survey (USGS) Earthquake Hazards Program, such as the ComCat catalog, Did You Feel It?, ShakeMap, ShakeCast, and PAGER, are highly visible and used by a wide variety of stakeholders. We propose two significant enhancements to the development pipelines for the Earthquake Hazards Program real-time and scenario products that have far-reaching benefits. First, we propose incorporating processed and archived ground-motion records into the data streams for real-time products. This increases reproducibility and transparency for ShakeMap and downstream products that serve critical functions in earthquake response and long-term research. It will also provide comprehensive, open access databases of ground-motion metrics (for example, peak ground acceleration, peak ground velocity, and acceleration response spectra) and ground-motion time histories that are fundamental tools in most engineering seismology studies. Second, we propose extending the pipeline for scenario products to provide a full set of complementary products to the real-time pipeline. This would define a comprehensive set of standards for archiving scenarios, including three-dimensional ground-motion simulations, and allow the suite of scenario products to be disseminated in the same way as real-time products. Ultimately, these enhancements would increase the value of some of the most important Earthquake Hazards Program products and transform the way USGS scientists and the engineering seismology community conduct ground-motion research.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th National Conference on Earthquake Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, Utah","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Aagaard, B.T., Wald, D.J., Thompson, E.M., Hearne, M., and Schleicher, L.S., 2022, Improving the Development Pipelines for USGS Earthquake Hazards Program Real-Time and Scenario Products, in Proceedings of the 12th National Conference on Earthquake Engineering, Salt Lake City, Utah, June 27-July 1, 2022.","ipdsId":"IP-134896","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":415993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":415983,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12753"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":869850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":869851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":869852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":869853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schleicher, Lisa Sue 0000-0001-6528-1753","orcid":"https://orcid.org/0000-0001-6528-1753","contributorId":264892,"corporation":false,"usgs":true,"family":"Schleicher","given":"Lisa","email":"","middleInitial":"Sue","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":869854,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230710,"text":"70230710 - 2022 - Extreme rainstorms drive exceptional organic carbon export from forested humid-tropical rivers in Puerto Rico","interactions":[],"lastModifiedDate":"2022-05-23T14:56:24.206653","indexId":"70230710","displayToPublicDate":"2022-04-19T06:33:28","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":"Extreme rainstorms drive exceptional organic carbon export from forested humid-tropical rivers in Puerto Rico","docAbstract":"Extreme rainfall events in the humid-tropical Luquillo Mountains, Puerto Rico export the bulk of suspended sediment and particulate organic carbon. Using 25 years of river carbon and suspended sediment data, which targeted hurricanes and other large rainstorms, we estimated biogenic particulate organic carbon yields of 65 ± 16 tC km−2 yr−1 for the Icacos and 17.7 ± 5.1 tC km−2 yr−1 for the Mameyes rivers. These granitic and volcaniclastic catchments function as substantial atmospheric carbon-dioxide sinks, largely through export of river biogenic particulate organic carbon during extreme rainstorms. Compared to other regions, these high biogenic particulate organic carbon yields are accompanied by lower suspended sediment yields. Accordingly, particulate organic carbon export from these catchments is underpredicted by previous yield relationships, which are derived mainly from catchments with easily erodible sedimentary rocks. Therefore, rivers that drain petrogenic-carbon-poor bedrock require separate accounting to estimate their contributions to the geological carbon cycle.
Genetic analysis of non-invasively obtained samples is an increasingly affordable option for many wildlife studies, but it has remained difficult to obtain high-quality samples from many species. We modified 8” Belisle foot snares (Belisle Enterprises, Quebec, Canada) to non-invasively obtain mountain lion (Puma concolor) hair samples in unbaited trail sets. We deployed 22 hair traps, monitored by remote cameras, at 66 locations for 1618 active trap nights (x̄= 24.5 nights, SD = 7.2 nights). Photos indicated 20 instances of mountain lions passing within 2 m of a hair trap and we collected 7 mountain lion hair samples, which averaged >20 hairs/sample. All samples contained hair with visible roots and were identifiable to species; 6 of the 7 (85.7%) yielded sufficient DNA for individual identification. We attributed failure to obtain samples to 3 primary causes: individual trap saturation (2 instances), trap failure (2 instances), and non-trigger events (9 instances). Black bears (Ursus americanus) and heavy rains were the primary sources of disturbance to hair trap sets, contributing to individual trap saturation and trap failure. We speculate that low trigger rates were associated with pan tension having been set too high in the first month of the study, as well as disturbance of hair traps or leading foot placements by nontarget species. We discuss strategies to increase hair sample collection rates, including seasonal use of hair traps, more selective placement on the landscape, and altering physical attributes of the hair traps. Taking these strategies and the quality of hair samples collected into account, we believe hair traps are a viable tool for noninvasively collecting genetic material for individual identification of mountain lions and other elusive species. These data can be applied to studies of habitat connectivity, breeding success and relatedness, population density, metapopulation structure, or any others in which a bank of individual genotypes are useful.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1257","usgsCitation":"Rossettie, T., Perry, T., and Cain, J.W., 2022, Noninvasive sampling of mountain lion hair using modified foothold traps: Wildlife Society Bulletin, v. 46, no. 1, e1257, 13 p., https://doi.org/10.1002/wsb.1257.","productDescription":"e1257, 13 p.","ipdsId":"IP-119182","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486524,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Sierra County","otherGeospatial":"Black Range Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.48798824240478,\n 33.36187929179046\n ],\n [\n -108.48798824240478,\n 32.91656124812863\n ],\n [\n -107.58956320668692,\n 32.91656124812863\n ],\n [\n -107.58956320668692,\n 33.36187929179046\n ],\n [\n -108.48798824240478,\n 33.36187929179046\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-04-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rossettie, Tricia S.","contributorId":355783,"corporation":false,"usgs":false,"family":"Rossettie","given":"Tricia S.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":938152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Travis W.","contributorId":355784,"corporation":false,"usgs":false,"family":"Perry","given":"Travis W.","affiliations":[{"id":84836,"text":"fu","active":true,"usgs":false}],"preferred":false,"id":938153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938151,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230602,"text":"ofr20211030K - 2022 - System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)","interactions":[{"subject":{"id":70230602,"text":"ofr20211030K - 2022 - System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)","indexId":"ofr20211030K","publicationYear":"2022","noYear":false,"chapter":"K","displayTitle":"System Characterization Report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)","title":"System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2022-04-19T10:54:07.62676","indexId":"ofr20211030K","displayToPublicDate":"2022-04-18T15:29:12","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"K","displayTitle":"System Characterization Report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)","title":"System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA)","docAbstract":"This report addresses system characterization of the Italian Space Agency’s PRecursore IperSpettrale della Missione Applicativa (PRISMA) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (band to band and image to image), radiometric, and spatial performances. Results of these analyses indicate that PRISMA has a band-to-band geometric performance in the range of −0.046 to 0.040 pixel; an image-to-image geometric performance (relative to the Landsat 8 Operational Land Imager) in the range of −60.791 meters (m; −2.03 pixels) to 299.541 m (9.98 pixels); a radiometric performance in the range of −0.037 to −0.001 in offset and 1.026 to 1.274 in slope; and a spatial performance with a relative edge response in the range of 0.56 to 0.63, full width at half maximum in the range of 1.84 to 1.97 pixels, and a modulation transfer function at a Nyquist frequency in the range of 0.054 to 0.096. Regarding fairly large geometric accuracy, the following explanation is provided to help the reader. The geometric accuracy required for PRISMA is a 200-m circular error at 90 percent (CE90) without ground control points (GCPs), a 15-m CE90 using GCPs is documented in the PRISMA mission overview (Agenzia Spaziale Italiana, 2021). The PRISMA images used for the current system characterization were georeferenced without using any GCPs; thus, the 200-m geometric accuracy requirement is applied. Beginning in 2022, a worldwide GCP database will be used in the PRISMA product processing chain, which will improve georeferencing accuracy to meet the 15-m CE90 requirement.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030K","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2022, System characterization report on PRecursore IperSpettrale della Missione Applicativa (PRISMA), chap. K of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 28 p., https://doi.org/10.3133/ofr20211030K.","productDescription":"iv, 28 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-129829","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":398958,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/k/coverthb.jpg"},{"id":398959,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/k/ofr20211030k.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-K"},{"id":398960,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/k/ofr20211030k.XML"},{"id":398961,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/k/images"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The Willamette River is home to at least 69 species of fish, 33 of which are native, including Chinook salmon (Oncorhynchus tshawytscha) and steelhead (Oncorhynchus mykiss). These fish need suitable hydraulic conditions, such as water depth and velocity, to fulfill various stages of their life. Hydraulic conditions are driven by interactions between channel morphology and streamflow, which throughout the Willamette River are strongly influenced by the operation of flood-control dams in upstream tributaries. To assess how streamflow management at these dams affects downstream fish habitat, the U.S. Geological Survey has developed high-resolution bathymetric datasets to support the development of two-dimensional hydraulic models. The datasets were created by combining data collected by airborne topo-bathymetric Light Detection and Ranging with boat-based sonar to create a seamless modeling surface over which a computational mesh with a resolution of roughly 5 by 5 meters was overlaid using the U.S. Army Corps of Engineers Hydraulic Engineering Center’s River Analysis System 5.0.7 hydraulic modeling software. Models were developed for about 200 river kilometers, separated into five modeling reaches, and hydraulic conditions were simulated at flows ranging from extremely low values to annual peak flows. Results of the simulations highlight distinct patterns of inundation extents, water depths, and velocities that vary longitudinally along the Willamette River. In the two farthest upstream model reaches, from Eugene to Corvallis, the river is slower, shallower, and inundates more area at similar seasonal flows than in reaches downstream from Corvallis, where the river generally is deeper and faster. These findings align with previous geomorphic analysis of the Willamette River showing the upper reaches of the river to be geomorphically more dynamic compared to the largely single-thread channel farther downstream. Results of simulations made with these hydraulic models can be used to drive fish-habitat models to further inform flow-management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225025","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"White, J.S., and Wallick, J.R., 2022, Development of continuous bathymetry and two-dimensional hydraulic models for the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5025, 67 p., https://doi.org/10.3133/sir20225025.","productDescription":"viii, 67 p.","onlineOnly":"Y","ipdsId":"IP-112990","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":435872,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NB0KUT","text":"USGS data release","linkHelpText":"Two-dimensional HEC-RAS models and topo-bathymetric datasets for the Willamette River, Oregon"},{"id":435871,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92TTY4R","text":"USGS data release","linkHelpText":"Single-beam Echosounder Bathymetry of the Willamette River, Oregon 2015-2018"},{"id":398793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5025/coverthb.jpg"},{"id":502381,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112938.htm","linkFileType":{"id":5,"text":"html"}},{"id":398796,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5025/sir20225025.XML"},{"id":398795,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5025/images"},{"id":398794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5025/sir20225025.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5025"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.59619140625001,\n 43.94537239244209\n ],\n [\n -121.904296875,\n 43.94537239244209\n ],\n [\n -121.904296875,\n 45.521743896993634\n ],\n [\n -123.59619140625001,\n 45.521743896993634\n ],\n [\n -123.59619140625001,\n 43.94537239244209\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201