{"pageNumber":"338","pageRowStart":"8425","pageSize":"25","recordCount":166022,"records":[{"id":70237589,"text":"70237589 - 2022 - Defining the Hoek-Brown constant mi for volcanic lithologies","interactions":[],"lastModifiedDate":"2023-01-10T16:30:36.565423","indexId":"70237589","displayToPublicDate":"2022-12-05T11:49:27","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"displayTitle":"Defining the Hoek-Brown constant mi for volcanic lithologies","title":"Defining the Hoek-Brown constant mi for volcanic lithologies","docAbstract":"The empirical Hoek-Brown failure criterion is a well-known and commonly used failure criterion for both intact rocks and rock masses, especially in geological engineering. The intact criterion is calculated using experimental triaxial compression test results on intact samples while the rock mass criterion modifies the intact strength using quantified measures of the rock mass quality. The Hoek-Brown failure criterion includes a fitting constant for intact rocks, mi, which controls the steepness and curvature of the failure envelope, and is derived from curve-fitting the failure criterion to triaxial test data. However, because of the existence of tabulated mi values for various rock types, calculated using 1000’s of triaxial experiments, mi values are often extracted from the tables in the literature rather than the more time- and resource-intensive triaxial experiments. Using 100’s of triaxial experiments on variously altered volcanic rocks from volcanoes around the world, we demonstrate that mi varies dramatically based on a complex combination of alteration, lithology and texture, for example ranging from 2-38 for andesites. In contrast, tabulated estimates are typically given as small ranges, for example 25±5 for andesite. This means the failure criteria for volcanic rocks based on tabulated estimates could significantly over or under predict the intact strength, and thereby the rock mass strength, causing errors for stability and deformation assessments for a variety of volcanological and geological engineering purposes, from dome deformation or flank stability to excavation in volcanic rocks. In this research we not only highlight the high variability of mi for volcanic rocks, but by building on published relationships between porosity and strength, we demonstrate that it too is sensitive to porosity. We propose a number of preliminary methods to constrain mi values, including one using porosity.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rock mechanics and engineering geology in volcanic fields","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"5th International Workshop on Rock Mechanics and Engineering Geology in Volcanic Fields","conferenceDate":"September 9-10, 2021","conferenceLocation":"Fukuoka, Japan","language":"English","publisher":"CRC Press","usgsCitation":"Villeneuve, M., Heap, M.J., and Schaefer, L.N., 2022, Defining the Hoek-Brown constant mi for volcanic lithologies, in Rock mechanics and engineering geology in volcanic fields, Fukuoka, Japan, September 9-10, 2021, p. 261-268.","productDescription":"8 p.","startPage":"261","endPage":"268","ipdsId":"IP-135372","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409800,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/edit/10.1201/9781003293590/rock-mechanics-engineering-geology-volcanic-fields-takehiro-ohta-takatoshi-ito-masahiko-osada","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Villeneuve, Marlène C.","contributorId":260116,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Marlène C.","affiliations":[{"id":52510,"text":"Chair of Subsurface Engineering, Montanuniversität Leoben, Leoben, Austria","active":true,"usgs":false}],"preferred":false,"id":854543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heap, Michael J. 0000-0002-4748-735X","orcid":"https://orcid.org/0000-0002-4748-735X","contributorId":297882,"corporation":false,"usgs":false,"family":"Heap","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":64429,"text":"Université de Strasbourg","active":true,"usgs":false}],"preferred":false,"id":854544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":854545,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246696,"text":"70246696 - 2022 - Assigning causality to events in the Holocene record of coral reefs","interactions":[],"lastModifiedDate":"2023-07-17T12:44:53.442905","indexId":"70246696","displayToPublicDate":"2022-12-05T07:43:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16303,"text":"Journal of the Geological Society of London","active":true,"publicationSubtype":{"id":10}},"title":"Assigning causality to events in the Holocene record of coral reefs","docAbstract":"
The uncemented reef-frameworks of Pacific Panamá, which have been dominated throughout the Holocene by branching corals of the genus Pocillopora, experienced a hiatus in vertical accretion lasting c. 2300 years, beginning c. 4100 years ago. The hiatus has been attributed to an increase in variability of the El Niño–Southern Oscillation (ENSO). We tested the alternative hypothesis that the hiatus was solely the result of bioerosion, assuming an acute disturbance halted coral growth 1800 years ago (the time at which reef accretion resumed after the hiatus) and that the entire framework remained in the taphonomically active zone at that time. We calculate that it would have taken 167–511 years for bioerosion to fully remove 2300 years-worth of framework growth under those circumstances. In fact, most of the reef-framework in Panamá is stabilized in sediment that prevents the activity of bioeroders; only the upper c. 1 m of open framework – several decades-worth of growth at most – would have been vulnerable to erosion, greatly increasing the time required to bioerode 2300 years of accumulation. We conclude that the hiatus was not solely an artefact of bioerosion; rather, a long-term increase in ENSO variability suppressed coral growth and vertical reef accretion.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP529-2022-47","usgsCitation":"Rodriguez-Ruano, V., Toth, L., and Aronson, R.B., 2022, Assigning causality to events in the Holocene record of coral reefs: Journal of the Geological Society of London, v. 529, p. 281-292, https://doi.org/10.1144/SP529-2022-47.","productDescription":"12 p.","startPage":"281","endPage":"292","ipdsId":"IP-138413","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":419004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"529","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rodriguez-Ruano, Victor","contributorId":316663,"corporation":false,"usgs":false,"family":"Rodriguez-Ruano","given":"Victor","email":"","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":878027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":878028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":878029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254721,"text":"70254721 - 2022 - Nonlethal tools to identify mass ovarian follicular atresia in Burbot","interactions":[],"lastModifiedDate":"2024-06-07T11:45:57.939385","indexId":"70254721","displayToPublicDate":"2022-12-05T06:42:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nonlethal tools to identify mass ovarian follicular atresia in Burbot","docAbstract":"

Skipped spawning, or variation in spawning periodicity, occurs in many annual spawning fish species and is an important consideration for population management. We assessed plasma sex steroid concentrations and measured gonad size and ovarian follicle diameter as metrics to nonlethally identify mass ovarian follicular atresia, which may contribute to skipped spawning in Burbot Lota lota. We maintained wild fish in captivity and exposed them to increasing water temperatures during a 3-wk period before the spawning season to induce mass ovarian follicular atresia. We collected ovarian follicles, blood plasma, and gonadal sonograms from fish weekly between January 28, 2018, and March 25, 2018. We histologically analyzed ovarian follicles to confirm stage of maturity. We measured concentrations of plasma sex steroids testosterone (T) and estradiol-17β (E2) by radioimmunoassay. We measured gonad diameter and circumference by ultrasonography and ovarian follicle diameter by image analysis. Mean plasma T concentration decreased from 8.94 ng/mL during late vitellogenesis to 1.83 ng/mL during atresia, suggesting that plasma T concentrations may be used to identify mass ovarian follicular atresia. We do not recommend using plasma E2 concentrations to identify mass ovarian follicular atresia because E2 concentrations rapidly decreased during the completion of vitellogenesis and the initiation of atresia in Burbot; therefore, plasma E2 may not accurately identify mass ovarian follicular atresia. Mean gonad diameter measured by ultrasonography decreased from 4.05 cm during late vitellogenesis to 3.65 cm during atresia. Mean diameter of ovarian follicles decreased during the final week of the study, suggesting that ovarian follicle diameter may be used to identify advanced mass ovarian follicular atresia. The nonlethal tools assessed—plasma sex steroid concentrations, ultrasonography, and ovarian follicle diameter—enable fisheries biologists to determine the occurrence and frequency of mass ovarian follicular atresia among Burbot in Lake Roosevelt and may be applied to other Burbot populations.

","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-22-018","usgsCitation":"McGarvey, L.M., Ilgen, J.E., Guy, C.S., McLellan, J.G., and Webb, M., 2022, Nonlethal tools to identify mass ovarian follicular atresia in Burbot: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 552-561, https://doi.org/10.3996/JFWM-22-018.","productDescription":"10 p.","startPage":"552","endPage":"561","ipdsId":"IP-138975","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445712,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-22-018","text":"Publisher Index Page"},{"id":429623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"McGarvey, Lauren M.","contributorId":337314,"corporation":false,"usgs":false,"family":"McGarvey","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ilgen, Jason E.","contributorId":337315,"corporation":false,"usgs":false,"family":"Ilgen","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLellan, Jason G.","contributorId":337318,"corporation":false,"usgs":false,"family":"McLellan","given":"Jason","email":"","middleInitial":"G.","affiliations":[{"id":81010,"text":"Fish and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":902347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Molly A. H.","contributorId":337319,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263091,"text":"70263091 - 2022 - Drivers of habitat quality for a reintroduced elk herd","interactions":[],"lastModifiedDate":"2025-01-29T15:09:39.072874","indexId":"70263091","displayToPublicDate":"2022-12-05T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of habitat quality for a reintroduced elk herd","docAbstract":"

Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk (Cervus canadensis) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.

","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-022-25058-9","usgsCitation":"Quinlan, B., Rosenberger, J., Kalb, D., Abernathy, H., Thorne, E., Ford, W., and Cherry, M., 2022, Drivers of habitat quality for a reintroduced elk herd: Scientific Reports, v. 12, 20960, 12 p., https://doi.org/10.1038/s41598-022-25058-9.","productDescription":"20960, 12 p.","ipdsId":"IP-142591","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-25058-9","text":"Publisher Index Page"},{"id":481447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"southwestern Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.81797132520401,\n 37.10392995435147\n ],\n [\n -83.4791350332288,\n 36.59438261785931\n ],\n [\n -80.45872432537026,\n 36.57458088905058\n ],\n [\n -80.9768195014316,\n 37.315441708410084\n ],\n [\n -81.71516471822216,\n 37.318178569421775\n ],\n [\n -81.94847969969248,\n 37.58994839228791\n ],\n [\n -82.81797132520401,\n 37.10392995435147\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Quinlan, Braiden A.","contributorId":350149,"corporation":false,"usgs":false,"family":"Quinlan","given":"Braiden A.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Jacalyn P.","contributorId":350150,"corporation":false,"usgs":false,"family":"Rosenberger","given":"Jacalyn P.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":925499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kalb, David M.","contributorId":350151,"corporation":false,"usgs":false,"family":"Kalb","given":"David M.","affiliations":[{"id":39552,"text":"Rhode Island Department of Environmental Management","active":true,"usgs":false}],"preferred":false,"id":925500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abernathy, Heather N.","contributorId":350220,"corporation":false,"usgs":false,"family":"Abernathy","given":"Heather N.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Emily D.","contributorId":350153,"corporation":false,"usgs":false,"family":"Thorne","given":"Emily D.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":925502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":925503,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cherry, Michael J.","contributorId":350156,"corporation":false,"usgs":false,"family":"Cherry","given":"Michael J.","affiliations":[{"id":13724,"text":"Texas A&M University-Kingsville","active":true,"usgs":false}],"preferred":false,"id":925504,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240304,"text":"70240304 - 2022 - Maladaptive nest-site selection and reduced nest survival in female sage-grouse following wildfire","interactions":[],"lastModifiedDate":"2023-02-03T16:15:36.825568","indexId":"70240304","displayToPublicDate":"2022-12-04T10:09:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Maladaptive nest-site selection and reduced nest survival in female sage-grouse following wildfire","docAbstract":"

Increased wildfire frequency and associated replacement of sagebrush (Artemisia spp.) with invasive annual grasses contribute to declines of greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) populations across the Great Basin. However, little is known about wildfire effects on sage-grouse nest-site selection and nest survival, which can influence population persistence. The primary objective of this study was to evaluate the effects of the Rush Fire on sage-grouse nest survival using before (2007–2009) and after (2015–2018) data collected from a population of sage-grouse occupying the border of northeastern California and northwestern Nevada. We employed a before–after–control–impact (BACI) experimental design to account for spatiotemporal heterogeneity in the system and to derive estimates of relative change in survival parameters. Sage-grouse nest survival decreased after the Rush Fire but decreased more in the burned area relative to the unburned area. Although female sage-grouse continued to occupy burned areas, nest survival was reduced from 52% to 19%. Using a BACI ratio approach we found that nest survival decreased approximately 51% in the burned area, relative to the unburned area, following wildfire. Habitat analyses were restricted to the postfire period and found that female sage-grouse that nested within unburned areas selected for wider nesting substrate, taller perennial grass height, and greater low sagebrush canopy cover. Conversely, female sage-grouse that nested in burned areas used shorter sagebrush canopy cover than what was available across the entire study area but showed stronger selection for perennial grass height than their unburned counterparts. Strong nest-site fidelity in sage-grouse may explain the continued use of suboptimal habitat in wildfire-altered landscapes, resulting in a reproductive cost, and overall reproduction well below replacement rate. Results suggest that fire suppression or rapid postfire habitat restoration, especially within nesting habitat, may be essential to conserving robust sage-grouse populations into the future.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4282","usgsCitation":"Dudley, I.F., Coates, P.S., Prochazka, B.G., Davis, D.M., Gardner, S.C., and Delehanty, D.J., 2022, Maladaptive nest-site selection and reduced nest survival in female sage-grouse following wildfire: Ecosphere, v. 13, no. 12, e4282, 19 p., https://doi.org/10.1002/ecs2.4282.","productDescription":"e4282, 19 p.","ipdsId":"IP-120007","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445715,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4282","text":"Publisher Index Page"},{"id":412686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","county":"Lassen County, Washoe County","otherGeospatial":"Buffalo-Skedaddle Population Management Unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.94518975982814,\n 40.579947239546414\n ],\n [\n -120.2542712694401,\n 40.579947239546414\n ],\n [\n -120.2542712694401,\n 40.275652408838\n ],\n [\n -119.94518975982814,\n 40.275652408838\n ],\n [\n -119.94518975982814,\n 40.579947239546414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudley, Ian F.","contributorId":294783,"corporation":false,"usgs":false,"family":"Dudley","given":"Ian","email":"","middleInitial":"F.","affiliations":[{"id":56372,"text":"Stantec","active":true,"usgs":false}],"preferred":false,"id":863313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Dawn M.","contributorId":254959,"corporation":false,"usgs":false,"family":"Davis","given":"Dawn","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":863316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863318,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70243300,"text":"70243300 - 2022 - Divergent responses of butterflies and bees to burning and grazing management in tallgrass prairies","interactions":[],"lastModifiedDate":"2023-05-08T11:56:22.736279","indexId":"70243300","displayToPublicDate":"2022-12-04T06:52:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Divergent responses of butterflies and bees to burning and grazing management in tallgrass prairies","docAbstract":"

Butterflies and bees contribute significantly to grassland biodiversity and play important roles as pollinators and herbivores. Grassland conservation and management must be seen through the lens of insect conservation and management if these species are to thrive. In North America, grasslands are a product of climate and natural disturbances such as fire and grazing. These natural disturbances have changed considerably since European colonization and subsequent landscape fragmentation. The aim of this study was to better understand the impacts of fire and grazing management on butterfly and bee communities in tallgrass prairie, enabling land managers and conservationists to better protect and manage remnant prairie. We examined butterfly and bee abundance, species richness, and diversity in Minnesota tallgrass prairies managed by grazing or fire. In 2016 and 2017, we surveyed butterflies, bees, vegetation, and surrounding land use at 20 remnant prairies (10 burned and 10 grazed) with known management histories. Butterfly and bee abundance at our study sites were significantly negatively correlated. Butterfly abundance, but not species richness, was higher in burned than grazed prairies, and prairie-associated grass-feeding butterflies were more abundant at sites with higher plant species richness. Bee abundance was unrelated to management type but was higher at sites with sandier soils; bee species richness was positively associated with forb frequency. These findings highlight the challenges of designing management plans tailored to wide groups of pollinators and the potential pitfalls of using one group of pollinators as indicators for another. They also point to the importance of a mosaic of management practices across the prairie landscape.

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Migration schedules and the timing of other annual events (e.g., pair formation and molt) can affect the distribution of genetic diversity as much as where these events occur. The greater white-fronted goose (Anser albifrons) is a circumpolar goose species, exhibiting temporal and spatial variation of events among populations during the annual cycle. Previous range-wide genetic assessments of the nuclear genome based on eight microsatellite loci suggest a single, largely panmictic population despite up to five subspecies currently recognized based on phenotypic differences. We used double digest restriction-site associated DNA (ddRAD-seq) and mitochondrial DNA (mtDNA) sequence data to re-evaluate estimates of spatial genomic structure and to characterize how past and present processes have shaped the patterns of genetic diversity and connectivity across the Arctic and subarctic. We uncovered previously undetected inter-population differentiation with genetic clusters corresponding to sampling locales associated with current management groups. We further observed subtle genetic clustering within each management unit that can be at least partially explained by the timing and directionality of migration events along with other behaviors during the annual cycle. The Tule Goose (A. a. elgasi) and Greenland subspecies (A. a. flavirostris) showed the highest level of divergence among all sampling locales investigated. The recovery of previously undetected broad and fine-scale spatial structure suggests that the strong cultural transmission of migratory behavior restricts gene flow across portions of the species’ range. Our data further highlight the importance of re-evaluating previous assessments conducted based on a small number of highly variable genetic markers in phenotypically diverse species.

","language":"English","publisher":"MDPI","doi":"10.3390/d14121067","usgsCitation":"Wilson, R., Sonsthagen, S.A., DaCost, J.M., Sorenson, M., Fox, A., Weaver, M., Skalos, D., Kondratyev, A., Scribner, K., Walsh, A., Ely, C.R., and Talbot, S.L., 2022, As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore: Diversity, v. 14, no. 12, 1067, 23 p., https://doi.org/10.3390/d14121067.","productDescription":"1067, 23 p.","ipdsId":"IP-145453","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445720,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d14121067","text":"Publisher Index Page"},{"id":433109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Greenland, Russia, United States","otherGeospatial":"Circumpolar Arctic","geographicExtents":"{\n \"type\": 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This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (fR) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured fR. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on fR estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top fR estimation performance (R2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top fR estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (R2 = 0.7581; RMSE = 0.1548). The 2036–2111–2217 nm band combination was also top performing in fR estimation (R2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for fR estimation.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. 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T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":859061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271307,"text":"70271307 - 2022 - Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","interactions":[],"lastModifiedDate":"2025-09-08T14:03:52.052483","indexId":"70271307","displayToPublicDate":"2022-12-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2746,"text":"Mineralium Deposita","active":true,"publicationSubtype":{"id":10}},"title":"Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits","docAbstract":"

The North Australian Zinc Belt is the largest zinc-lead province in the world, containing three of the ten largest known individual deposits (HYC, Hilton-George Fisher, and Mount Isa). The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (238U/204Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00126-022-01153-9","usgsCitation":"Huston, D.L., Champion, D.C., Czarnota, K., Duan, J., Hutchens, M., Paradis, S., Hoggard, M., Ware, B., Gibson, G.M., Doublier, M.P., Kelley, K.D., McCafferty, A.E., Hayward, N., Richards, F., Tessalina, S., and Carr, G., 2022, Zinc on the edge—Isotopic and geophysical evidence that cratonic edges control world-class shale-hosted zinc-lead deposits: Mineralium Deposita, v. 58, p. 707-729, https://doi.org/10.1007/s00126-022-01153-9.","productDescription":"23 p.","startPage":"707","endPage":"729","ipdsId":"IP-135613","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495149,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495180,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00126-022-01153-9","text":"Publisher Index Page"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 134.27421209840645,\n -14.569058942329349\n ],\n [\n 134.27421209840645,\n -25.53495369611406\n ],\n [\n 142.46091725232395,\n -25.53495369611406\n ],\n [\n 142.46091725232395,\n -14.569058942329349\n ],\n [\n 134.27421209840645,\n -14.569058942329349\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Huston, David L. 0000-0002-1740-6336","orcid":"https://orcid.org/0000-0002-1740-6336","contributorId":328600,"corporation":false,"usgs":false,"family":"Huston","given":"David","middleInitial":"L.","affiliations":[{"id":35920,"text":"Geoscience 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Fred","contributorId":360921,"corporation":false,"usgs":false,"family":"Richards","given":"Fred","affiliations":[],"preferred":false,"id":947923,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tessalina, Svetlana","contributorId":360922,"corporation":false,"usgs":false,"family":"Tessalina","given":"Svetlana","affiliations":[],"preferred":false,"id":947924,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Carr, Graham","contributorId":360923,"corporation":false,"usgs":false,"family":"Carr","given":"Graham","affiliations":[],"preferred":false,"id":947925,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70238667,"text":"ofr20221100 - 2022 - Verification of multiple phosphorus analyzers for use in surface-water applications","interactions":[],"lastModifiedDate":"2026-03-30T20:49:48.631242","indexId":"ofr20221100","displayToPublicDate":"2022-12-02T13:49:32","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1100","displayTitle":"Verification of Multiple Phosphorus Analyzers for Use in Surface-Water Applications","title":"Verification of multiple phosphorus analyzers for use in surface-water applications","docAbstract":"

The U.S. Geological Survey (USGS) completed a verification study of selected commercially available phosphorus analyzers for their applicability to scientific surface-water applications. In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221100","collaboration":"Prepared in cooperation with the Next Generation Water Observing System","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., 2022, Verification of multiple phosphorus analyzers for use in surface-water applications: U.S. Geological Survey Open-File Report 2022–1100, 23 p., https://doi.org/10.3133/ofr20221100.","productDescription":"Report: viii, 23 p.; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-139337","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":410009,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221100/full","text":"Report"},{"id":409997,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.XML"},{"id":409995,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1100/coverthb.jpg"},{"id":501839,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113882.htm","linkFileType":{"id":5,"text":"html"}},{"id":409998,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1100/images"},{"id":409996,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1100"},{"id":409999,"rank":5,"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"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Vermilion River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.41449158849616,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 39.979211528524246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-12-02","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Peake, Colin S. 0000-0001-9712-1623","orcid":"https://orcid.org/0000-0001-9712-1623","contributorId":268354,"corporation":false,"usgs":true,"family":"Peake","given":"Colin","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858230,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238668,"text":"ofr20221080 - 2022 - Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19","interactions":[],"lastModifiedDate":"2026-03-30T20:36:11.952009","indexId":"ofr20221080","displayToPublicDate":"2022-12-02T13:21:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1080","displayTitle":"Summary of Extreme Water-Quality Conditions in Upper Klamath Lake, Oregon, 2005–19","title":"Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19","docAbstract":"

This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wherry, S.A., 2022, Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19: U.S. Geological Survey Open-File Report 2022–1080, 29 p., https://doi.org/10.3133/ofr20221080.","productDescription":"vii, 29 p.","onlineOnly":"Y","ipdsId":"IP-128098","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501831,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113883.htm","linkFileType":{"id":5,"text":"html"}},{"id":410005,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.XML"},{"id":410002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1080"},{"id":410001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1080/coverthb.jpg"},{"id":410004,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1080/images"},{"id":410003,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1080"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11865576927013,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.623699726465674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-12-02","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":858231,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238785,"text":"70238785 - 2022 - BIA branch of tribal climate resilience regional assessment report","interactions":[],"lastModifiedDate":"2022-12-12T15:38:22.405397","indexId":"70238785","displayToPublicDate":"2022-12-02T09:16:34","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":12977,"text":"Regional Assessment Report","active":true,"publicationSubtype":{"id":1}},"title":"BIA branch of tribal climate resilience regional assessment report","docAbstract":"

The Bureau of Indian Affairs (BIA) Branch of Tribal Climate Resilience (TCR) was established in 2011 to enable Tribal and BIA Office of Trust Services Programs to incorporate climate considerations into their programs' planning and decision-making. The TCR’s purpose is to fulfill trust responsibility to Federally recognized Tribal Nations by supporting and building Tribal capacity for climate resilience efforts through both technical and financial assistance. That financial assistance includes the TCR Annual Awards Program in which over 700 awards have been distributed totaling more than $74 million as of September 24th, 2021. The TCR has funded over 250 adaptation plans and vulnerability and risk assessments over the last 11 years. Tribes can leverage TCR programs to further support their existing operations, program planning, project design, as well as incorporate Indigenous and Traditional Knowledges into their management and protection of Trust resources and Tribal economies.

Due to the availability of TCR awards and other funding, many Tribes now have climate adaptation plans. Thus, both TCR and Tribes are at a new stage compared to a decade ago and have new needs related to implementation of climate adaptation and resiliency projects. This assessment aims to evaluate the effectiveness of TCR’s Annual Awards Program and technical assistance and incorporate direct Tribal input to meet Tribal needs and priorities. To provide more effective assistance to Tribal communities moving forward; BIA staff, in partnership with staff from the United States Geological Survey (USGS), interviewed 16 Tribal employees to gather their feedback on their approaches to climate adaptation as well as their experiences with TCR services. This report aims to summarize guidance from participating Tribes to inform future changes to BIA TCR.

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Center","active":true,"usgs":true}],"preferred":true,"id":858701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238880,"text":"70238880 - 2022 - GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions","interactions":[],"lastModifiedDate":"2022-12-15T13:54:31.86052","indexId":"70238880","displayToPublicDate":"2022-12-02T07:49:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions","docAbstract":"

The Chesapeake Bay is a region along the eastern coast of the United States where sea-level rise is confounded with poorly resolved rates of land subsidence, thus new constraints on vertical land motions (VLM) in the region are warranted. In this paper, we provide a description of two campaign-style Global Positioning System (GPS) datasets, explain the methods used in data collection and validation, and present the experiment designed to quantify a new baseline of VLM in the Chesapeake Bay region of eastern North America. Data from GPS campaigns in 2019 and 2020 are presented as ASCII RINEX2.11 files and logsheets for each observation from the campaigns. Data were quality checked using the open-source program TEQC, resulting in average multipath 1 and 2 values of 0.68 and 0.57, respectively. All data are archived and publicly available for open access at the geodesy facility UNAVCO to abide by Findable, Accessible, Interoperable, Reusable (FAIR) data principles.

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While there have been far fewer missions to the outer Solar System than to the inner Solar System, spacecraft destined for the giant planets have conducted a wide range of fundamental investigations, returning data that continues to reshape our understanding of these complex systems, sometimes decades after the data were acquired. These data are preserved and accessible from national and international planetary science archives. For all NASA planetary missions and instruments the data are available from the science discipline nodes of the NASA Planetary Data System (PDS). Looking ahead, the PDS will be the primary repository for giant planets data from several upcoming missions and derived datasets, as well as supporting research conducted to aid in the interpretation of the remotely sensed giant planets data already archived in the PDS.

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Laterally directed explosive eruptions are responsible for multiple fatalities over the past decade and are an increasingly important volcanology problem. To understand the energy dynamics for these events, we collected field-scale explosion data from nine acoustic sensors surrounding a tiltable cannon as part of an exploratory experimental design. For each cannon discharge, the blast direction was varied systematically at 0°, 12°, and 24° from vertical, capturing acoustic wavefield directivity related to the tilt angle. While each event was similar in energy discharge potential, the resulting acoustic signal features were variable event-to-event, producing non-repetitious waveforms and spectra. Systematic features were observed in a subset of individual events for vertical and lateral discharges. For vertical discharges, the acoustic energy had a uniform radiation pattern. The lateral discharges showed an asymmetric radiation pattern with higher frequencies in the direction of the blast and depletion of those frequencies behind the cannon. Results suggest that, in natural volcanic systems, near-field blast directionality may be elucidated from acoustic sensors in absence of visual data, with implications for volcano monitoring and hazard assessment.

","language":"English","publisher":"Springer","doi":"10.1186/s40623-022-01732-0","usgsCitation":"Jolly, A., Kennedy, B., Matoza, R.S., Iezzi, A., Christensen, B.W., Johnson, R., Sork, A., and Fee, D., 2022, Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon: Earth, Planets and Space, v. 74, 177, 16 p., https://doi.org/10.1186/s40623-022-01732-0.","productDescription":"177, 16 p.","ipdsId":"IP-138530","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-022-01732-0","text":"Publisher Index Page"},{"id":413396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":865016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Benjamin","contributorId":302666,"corporation":false,"usgs":false,"family":"Kennedy","given":"Benjamin","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":865018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":865019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Bruce W.","contributorId":196298,"corporation":false,"usgs":false,"family":"Christensen","given":"Bruce","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Richard","contributorId":190189,"corporation":false,"usgs":false,"family":"Johnson","given":"Richard","email":"","affiliations":[],"preferred":false,"id":865021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sork, Amilea","contributorId":302667,"corporation":false,"usgs":false,"family":"Sork","given":"Amilea","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865023,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238684,"text":"70238684 - 2022 - Can we avert an Amazon tipping point? The economic and environmental costs","interactions":[],"lastModifiedDate":"2022-12-05T12:37:03.967845","indexId":"70238684","displayToPublicDate":"2022-12-02T06:32:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Can we avert an Amazon tipping point? The economic and environmental costs","docAbstract":"

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

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0000-0002-7470-0697","orcid":"https://orcid.org/0000-0002-7470-0697","contributorId":213453,"corporation":false,"usgs":false,"family":"Coe","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":858265,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Neill, Christopher","contributorId":218247,"corporation":false,"usgs":false,"family":"Neill","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":858266,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Damiani Marti, Octavio","contributorId":299657,"corporation":false,"usgs":false,"family":"Damiani Marti","given":"Octavio","email":"","affiliations":[{"id":64921,"text":"Interamerican Development Bank","active":true,"usgs":false}],"preferred":false,"id":858267,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Avila Murillo, Josue","contributorId":299658,"corporation":false,"usgs":false,"family":"Avila Murillo","given":"Josue","email":"","affiliations":[{"id":64921,"text":"Interamerican Development Bank","active":true,"usgs":false}],"preferred":false,"id":858268,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70236050,"text":"70236050 - 2022 - Wetland ecosystem health and biodiversity","interactions":[],"lastModifiedDate":"2024-03-27T20:46:12.939206","indexId":"70236050","displayToPublicDate":"2022-12-01T15:45:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"chapter":"14","title":"Wetland ecosystem health and biodiversity","docAbstract":"

• Cropland expansion from 2008 to 2016 was mostly from losses of grassland (88%), with 3% losses from wetlands (a total of nearly 275,000 acres of wetlands, concentrated in the Prairie Pothole Region). Given the lack of national or regional datasets to track changes in RFS acreage, the extent of wetland losses directly attributable to the RFS cannot be more accurately estimated in the RtC3.

• Wetlands gains and losses are not distributed evenly across wetland types or sizes. Since 2007, the nation has lost 120.3 thousand acres of palustrine (marsh-like) wetlands and gained 205.9 thousand acres of lacustrine (lake-like) habitats in the conterminous United States. The diverse wetlands within these classes support different species and perform different ecosystem functions, including loss of functions that impact watershed hydrology, water quality, and water quantity.

• Small, seasonal wetlands are being lost at the fastest rate. The loss and consolidation of small wetlands to promote crop production has negatively impacted amphibians, invertebrates, and other aquatic species that depend on shallow water depths for reproduction. Shifts to longer hydroperiods in large or consolidated wetlands have more uniform (less diverse) invertebrate communities and can support fish that prey on insects and amphibians.

• Small wetlands and ponds are primary sources of water for aquifer recharge in the Northern Prairies. Recent studies in the Canadian portion of the Prairie Pothole Region found that while permanent ponds and wetlands are sources for recharge to aquifers, wetlands with surface water ponds that dry out every year play the dominant role in groundwater replenishment.

• While some Endangered Species Act-listed and other waterbirds have declined, waterfowl (ducks, geese, swans) as a group have not experienced declines over the past decade, possibly due to availability of food (grains), increased precipitation, and the interspersion of ponded waters and agricultural fields along migration routes.

• Shifts to corn and soybean production have resulted in more frequent application of chemicals, including pesticides and fertilizers. Increased usage of neonicotinoid insecticides is of particular concern because of their high toxicity to invertebrates, which are important food sources for wetland-dependent taxa.

• Evidence from the Prairie Pothole Region suggests that trends in larger wetland size, shifts to lakes and ponds (vs. vegetated wetlands), and prolonged and more frequent flooding are due to the combined effects of climate change and increased wetland ditching and consolidation. These trends are highly correlated with increased annual precipitation, which is projected to continue.

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Mitigating risk to migratory birds from energy development requires information on the distribution and abundance of seabirds in offshore waters. Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Marine bird distribution and abundance in offshore waters","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"Bureau of Ocean Energy Management (BOEM AK-17-03)","usgsCitation":"Arimitsu, M.L., and Kathy Kuletz, 2022, Appendix 7: Application of joint dynamic species distribution models to at-sea survey data for seabirds in the Bering Strait and Chukchi Sea, 13 p.","productDescription":"13 p.","startPage":"163","endPage":"175","ipdsId":"IP-144357","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":417892,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.boem.gov/regions/alaska-ocs-region/scientific-and-technical-publications-2022"},{"id":427246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 72\n ],\n [\n -179.9,\n 62\n ],\n [\n -146,\n 62\n ],\n [\n -146,\n 72\n ],\n [\n -179.9,\n 72\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":874854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kathy Kuletz","contributorId":306145,"corporation":false,"usgs":false,"family":"Kathy Kuletz","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":874855,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251468,"text":"70251468 - 2022 - Progress and challenges toward the development of a uniform moment magnitude catalog for eastern Canada","interactions":[],"lastModifiedDate":"2026-03-25T15:45:39.430885","indexId":"70251468","displayToPublicDate":"2022-12-01T10:43:00","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Progress and challenges toward the development of a uniform moment magnitude catalog for eastern Canada","docAbstract":"

No abstract available.

","conferenceTitle":"3ECEES - Third European Conference on Earthquake Engineering & Seismology","conferenceDate":"September 4-9, 2022","conferenceLocation":"Bucharest, Romania","language":"English","publisher":"Conspress","usgsCitation":"Bent, A.L., Mayeda, K., Roman-Nieves, J., Shelly, D.R., and Barno, J., 2022, Progress and challenges toward the development of a uniform moment magnitude catalog for eastern Canada, 3ECEES - Third European Conference on Earthquake Engineering & Seismology, Bucharest, Romania, September 4-9, 2022, p. 5105-5111.","productDescription":"7 p.","startPage":"5105","endPage":"5111","ipdsId":"IP-139522","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bent, Allison L.","contributorId":239555,"corporation":false,"usgs":false,"family":"Bent","given":"Allison","email":"","middleInitial":"L.","affiliations":[{"id":47914,"text":"Canadian Hazards Information Service","active":true,"usgs":false}],"preferred":false,"id":894659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayeda, Kevin","contributorId":289896,"corporation":false,"usgs":false,"family":"Mayeda","given":"Kevin","email":"","affiliations":[{"id":62278,"text":"Air Force Technical Applications Center, USA","active":true,"usgs":false}],"preferred":false,"id":894660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roman-Nieves, Jorge I.","contributorId":334069,"corporation":false,"usgs":false,"family":"Roman-Nieves","given":"Jorge I.","affiliations":[{"id":80057,"text":"Air Force Technical Applications Center","active":true,"usgs":false}],"preferred":false,"id":894661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":894662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barno, Justin","contributorId":289897,"corporation":false,"usgs":false,"family":"Barno","given":"Justin","email":"","affiliations":[{"id":62279,"text":"Lawrence Livermore National Laboratory, Livermore, CA, USA","active":true,"usgs":false}],"preferred":false,"id":894663,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263604,"text":"70263604 - 2022 - Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States","interactions":[],"lastModifiedDate":"2025-02-18T16:43:58.785838","indexId":"70263604","displayToPublicDate":"2022-12-01T10:38:16","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States","docAbstract":"

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that could be produced using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying onshore and State-owned offshore waters (herein after, onshore and State waters areas) of the conterminous United States. Our assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were amenable to miscible CO2 injection. The assessed reservoirs are located in 185 plays previously defined by a USGS National Oil and Gas Assessment in 33 petroleum provinces of seven national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 probability percentile to as much as 32,000 MMbbl at the P95 probability percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt.

","conferenceTitle":"Social Science Research Network (SSRN), Conference Paper, 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16","conferenceDate":"October 23-27, 2022","conferenceLocation":"Lyon, France","language":"English","publisher":"SSRN Elsevier","doi":"10.2139/ssrn.4279712","usgsCitation":"Warwick, P., Attanasi, E., Blondes, M., Brennan, S., Buursink, M., Cahan, S., Doolan, C.A., Freeman, P., Karacan, C.O., Lohr, C., Merrill, M., Olea, R., Shelton, J., Slucher, E.R., and Varela, B.A., 2022, Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States, Social Science Research Network (SSRN), Conference Paper, 16th International Conference on Greenhouse Gas Control Technologies, GHGT-16, Lyon, France, October 23-27, 2022, 6 p., https://doi.org/10.2139/ssrn.4279712.","productDescription":"6 p.","ipdsId":"IP-144052","costCenters":[{"id":241,"text":"Eastern Energy Resources Science 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This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The original ABAM model has little information about the effects of the herbicide indaziflam (Esplanade or Rejuvra, Bayer Environmental Sciences) on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to provide some of that information in order to accelerate the rate of learning accomplished in the adaptive management cycle. This annual report to the partner provides that information as collected in 2022 in 3 plots at Little Bighorn Battlefield National Monument.","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., and Bekedam, S., 2022, Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-152074","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415840,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573321","linkFileType":{"id":5,"text":"html"}},{"id":426326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Little Bighorn Battlefield National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.42780937203189,\n 45.55613907753829\n ],\n [\n -107.41424157476726,\n 45.56297486244455\n ],\n [\n -107.42644541357662,\n 45.57478473659421\n ],\n [\n -107.44274112775177,\n 45.56674424099478\n ],\n [\n -107.44575619381031,\n 45.566543213856875\n ],\n [\n -107.44259755317754,\n 45.56327642203598\n ],\n [\n -107.43943891254428,\n 45.56151730159996\n ],\n [\n -107.4385056778117,\n 45.560763375980855\n ],\n [\n -107.44123359472226,\n 45.55814968884059\n ],\n [\n -107.43814674137612,\n 45.55679253410301\n ],\n [\n -107.43584954818878,\n 45.55789836636245\n ],\n [\n -107.43412665329791,\n 45.56016022820128\n ],\n [\n -107.43218839654568,\n 45.55855180246806\n ],\n [\n -107.43419844058504,\n 45.55593801245129\n ],\n [\n -107.43075265080329,\n 45.555586146818285\n ],\n [\n -107.42780937203189,\n 45.55613907753829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekedam, Steven","contributorId":240924,"corporation":false,"usgs":false,"family":"Bekedam","given":"Steven","email":"","affiliations":[{"id":29837,"text":"National Park Service, Yellowstone National Park, WY","active":true,"usgs":false}],"preferred":false,"id":895966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238432,"text":"sir20225101 - 2022 - Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18","interactions":[],"lastModifiedDate":"2026-04-27T19:03:56.914908","indexId":"sir20225101","displayToPublicDate":"2022-12-01T10:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5101","displayTitle":"Stormwater Reduction and Water Budget for a Rain Garden on Sandy Soil, Gary, Indiana, 2016–18","title":"Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18","docAbstract":"

Stormwater reduction measures, or green infrastructure, were implemented in the parking area at Gary City Hall, Gary, Indiana, with the intention of reducing stormwater discharge to the sewers. A study area, including a centrally located rain garden and the surrounding paved surfaces and green space, was instrumented during both a preconstruction and a postconstruction period to (1) develop water budgets to improve understanding of the rain garden hydrology and (2) determine the quantity of stormwater runoff that was diverted and retained by the green infrastructure instead of reaching the combined storm and sanitary sewer. The study was focused on warm-season precipitation and was monitored during spring, summer, and fall of 2016, 2017 and 2018.

Before construction of the rain garden in the parking lot of Gary City Hall in 2017, nearly all precipitation was conveyed away from the parking lot by underground drains, discharged to the sewer, and treated as sanitary waste at the Gary Sanitary District’s treatment plant or discharged directly to local waterways if stormflow exceeded capabilities of the sewage treatment plant. A goal of the Great Lakes Restoration Initiative is the reduction of sewer overflows to local waterways to improve the quality of water entering the Great Lakes. Cities such as Gary benefit financially and environmentally by reducing discharges of stormwater runoff to the sewer system, eliminating the need for treatment. Before implementation of green infrastructure at Gary City Hall, approximately 25 percent of precipitation (approximately 10,200 cubic feet) discharged as stormwater to the sewers through the parking lot drain. After implementation, 2 percent of precipitation discharged to the sewers. For the spring, summer, and fall seasons of 2017 and 2018, 21–24 percent (about 10,700–19,700 cubic feet) of precipitation was captured by the newly installed rain garden. Stormwater discharged to the rain garden infiltrated the sandy soil and was later evaporated from the soil surface, was transpired by plants, or recharged the underlying groundwater aquifer. The percent reduction in stormwater discharged to the storm sewer after the construction of the rain garden was 80.3 percent, equating to approximately 21,400 and 39,300 gallons of stormwater in 2017 and 2018, respectively.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225101","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Lampe, D.C., Bayless, E.R., and Follette, D.D., 2022, Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18: U.S. Geological Survey Scientific Investigations Report 2022–5101, 39 p., https://doi.org/10.3133/sir20225101.","productDescription":"Report: viii, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126798","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":503563,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113881.htm","linkFileType":{"id":5,"text":"html"}},{"id":409548,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.XML"},{"id":409546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.pdf","text":"Report","size":"7.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5101"},{"id":409545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5101/coverthb.jpg"},{"id":409550,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H5RNNE","text":"USGS data release","linkHelpText":"Groundwater recharge estimates for a green infrastructure installation at Gary City Hall, Gary, Indiana 2016–18"},{"id":409549,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5101/images/"}],"country":"United States","state":"Indiana","city":"Gary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.33719284301965,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.60392762249708\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-12-01","noUsgsAuthors":false,"publicationDate":"2022-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lampe, David C. 0000-0002-8904-0337 dclampe@usgs.gov","orcid":"https://orcid.org/0000-0002-8904-0337","contributorId":2441,"corporation":false,"usgs":true,"family":"Lampe","given":"David","email":"dclampe@usgs.gov","middleInitial":"C.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bayless, E. Randall 0000-0002-0357-3635","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":42586,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"","middleInitial":"Randall","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Follette, Danielle D. 0000-0002-3203-813X","orcid":"https://orcid.org/0000-0002-3203-813X","contributorId":299291,"corporation":false,"usgs":true,"family":"Follette","given":"Danielle","email":"","middleInitial":"D.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":857481,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238110,"text":"70238110 - 2022 - Bivalves","interactions":[],"lastModifiedDate":"2026-03-18T15:25:15.112087","indexId":"70238110","displayToPublicDate":"2022-12-01T10:19:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"98","chapter":"5","title":"Bivalves","docAbstract":"

Bivalves are important as consumers of pelagic and demersal food resources. With sufficient biomass, they can compete with and, in some cases, outcompete other members of the pelagic food web for food resources such as phytoplankton and zooplankton.  We include bivalves in the San Francisco Estuary (SFE) and Delta in the FLOAT MAST because they have been and continue to be an important member of the food web. Changes in the bivalves over the last 40 years have led us to hypothesize that bivalves may limit food resources for Delta Smelt and other pelagic fish species (Kimmerer and Thompson 2014, Sommer et al 2007).

We will discuss the two bivalves with the largest biomass, the estuarine bivalve Potamocorbula amurensis (hereafter Potamocorbula) and the freshwater bivalve Corbicula fluminea (hereafter Corbicula).  The distribution of these two species together covers the full range of salinities between the Golden Gate and the upstream reaches of the SR and SJR.  The species overlap in the region of X2.  Both species’ distributions expand or contract when the salinity distribution changes and do so in near synchrony with each other at a salinity of approximately 2.   It is this interaction of both bivalves at their threshold levels of salinity within the ecologically sensitive low salinity zone (LSZ) in addition to their distribution in the rest of the system that determines each species effect on the food web.  

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"White papers providing a synthesis of knowledge relating to Delta Smelt biology in the San Francisco Estuary, emphasizing effects of flow","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Interagency Ecological Program for the San Francisco Bay-Delta Estuary","usgsCitation":"Thompson, J.K., 2022, Bivalves: IEP Technical Report 98, 20 p.","productDescription":"20 p.","startPage":"84","endPage":"103","ipdsId":"IP-134014","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":409287,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iep.ca.gov/Publications/Technical-Publications"},{"id":501248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.94540458800081,\n 39.02592236382674\n ],\n [\n -122.52823343529754,\n 39.02592236382674\n ],\n [\n -122.52823343529754,\n 37.5452436738196\n ],\n [\n -120.94540458800081,\n 37.5452436738196\n ],\n [\n -120.94540458800081,\n 39.02592236382674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":856903,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70242768,"text":"70242768 - 2022 - Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report","interactions":[],"lastModifiedDate":"2024-03-05T16:22:08.807736","indexId":"70242768","displayToPublicDate":"2022-12-01T10:13:24","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report","docAbstract":"

The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model's parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating is called \"learning.\" Currently, the ABAM model has little information about the effects of the herbicide indaziflam, applied alone or together with the herbicide imazapic, at different times during the growing season, on target invasive annual grasses and other components of the vegetation. The purpose of this study is to increase the amount of information about this herbicide and therefore accelerate the rate of learning accomplished in the adaptive management cycle.

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No abstract available.

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