Channels change in response to natural or anthropogenic fluctuations in streamflow and/or sediment supply and measurements of channel change are critical to many river management applications. Whereas repeated field surveys are costly and time‐consuming, remote sensing can be used to detect channel change at multiple temporal and spatial scales. Repeat images have been widely used to measure long‐term channel change, but these measurements are only significant if the magnitude of change exceeds the uncertainty. Existing methods for characterizing uncertainty have two important limitations. First, while the use of a spatially variable image co‐registration error avoids the assumption that errors are spatially uniform, this type of error, as originally formulated, can only be applied to linear channel adjustments, which provide less information on channel change than polygons of erosion and deposition. Second, previous methods use a level‐of‐detection (LoD) threshold to remove non‐significant measurements, which is problematic because real changes that occurred but were smaller than the LoD threshold would be removed. In this study, we present a new method of quantifying uncertainty associated with channel change based on probabilistic, spatially varying estimates of co‐registration error and digitization uncertainty that obviates a LoD threshold. The spatially distributed probabilistic (SDP) method can be applied to both linear channel adjustments and polygons of erosion and deposition, making this the first uncertainty method generalizable to all metrics of channel change. Using a case study from the Yampa River, Colorado, we show that the SDP method reduced the magnitude of uncertainty and enabled us to detect smaller channel changes as significant. Additionally, the distributional information provided by the SDP method allowed us to report the magnitude of channel change with an appropriate level of confidence in cases where a simple LoD approach yielded an indeterminate result.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4926","usgsCitation":"Leonard, C., Legleiter, C.J., Lea, D.M., and Schmidt, J.C., 2020, Measuring channel planform change from image time series: A generalizable, spatially distributed, probabilistic method for quantifying uncertainty: Earth Surface Processes and Landforms, v. 45, no. 11, p. 2727-2744, https://doi.org/10.1002/esp.4926.","productDescription":"18 p.","startPage":"2727","endPage":"2744","ipdsId":"IP-113525","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436932,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SEBJ3X","text":"USGS data release","linkHelpText":"Aerial photographs from the Yampa and Little Snake Rivers in northwest Colorado used to characterize channel changes occurring between 1954 and 1961"},{"id":378500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Leonard, Christina","contributorId":195596,"corporation":false,"usgs":false,"family":"Leonard","given":"Christina","email":"","affiliations":[],"preferred":true,"id":799076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":799077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lea, Devin M.","contributorId":240907,"corporation":false,"usgs":false,"family":"Lea","given":"Devin","email":"","middleInitial":"M.","affiliations":[{"id":48159,"text":"Department of Geography, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":799078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":799079,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210999,"text":"70210999 - 2020 - Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA)","interactions":[],"lastModifiedDate":"2020-08-26T19:19:54.479689","indexId":"70210999","displayToPublicDate":"2020-06-12T08:27:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA)","docAbstract":"This research examined the influences of outflow characteristics affecting riverbank stability. The 130 km stretch of the lower Osage River downstream from Bagnell Dam (Missouri, USA) provided an excellent case study for this purpose. The integrated BSTEM model with the HEC-RAS model was accurately calibrated and validated with data from the U.S. Geological Survey (USGS). Then, the outflow characteristics (peak flow duration, flow drawdown rate, and low flow duration) were investigated individually. The results of this study showed that: 1) Riverbank stability is little affected by the duration time of the peak flow, especially on the reaches far from the dam. 2) Sudden flow drawdown significantly reduces riverbank stability. However, the impact of the drawdown rate decreases with distance from the dam. 3) The duration of the low flow after peak flow influences the riverbank stability value proportional to the distance from the dam. The time of low flow before failure increases as the distance from the dam increases.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2020.1772974","usgsCitation":"Mohammed-Ali, W., Mendoza, C., and Holmes, R.R., 2020, Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA): Hydrological Sciences Journal, v. 65, no. 10, p. 1784-1793, https://doi.org/10.1080/02626667.2020.1772974.","productDescription":"10 p.","startPage":"1784","endPage":"1793","ipdsId":"IP-110034","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Lower Osage River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.7081298828125,\n 38.13887716726548\n ],\n [\n -92.1697998046875,\n 38.13887716726548\n ],\n [\n -92.1697998046875,\n 38.302869955150044\n ],\n [\n -92.7081298828125,\n 38.302869955150044\n ],\n [\n -92.7081298828125,\n 38.13887716726548\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Mohammed-Ali, Wesam","contributorId":225556,"corporation":false,"usgs":false,"family":"Mohammed-Ali","given":"Wesam","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":792383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Cesar","contributorId":225557,"corporation":false,"usgs":false,"family":"Mendoza","given":"Cesar","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":792384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmes, Robert R. Jr. 0000-0002-5060-3999 bholmes@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":1624,"corporation":false,"usgs":true,"family":"Holmes","given":"Robert","suffix":"Jr.","email":"bholmes@usgs.gov","middleInitial":"R.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":793358,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224298,"text":"70224298 - 2020 - Assessment of fire fuel load dynamics in shrubland ecosystems in the western United States using MODIS products","interactions":[],"lastModifiedDate":"2021-09-21T13:14:01.451306","indexId":"70224298","displayToPublicDate":"2020-06-12T08:11:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of fire fuel load dynamics in shrubland ecosystems in the western United States using MODIS products","docAbstract":"Kodiak Island in southern Alaska is one of the premier examples globally for the study of forearc magmatism. This location contains two Paleocene intrusive belts that formed due to the subduction of a migrating spreading ridge and slab-window: the Kodiak batholith and the trenchward magmatic belt. These magmatic rocks are part of the Sanak-Baranof belt, which extends for greater than 2,100 km along the southern Alaskan margin and vary in age from 61 to 50 Ma west to east.
Trenchward-belt rocks, with an 40Ar/39Ar age of 60.2±0.9 Ma, intrude into the Paleocene Ghost Rocks Formation and are composed of granitoids, basaltic dikes, and small gabbroic plutons that lie along or southward of the Kalsin Bay Fault. Such intrusions were emplaced at shallow levels and have abundant evidence of incomplete intermingling of basaltic and granitic magmas. These textures indicate trenchward-belt intrusions that froze before complete assimilation, leaving behind features such as abundant locally stoped blocks, gabbroic pods within granitic intrusions, and microstructural evidence such as strongly embayed olivine and pyroxene phenocrysts in granitoid bodies.
The Kodiak batholith and satellite intrusions extend for over 110 km along the axis of Kodiak Island and vary in width from 2 to 6 km. These intrude into the Late Cretaceous Kodiak Formation. U-Pb ages on zircon from the intrusions range from 59.2±0.2 Ma in the southwest to 58.4±0.2 Ma near its northwest tip. We interpret these ages as tracking the location of a migrating triple junction and associated slab-window. The batholith is composed of granite and granodiorite, with lesser amounts of tonalite and diorite. The center of the Kodiak batholith contains high-inclusion zones with abundant residual host rock fragments that were carried up from 5–10 km below current exposure levels. These high-inclusion zones contain biotite aggregates, pure quartz clots, and large xenocrysts of sillimanite, kyanite, andalusite, and garnet. This is a higher-pressure mineral assemblage than exists in the batholith metamorphic aureole. Gravity observations and modeling are consistent with the high-inclusion zones extending downward for 5–10 km. The Kodiak batholith results from a migrating triple junction and slab-window that led to high degrees of partial melting within the Kodiak accretionary prism.
Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Invasive predatory lake trout Salvelinus namaycush were discovered in Yellowstone Lake in 1994 and caused a precipitous decrease in abundance of native Yellowstone cutthroat trout Oncorhynchus clarkii bouvieri. Suppression efforts (primarily gillnetting) initiated in 1995 did not curtail lake trout population growth or lakewide expansion. An adaptive management strategy was developed in 2010 that specified desired conditions indicative of ecosystem recovery. Population modeling was used to estimate effects of suppression efforts on the lake trout and establish effort benchmarks to achieve negative population growth (λ < 1). Partnerships enhanced funding support, and a scientific review panel provided guidance to increase suppression gillnetting effort to >46,800 100-m net nights; this effort level was achieved in 2012 and led to a reduction in lake trout biomass. Total lake trout biomass declined from 432,017 kg in 2012 to 196,675 kg in 2019, primarily because of a 79% reduction in adults. Total abundance declined from 925,208 in 2012 to 673,983 in 2019 but was highly variable because of recruitment of age-2 fish. Overall, 3.35 million lake trout were killed by suppression efforts from 1995 to 2019. Cutthroat trout abundance remained below target levels, but relative condition increased, large individuals (> 400 mm) became more abundant, and individual weights doubled, probably because of reduced density. Continued actions to suppress lake trout will facilitate further recovery of the cutthroat trout population and integrity of the Yellowstone Lake ecosystem.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes5020018","usgsCitation":"Koel, T., Arnold, J.L., Bigelow, P., Brenden, T.O., Davis, J.D., Detjens, C.R., Doepke, P., Ertel, B.D., Glassic, H., Gresswell, R.E., Guy, C., MacDonald, D.J., Ruhl, M.E., Stuth, T.J., Sweet, D.P., Syslo, J.M., Thomas, N.A., Tronstad, L., White, P.J., and Zale, A.V., 2020, Yellowstone Lake ecosystem restoration: A case study for invasive fish management: Fishes, v. 5, no. 2, 18, 63 p., https://doi.org/10.3390/fishes5020018.","productDescription":"18, 63 p.","ipdsId":"IP-118729","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":456433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes5020018","text":"Publisher Index Page"},{"id":396739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.9619140625,\n 44.01652134387754\n ],\n [\n -109.6875,\n 44.01652134387754\n ],\n [\n -109.6875,\n 44.95702412512118\n ],\n [\n -110.9619140625,\n 44.95702412512118\n ],\n [\n -110.9619140625,\n 44.01652134387754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Koel, Todd M.","contributorId":272054,"corporation":false,"usgs":false,"family":"Koel","given":"Todd M.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Jeffrey L.","contributorId":278609,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bigelow, Patricia E.","contributorId":276048,"corporation":false,"usgs":false,"family":"Bigelow","given":"Patricia E.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenden, Travis O.","contributorId":126759,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis","email":"","middleInitial":"O.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":837116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Jeffery D.","contributorId":287835,"corporation":false,"usgs":false,"family":"Davis","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":837117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Detjens, Colleen R.","contributorId":270712,"corporation":false,"usgs":false,"family":"Detjens","given":"Colleen","email":"","middleInitial":"R.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Doepke, Philip D.","contributorId":278610,"corporation":false,"usgs":false,"family":"Doepke","given":"Philip 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Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":837184,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Guy, Christopher S","contributorId":120991,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher S","affiliations":[],"preferred":false,"id":837185,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"MacDonald, Drew J.","contributorId":270660,"corporation":false,"usgs":false,"family":"MacDonald","given":"Drew","email":"","middleInitial":"J.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837186,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ruhl, Michael E.","contributorId":287915,"corporation":false,"usgs":false,"family":"Ruhl","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837187,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stuth, Todd J.","contributorId":287916,"corporation":false,"usgs":false,"family":"Stuth","given":"Todd","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837188,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sweet, David P.","contributorId":287917,"corporation":false,"usgs":false,"family":"Sweet","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":837189,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Syslo, John M.","contributorId":276045,"corporation":false,"usgs":false,"family":"Syslo","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":837190,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Thomas, Nathan A.","contributorId":270658,"corporation":false,"usgs":false,"family":"Thomas","given":"Nathan","email":"","middleInitial":"A.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":837191,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":837192,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"White, Patrick J.","contributorId":169530,"corporation":false,"usgs":false,"family":"White","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":837193,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837194,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70210608,"text":"70210608 - 2020 - Increased drought severity tracks warming in the United States’ largest river basin","interactions":[],"lastModifiedDate":"2020-09-18T14:53:21.021876","indexId":"70210608","displayToPublicDate":"2020-06-11T13:03:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Increased drought severity tracks warming in the United States’ largest river basin","docAbstract":"Across the Upper Missouri River Basin, the recent drought of 2000 to 2010, known as the “turn-of-the-century drought,” was likely more severe than any in the instrumental record including the Dust Bowl drought. However, until now, adequate proxy records needed to better understand this event with regard to long-term variability have been lacking. Here we examine 1,200 y of streamflow from a network of 17 new tree-ring–based reconstructions for gages across the upper Missouri basin and an independent reconstruction of warm-season regional temperature in order to place the recent drought in a long-term climate context. We find that temperature has increasingly influenced the severity of drought events by decreasing runoff efficiency in the basin since the late 20th century (1980s) onward. The occurrence of extreme heat, higher evapotranspiration, and associated low-flow conditions across the basin has increased substantially over the 20th and 21st centuries, and recent warming aligns with increasing drought severities that rival or exceed any estimated over the last 12 centuries. Future warming is anticipated to cause increasingly severe droughts by enhancing water deficits that could prove challenging for water management.","language":"English","publisher":"Proceedings of the National Academies of Science","doi":"10.1073/pnas.1916208117","usgsCitation":"Martin, J.T., Pederson, G.T., Woodhouse, C.A., Cook, E.R., McCabe, G.J., Anchukaitis, K.J., Wise, E.K., Erger, P., Dolan, L.S., McGuire, M., Gangopadhyay, S., Chase, K.J., Littell, J., Gray, S., St. George, S., Friedman, J.M., Sauchyn, D.J., St. Jacques, J., and King, J., 2020, Increased drought severity tracks warming in the United States’ largest river basin: PNAS, v. 117, no. 21, p. 11328-11336, https://doi.org/10.1073/pnas.1916208117.","productDescription":"9 p.","startPage":"11328","endPage":"11336","ipdsId":"IP-102315","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and 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Center","active":true,"usgs":true}],"preferred":true,"id":790805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":790806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":790807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Edward R.","contributorId":225235,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","email":"","middleInitial":"R.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":790808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":790809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anchukaitis, Kevin J.","contributorId":195005,"corporation":false,"usgs":false,"family":"Anchukaitis","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":790810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wise, Erika K.","contributorId":202071,"corporation":false,"usgs":false,"family":"Wise","given":"Erika","email":"","middleInitial":"K.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":790811,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erger, Patrick","contributorId":218753,"corporation":false,"usgs":false,"family":"Erger","given":"Patrick","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of 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0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":790814,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":790815,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":790816,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":790817,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"St. George, Scott","contributorId":218756,"corporation":false,"usgs":false,"family":"St. George","given":"Scott","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":790818,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790819,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sauchyn, David J.","contributorId":218758,"corporation":false,"usgs":false,"family":"Sauchyn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":790820,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"St. Jacques, Jeannine-Marie","contributorId":195063,"corporation":false,"usgs":false,"family":"St. Jacques","given":"Jeannine-Marie","affiliations":[],"preferred":false,"id":790821,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"King, John C.","contributorId":225237,"corporation":false,"usgs":false,"family":"King","given":"John C.","affiliations":[{"id":41082,"text":"Lone Pine Research","active":true,"usgs":false}],"preferred":false,"id":790822,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70210607,"text":"ofr20201064 - 2020 - Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report","interactions":[],"lastModifiedDate":"2020-06-12T16:03:59.858553","indexId":"ofr20201064","displayToPublicDate":"2020-06-11T13:00:59","publicationYear":"2020","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":"2020-1064","displayTitle":"Juvenile Lost River and Shortnose Sucker Year-Class Formation, Survival, and Growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 Monitoring Report","title":"Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report","docAbstract":"Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth; (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake. The U.S. Geological Survey monitoring program, which began in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Juvenile sucker year-class strength and apparent survival were low in 2018 in Upper Klamath Lake. Most juvenile sucker mortality occurs within the first year of life. The Upper Klamath Lake year-class strength indices for Lost River and shortnose suckers in 2018 were the lowest they had been since the start of monitoring in 2015. The annual catch rates of shortnose sucker remained consistently low, whereas Lost River sucker catch rates varied. The capture of only four age-1 and older suckers from Upper Klamath Lake during the 2018 sampling season indicated low annual survival of the 2017 cohort.
Annual production indices of juvenile suckers in Clear Lake are highly variable and potentially affected by seasonal connections to spawning habitat in Willow Creek. A total of seven age-0 shortnose or Klamath largescale suckers (Catostomus snyderi) were captured from Clear Lake in 2018, which was a relatively wet year, indicating that a small cohort was formed or that there was a delay in the recruitment of age-0 suckers. The 2018 sampling continued to detect recruitment of juveniles from the 2015 cohort to the lake. Given the dysconnectivity between Willow Creek and Clear Lake during the 2015 spawning season, the continued recruitment of young fish of this cohort to the lake may be attributed to reproduction by resident suckers in Willow Creek. Suckers younger than age-3 in Clear Lake could be identified as either shortnose or Klamath largescale suckers. A stream resident life history, if it were occurring, is consistent with these fish being Klamath largescale suckers. Survival of all distinguishable taxa of juvenile suckers is much higher in Clear Lake than in Upper Klamath Lake, with non-trivial numbers of suckers surviving to join spawning aggregations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2020, Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report: U.S. Geological Survey Open-File Report 2020–1064, 33 p., https://doi.org/10.3133/ofr20201064.","productDescription":"vi, 33 p.","onlineOnly":"Y","ipdsId":"IP-116680","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375530,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1064/ofr20201064.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1064"},{"id":375529,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1064/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Clear Lake Reservoir, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25747680664064,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.789744876718984\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1075439453125,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.224449701009725\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
We test the hypothesis that ocean seafloor pressures impart stresses that alter the initiation or termination of transient slow slip events (SSEs) on shallow submarine and near-coastal faults, using simulated seafloor pressures and a new catalog of SSEs in the Hikurangi subduction zone. We show that seafloor pressures may be represented by an average time history over the ~100-km dimensions of the study area. We account for SSE uncertainties and the multiplicity of processes that affect SSEs statistically by estimating the probabilities of rejecting the null hypothesis that SSE initiation or termination pressures are those to be expected by chance sampling of known (modeled) seafloor pressures, with low probabilities indicating some causal connection. No impact of ocean pressure changes on SSE initiation is detectable, but a correlation with their terminations is suggested. SSE slip that weakens the fault and makes it more sensitive to small stress changes may explain results.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL087273","usgsCitation":"Gomberg, J.S., Baxter, P.J., Smith, E.G., Ariyoshi, K., and Chiswell, S., 2020, The ocean's impact on slow slip events: Geophysical Research Letters, v. 47, no. 14, e2020GL087273, 15 p., https://doi.org/10.1029/2020GL087273.","productDescription":"e2020GL087273, 15 p.","ipdsId":"IP-115199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499853,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/ffe5bbfe0ddb4ed785934362b7777064","text":"External Repository"},{"id":480845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 177.28639581617597,\n -38.17149200548941\n ],\n [\n 177.28639581617597,\n -40.523586910552204\n ],\n [\n 180.53561304652231,\n -40.523586910552204\n ],\n [\n 180.53561304652231,\n -38.17149200548941\n ],\n [\n 177.28639581617597,\n -38.17149200548941\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baxter, Peter J.","contributorId":201839,"corporation":false,"usgs":false,"family":"Baxter","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":924648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Euan G. C.","contributorId":194943,"corporation":false,"usgs":false,"family":"Smith","given":"Euan","email":"","middleInitial":"G. C.","affiliations":[],"preferred":false,"id":924649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ariyoshi, Keisuke","contributorId":349718,"corporation":false,"usgs":false,"family":"Ariyoshi","given":"Keisuke","affiliations":[{"id":40272,"text":"Japan Agency for Marine-Earth Science and Technology","active":true,"usgs":false}],"preferred":false,"id":924650,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiswell, Steve","contributorId":242932,"corporation":false,"usgs":false,"family":"Chiswell","given":"Steve","email":"","affiliations":[{"id":48587,"text":"National Institute of Water & Atmospheric Research Ltd","active":true,"usgs":false}],"preferred":false,"id":924651,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227037,"text":"70227037 - 2020 - Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate","interactions":[],"lastModifiedDate":"2021-12-28T15:37:37.953059","indexId":"70227037","displayToPublicDate":"2020-06-11T09:34:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate","docAbstract":"To increase resource gain, many herbivores pace their migration with the flush of nutritious plant green-up that progresses across the landscape (termed “green-wave surfing”). Despite concerns about the effects of climate change on migratory species and the critical role of plant phenology in mediating the ability of ungulates to surf, little is known about how drought shapes the green wave and influences the foraging benefits of migration. With a 19 year dataset on drought and plant phenology across 99 unique migratory routes of mule deer (Odocoileus hemionus) in western Wyoming, United States, we show that drought shortened the duration of spring green-up by approximately twofold (2.5 weeks) and resulted in less sequential green-up along migratory routes. We investigated the possibility that some routes were buffered from the effects of drought (i.e., routes that maintained long green-up duration irrespective of drought intensity). We found no evidence of drought-buffered routes. Instead, routes with the longest green-up in non-drought years also were the most affected by drought. Despite phenological changes along the migratory route, mule deer closely followed drought-altered green waves during migration. Migrating deer did not experience a trophic mismatch with the green wave during drought. Instead, the shorter window of green-up caused by drought reduced the opportunity to accumulate forage resources during rapid spring migrations. Our work highlights the synchronization of phenological events as an important mechanism by which climate change can negatively affect migratory species by reducing the temporal availability of key food resources. For migratory herbivores, climate change poses a new and growing threat by altering resource phenology and diminishing the foraging benefit of migration.
Heterospecific breeding associations may benefit individuals by mitigating predation risk but may also create costs if they increase competition for resources or are more easily detectable by predators. Our understanding of the interactions among hetero‐ and conspecifics is often lacking in mixed species colonies. Here, we test how the presence of hetero‐ and conspecifics influence nest and chick survival for two listed (under the U.S. Endangered Species Act) migratory species breeding on the Missouri River, USA. We monitored 2507 piping plover Charadrius melodus nests and 3245 chicks as well as 1060 least tern Sternula antillarum nests and 1374 chicks on Lake Sakakawea, the Garrison River Reach and the Gavins Point Reach for varying years between 2007 and 2016. Piping plover nest and chick survival improved with the presence and abundance of least terns, but least terns only benefited from piping plover presence for certain study areas and breeding stages. Piping plover nest survival was also improved by the presence and abundance of conspecifics on the Garrison River Reach and was negatively influenced by conspecific presence on Lake Sakakawea. Least tern chick survival improved with the presence of other least terns only on the Gavins Point Reach. Ultimately, the heterospecific breeding association between plovers and terns is mutualistic but asymmetric and is moderated by habitat, abundance of conspecifics and breeding stage. Our results highlight that spatiotemporal variation in the interactions among individuals breeding in groups precludes simple generalizations and suggests that management focused on one species may restrict benefits to that focal species if nest site requirements for heterospecifics are not also included.
Federal mandates and U.S. Geological Survey (USGS, also known as the Bureau) Fundamental Science Practices (FSP) policies require that publicly funded scientific data, publications, and derivative works be openly accessible to researchers and the public. Open access helps to leverage the public investment by making the acquired data and published information products—collectively referred to as “data assets”—easier to locate, reproduce, and reuse. Open access also provides transparency to the processes used to acquire and analyze the data, thereby helping to ensure the scientific integrity of USGS data and products.
The data assets produced by USGS programs, science centers, and projects are preserved digitally in various USGS and non-USGS repositories. To capitalize on the investment expended for data collection, analysis, and interpretation, these systems must remain useful and meaningful. For USGS repositories, the Bureau FSP Advisory Committee has implemented an evaluation process to ensure that the systems being used to preserve these data assets are trustworthy, reliable, and secure and thus provide for data longevity, integrity, and security. A system that is found to meet the reliability and suitability requirements is certified as a USGS Trusted Digital Repository.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203032","usgsCitation":"Latysh, N., Kirk, K.G., and Faundeen, J., 2020, Purpose and benefits of U.S. Geological Survey Trusted Digital Repositories: U.S. Geological Survey Fact Sheet 2020–3032, 4 p., https://doi.org/10.3133/fs20203032.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-108444","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":375487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3032/fs20203032.pdf","text":"Report","size":"453 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3032"},{"id":375486,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3032/coverthb.jpg"}],"contact":"Office of Science Quality and Integrity
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.
use changes in one location carry through to other areas due to species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different than other contribution metrics as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences ordering of node contribution. We find that habitats through which all migrants flow are the most important to short-term network growth under complete-removal scenarios. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.
","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/709009","usgsCitation":"Sample, C., Bieri, J., Allen, B.L., Dementieva, Y., Carson, A., Higgins, C., Piatt, S., Qiu, S., Stafford, S., Mattsson, B., Semmens, D., Diffendorfer, J., and Thogmartin, W.E., 2020, Quantifying the contribution of habitats and pathways to a spatially structured population facing environmental change: American Naturalist, v. 196, no. 2, p. 157-168, https://doi.org/10.1086/709009.","productDescription":"12 p.","startPage":"157","endPage":"168","ipdsId":"IP-110963","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":456440,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/709009","text":"Publisher Index Page"},{"id":377324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"196","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sample, Christine","contributorId":201597,"corporation":false,"usgs":false,"family":"Sample","given":"Christine","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bieri, Joanna A.","contributorId":201599,"corporation":false,"usgs":false,"family":"Bieri","given":"Joanna A.","affiliations":[{"id":36213,"text":"University of Redlands","active":true,"usgs":false}],"preferred":false,"id":795677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Benjamin L.","contributorId":193210,"corporation":false,"usgs":false,"family":"Allen","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":795678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dementieva, Yulia","contributorId":219841,"corporation":false,"usgs":false,"family":"Dementieva","given":"Yulia","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carson, Alyssa","contributorId":219842,"corporation":false,"usgs":false,"family":"Carson","given":"Alyssa","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Higgins, Connor","contributorId":237967,"corporation":false,"usgs":false,"family":"Higgins","given":"Connor","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Piatt, Sadie","contributorId":219844,"corporation":false,"usgs":false,"family":"Piatt","given":"Sadie","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795682,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Qiu, Shirley","contributorId":219845,"corporation":false,"usgs":false,"family":"Qiu","given":"Shirley","email":"","affiliations":[{"id":35881,"text":"Emmanuel College","active":true,"usgs":false}],"preferred":false,"id":795683,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stafford, Summer","contributorId":219846,"corporation":false,"usgs":false,"family":"Stafford","given":"Summer","email":"","affiliations":[{"id":36213,"text":"University of Redlands","active":true,"usgs":false}],"preferred":false,"id":795684,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mattsson, Brady J.","contributorId":171612,"corporation":false,"usgs":false,"family":"Mattsson","given":"Brady J.","affiliations":[{"id":26928,"text":"Univ. of Vienna","active":true,"usgs":false}],"preferred":false,"id":795685,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":795686,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":795687,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":795688,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70210940,"text":"70210940 - 2020 - Geochronologic and Hf-isotope framework of Proterozoic rocks from central New Mexico, USA: Formation of the Mazatzal crustal province in an extended continental margin arc","interactions":[],"lastModifiedDate":"2020-07-08T15:58:01.581242","indexId":"70210940","displayToPublicDate":"2020-06-11T08:52:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Geochronologic and Hf-isotope framework of Proterozoic rocks from central New Mexico, USA: Formation of the Mazatzal crustal province in an extended continental margin arc","docAbstract":"The growth of southern Laurentia has been attributed to the accretion of juvenile arc terranes during the successive 1.74-1.68 Ga Yavapai and 1.65-1.60 Ga Mazatzal orogenies. However, in light of the increasing importance of the ca. 1.49-1.40 Ga Mesoproterozoic Picuris orogeny, the tectonic setting in which the Mazatzal crustal province and its distinctive quartzite-rhyolite successions were generated needs additional examination. The Sandia-Manzano-Los Pinos uplift in central New Mexico is an ideal place to characterize the tectonic history of the Mazatzal crustal province. A comprehensive geochronologic and Hf-isotopic dataset for Proterozoic rocks of the Sandia-Manzano-Los Pinos uplift is presented. Plutonic and metavolcanic rocks in the Sandia-Manzano-Los Pinos uplift were emplaced in three pulses at 1668-1655 Ma, 1587 Ma, and 1459-1453 Ma. Hf-isotope data from the Paleoproterozoic plutonic rocks are juvenile, with both leucogranite and arc-related granodiorite yielding εHf(t) values ranging from +6 to +12, compared to the coeval depleted mantle value of +10 at ca. 1.65 Ga. Inherited zircon in Paleoproterozoic rocks suggest that crust older than 1.7 Ga was involved in their genesis. Hf-isotope data from Mesoproterozoic plutonic rocks in the Sandia-Manzano-Los Pinos uplift are consistent with derivation from 1.7-1.6 Ga lithosphere. Detrital zircon indicate that metasedimentary rocks of the lower Manzano Group were derived primarily from local sources that have U-Pb-Hf isotope compositions similar to the plutonic rocks which intrude and volcanic rocks that underlie the Manzano Group. The detrital zircon provenance of the Manzano Group broadens up-section from unimodal populations with age peaks at ca. 1.65 Ga to include 1.7-3.0 Ga detrital zircon derived from older Laurentian sources like the Yavapai and Mojave provinces. We offer a new model for the formation of the Mazatzal crustal province of New Mexico as a continental margin arc built on top of the previously assembled Yavapai province. The Manzano Group quartzite-rhyolite succession was formed by lithospheric extension above a north-dipping, southward retreating subduction zone. The Manzano Group was then subjected to ca. 1.65 Ga syn-magmatic tectonism and later intracratonic contractional tectonism, likely during the 1.46-1.40 Ga Picuris orogeny.","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2020.105820","usgsCitation":"Holland, M.E., Grambling, T.A., Karlstrom, K.E., Jones, J.V., Nagotko, K.N., and Daniel, C.G., 2020, Geochronologic and Hf-isotope framework of Proterozoic rocks from central New Mexico, USA: Formation of the Mazatzal crustal province in an extended continental margin arc: Precambrian Research, v. 347, 105820, 19 p., https://doi.org/10.1016/j.precamres.2020.105820.","productDescription":"105820, 19 p.","ipdsId":"IP-119090","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":436934,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U0P2ZY","text":"USGS data release","linkHelpText":"U-Pb Isotopic Data and Ages of Zircon from the Manzano Mountains, New Mexico"},{"id":376146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.45703125,\n 32.52828936482526\n ],\n [\n -103.46923828124999,\n 32.52828936482526\n ],\n [\n -103.46923828124999,\n 36.38591277287651\n ],\n [\n -108.45703125,\n 36.38591277287651\n ],\n [\n -108.45703125,\n 32.52828936482526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"347","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Holland, Mark E.","contributorId":228842,"corporation":false,"usgs":false,"family":"Holland","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":792239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grambling, Tyler A.","contributorId":228843,"corporation":false,"usgs":false,"family":"Grambling","given":"Tyler","email":"","middleInitial":"A.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":792240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karlstrom, Karl E.","contributorId":228844,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","email":"","middleInitial":"E.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":792241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":792242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nagotko, Kimberly N.","contributorId":228845,"corporation":false,"usgs":false,"family":"Nagotko","given":"Kimberly","email":"","middleInitial":"N.","affiliations":[{"id":16651,"text":"Bucknell University","active":true,"usgs":false}],"preferred":false,"id":792243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daniel, Christopher G.","contributorId":195246,"corporation":false,"usgs":false,"family":"Daniel","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":792244,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211001,"text":"70211001 - 2020 - Potential for recreational restrictions to reduce grizzly bear–caused human injuries","interactions":[],"lastModifiedDate":"2020-07-10T13:22:30.718297","indexId":"70211001","displayToPublicDate":"2020-06-11T08:20:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Potential for recreational restrictions to reduce grizzly bear–caused human injuries","docAbstract":"In 2011, 2 hikers were killed by grizzly bears (Ursus arctos) in separate incidents on backcountry trails in Hayden Valley, Yellowstone National Park, USA (YNP). Hayden Valley provides prime habitat for grizzly bears and is known to have high densities of bears. During 1970–2017, 23% (10 of 44) of all backcountry grizzly bear–inflicted human injuries and fatalities in YNP occurred in the valley even though it comprises only 1% of the park. In addition, 3 of the last 5 fatal bear attacks in the park occurred in the valley. We evaluated retrospectively whether restrictions and closures on visitor recreational activity would have prevented many of these injuries. We considered prohibitions on recreational activity during seasons when bears forage for specific high-quality foods; potential closures that coincided with the times of day and year bears were most active in the valley; and visitor use restrictions that would have prevented the most common human behaviors associated with grizzly bear–caused human injuries. The food-based closure that may have prevented the most human injuries occurred during middle to late summer when bears scavenge bison (Bison bison) carcasses that result from annual rutting behavior of bison in the valley. However, safety precautions such as hiking in groups of >=3, remaining on maintained trails, and carrying bear spray would likely reduce the frequency of bear-inflicted human injuries more than most food-based seasonal closures. Our analyses provide broadly applicable findings regarding use of visitor behavior restrictions and seasonal closures to reduce the risk of bear-inflicted human injuries.","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSUS-D-18-0005.1","usgsCitation":"Gunther, K.A., and Haroldson, M.A., 2020, Potential for recreational restrictions to reduce grizzly bear–caused human injuries: Ursus, v. 2020, 31e6, 17 p., https://doi.org/10.2192/URSUS-D-18-0005.1.","productDescription":"31e6, 17 p.","ipdsId":"IP-095139","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":456442,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-18-0005.1","text":"Publisher Index Page"},{"id":376248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.05529785156249,\n 43.67581809328341\n ],\n [\n -109.2041015625,\n 43.67581809328341\n ],\n [\n -109.2041015625,\n 45.00365115687186\n ],\n [\n -111.05529785156249,\n 45.00365115687186\n ],\n [\n -111.05529785156249,\n 43.67581809328341\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2020","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":792393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":792394,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211023,"text":"70211023 - 2020 - Land use effects on sediment nutrient processes in a heavily modified watershed using structural equation models","interactions":[],"lastModifiedDate":"2020-07-10T13:10:51.180487","indexId":"70211023","displayToPublicDate":"2020-06-11T08:07:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Land use effects on sediment nutrient processes in a heavily modified watershed using structural equation models","docAbstract":"Contemporary land use can affect sediment nutrient processes in rivers draining heavily modified watersheds; however, studies linking land use to sediment nutrient processes in large river networks are limited. In this study, we developed and evaluated structural equation models (SE models) for denitrification and phosphorus retention capacity to determine direct and indirect linkages between current land use and sediment nutrient processes during baseflow in the Fox River watershed, Wisconsin USA. A large spatial-scale dataset used for this study included sediment nitrogen and phosphorus retention measurements and land use information for 106 sites. The SE models for the Fox River watershed identified direct links between current land use and in-stream sediment nutrient processes. Sub-watersheds with agricultural land consisting of more natural land cover had lower surface water nitrate concentrations and higher denitrification enzyme activity than sub-watersheds with less alternative cover. This suggests that best management practices implemented in the Fox River watershed that restore natural land cover can improve water quality through nitrogen removal on the agricultural landscape and in the river network. Best management practices are not having the same measurable affect on phosphorus in the river network, most likely due to legacy phosphorus stored in the sediment.","language":"English","publisher":"Wiley","doi":"10.1029/2019WR026655","usgsCitation":"Kreiling, R.M., Thoms, M.C., Bartsch, L., Larson, J.H., and Christensen, V., 2020, Land use effects on sediment nutrient processes in a heavily modified watershed using structural equation models: Water Resources Research, v. 56, no. 7, e2019WR026655, 17 p., https://doi.org/10.1029/2019WR026655.","productDescription":"e2019WR026655, 17 p.","ipdsId":"IP-108469","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":376246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fox River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.95654296875,\n 44.61393394730626\n ],\n [\n -88.5498046875,\n 44.692088041727786\n ],\n [\n -88.26416015625001,\n 45.166547157856016\n ],\n [\n -88.714599609375,\n 45.62940492064498\n ],\n [\n -89.241943359375,\n 45.96642454131025\n ],\n [\n -89.8681640625,\n 45.706179285330855\n ],\n [\n -89.95605468750001,\n 44.95702412512118\n ],\n [\n -89.5166015625,\n 44.41808794374846\n ],\n [\n -89.439697265625,\n 43.929549935614574\n ],\n [\n -89.52758789062501,\n 43.57243174740972\n ],\n [\n -89.351806640625,\n 43.37311218381999\n ],\n [\n -88.93432617187501,\n 43.31718491566708\n ],\n [\n -88.53881835937499,\n 43.36512572875844\n ],\n [\n -88.11035156249999,\n 43.45291889355465\n ],\n [\n -87.82470703125,\n 44.134913443750726\n ],\n [\n -87.53906250000001,\n 44.574817404670306\n ],\n [\n -87.659912109375,\n 44.62957319195102\n ],\n [\n -87.879638671875,\n 44.527842798455474\n ],\n [\n -87.95654296875,\n 44.61393394730626\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-07-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thoms, Martin C. 0000-0002-8074-0476","orcid":"https://orcid.org/0000-0002-8074-0476","contributorId":145710,"corporation":false,"usgs":false,"family":"Thoms","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":16205,"text":"Riverine Landscapes Research Laboratory, University of New England, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":792461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartsch, Lynn A. 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":149360,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn A.","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":792463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792464,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211894,"text":"70211894 - 2020 - A non-linear relationship between marsh size and sediment trapping capacity compromises salt marshes’ resilience to sea-level rise","interactions":[],"lastModifiedDate":"2020-09-23T15:56:59.9984","indexId":"70211894","displayToPublicDate":"2020-06-10T08:24:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"A non-linear relationship between marsh size and sediment trapping capacity compromises salt marshes’ resilience to sea-level rise","docAbstract":"Global assessments predict the impact of sea-level rise on salt marshes with present-day levels of sediment supply from rivers and the coastal ocean. However, these assessments do not consider that variations in marsh extent and the related reconfiguration of intertidal area affect local sediment dynamics, ultimately controlling the fate of the marshes themselves. We conducted a meta-analysis of six bays along the United States East Coast to show that a reduction in the current salt marsh area decreases the sediment availability in estuarine systems through changes in regional-scale hydrodynamics. This positive feedback between marsh disappearance and the ability of coastal bays to retain sediments reduces the trapping capacity of the whole tidal system and jeopardizes the survival of the remaining marshes. We show that on marsh platforms, the sediment deposition per unit area decreases exponentially with marsh loss. Marsh erosion enlarges tidal prism values and enhances the tendency toward ebb dominance, thus decreasing the overall sediment availability of the system. Our findings highlight that marsh deterioration reduces the sediment stock in back-barrier basins and therefore compromises the resilience of salt marshes.
Submarine landslides caused by strong ground shaking during the M9.2 1964 Great Alaska earthquake generated a tsunami that destroyed much of the old town of Valdez, Alaska, and was responsible for 32 deaths at that location. We explore structural details of the 1964 landslide deposit, as well as landslide deposits from earlier events, in order to characterize kinematics of the landslide process. We present a new high‐resolution seismic reflection data set that images the 1964 landslide deposit and six pre‐1964 deposits with great detail. These deposits are represented by thick packages (~7–23 m) of debris within >500 m of fjord sedimentation above basement. Internal slide structures are associated with distinctive landslide failure mechanisms, including detailed erosional and depositional features and structures resolved within both landslide blocks and distal debris flow layers. Based on comparisons of deposit volume from subbottom structure and differenced bathymetry, we refine prior interpretations of the source of failed material. New data show evidence for basal erosion and reworking of fjord‐floor sedimentation. Additionally, material comprising the 1964 landslide appears to have been translated and deformed by lateral thrusting, rather than having been sourced entirely from upslope evacuation zones. Taking into account these complexities in depositional patterns, we show variations in slide size through Holocene time and relate the history of landslides to the paleoseismic record. Collectively, these new observations demonstrate that Port Valdez has a repeated history of large submarine landslides, which are likely associated with large megathrust earthquakes.
We observed cannibalism, the act of consuming a conspecific, of eggs and nestlings by Common Ravens (Corvus corax; hereafter “raven”) by video-monitoring nests in Nevada and California. Specifically, within the sagebrush steppe of Nevada, adult ravens killed and consumed raven chicks from an active nest. Additionally, on the coast of California, we observed adult ravens consume inviable eggs from their own nest following full-term incubation. To our knowledge, these observations represent the first documented cannibalistic behavior by ravens.
Geomagnetically induced currents (GICs) are quasi-direct current (DC) electric currents that flow in technological conductors during geomagnetic storms. Extreme GICs are hazardous to man-made infrastructure. GICs enter and exit the technological systems, such as the electric power grid, at grounding points, and their magnitudes depend on the currents that flow underground. They are, therefore, a function of the Earth's electrical conductivity, represented at ground level as Earth impedances, as well as the resistance parameters of the power network. Traditional GIC estimation practices are based on Earth impedances obtained from laterally homogeneous or piecewise layered-Earth models. We refer to these methods, collectively, as the 1-D approximation. However, GIC hazard mitigation can be improved with more accurate GIC modeling that takes the spatially heterogeneous Earth's conductivity into account. Here, we propose a modified approximation for GIC estimation that is very similar to the 1-D approximation but is instead derived from empirical 3-D Earth impedances. Our formulation sets up the computation of static, frequency-dependent power line telluric response functions, which, once computed, may be considered part of the power grid system model. These response functions may then be used for historical scenario analysis of GIC hazards and for simplified real-time, albeit approximate, GIC estimation in a power grid. This modest modification to the simpler local field formulation approach avoids real-time integration of geoelectric fields along power lines while taking the realistic 3-D Earth into account in a rigorous manner. Once implemented, the method provides a power grid operator with the benefits of convenience and computational speed for a first look real-time operational GIC hazard assessment. We estimate that the proposed modified 3-D GIC modeling approach produces GIC values that are well within 50% of those obtained with the full-scale power line integration of spatially variable geoelectric fields, for storms comparable in scale to the 2003 Halloween storm, all geological structures, and power lines located in the contiguous United States and other low- to middle-latitude regions.
A microstructural and thermochronometric analysis of the Coyote Mountains detachment shear zone provides new insight into the collapse of the southern North American Cordillera. The Coyote Mountains is a metamorphic core complex that makes up the northern end of the Baboquivari Mountains in southern Arizona. The Baboquivari Mountains records several episodes of crustal shortening and thickening and regional metamorphism, including the Late Cretaceous‐early Paleogene Laramide orogeny which is locally expressed by the Baboquivari thrust fault. Thrusting and shortening were accompanied by magmatic activity recorded by intrusion of Paleocene muscovite‐biotite‐garnet peraluminous granites such as the ~58 Ma Pan Tak Granite, interpreted as anatectic melts representing the culmination of the Laramide orogeny. Following Laramide crustal shortening, the northern end of the Baboquivari Mountains was exhumed along a top‐to‐the‐north detachment shear zone, which resulted in the formation of the Coyote Mountains metamorphic core complex. Structural and microstructural analysis show that the detachment shear zone evolved under a strong component of noncoaxial (simple shear) deformation, at deformation conditions of ~450 ± 50°C, under a differential stress of ~60 MPa, and a strain rate of 1.5 × 10−11 to 5.0 × 10−13 s−1 at depth of ~11–14 km. Detailed 40Ar/39Ar geochronology of biotite and muscovite, in the context of the deformation conditions determined by quartz microstructures, suggests that the mylonitization associated with the formation of the Coyote Mountains metamorphic core complex started at ~29 Ma (early Oligocene). Apatite fission track ages indicate that the footwall of the Coyote Mountains metamorphic core complex experienced rapid exhumation to the upper crust by ~24 Ma. The fact that mylonitization and rapid extensional exhumation postdates Laramide thickening by ~30 Myr indicates that crustal thickness alone was insufficient to initiate extensional tectonic and required an additional driving force. The timing of mylonitization and rapid exhumation documented here and in other MCCs are consistent with the hypothesis that slab rollback and the effect of a slab window trailing the Mendocino Triple Junction have been critical in driving the development of the MCCs of the southwest.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019TC006050","usgsCitation":"Gottardi, R., McAleer, R.J., Casale, G., Borel, M., Iriondo, A., and Jepson, G., 2020, Exhumation of the Coyote Mountains metamorphic core complex (Arizona): Implications for orogenic collapse of the southern North American Cordillera.: Tectonics, v. 39, no. 8, e2019TC006050, 33 p., https://doi.org/10.1029/2019TC006050.","productDescription":"e2019TC006050, 33 p.","ipdsId":"IP-112230","costCenters":[],"links":[{"id":489084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019tc006050","text":"Publisher Index Page"},{"id":378558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States, Mexico","state":"British Columbia, Washington, Oregon, California, Arizona, Nevada, New Mexico, Utah, Colorado, Wyoming, Idaho, Montana","otherGeospatial":"North American Cordillera, Baboquivari Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.96875,\n 50.680797145321655\n ],\n [\n -124.365234375,\n 39.57182223734374\n ],\n [\n -120.58593749999999,\n 34.161818161230386\n ],\n [\n -115.927734375,\n 30.221101852485987\n ],\n [\n -110.21484375,\n 27.605670826465445\n ],\n [\n -105.029296875,\n 32.54681317351514\n ],\n [\n -105.732421875,\n 38.75408327579141\n ],\n [\n -109.16015624999999,\n 44.33956524809713\n ],\n [\n -113.818359375,\n 49.095452162534826\n ],\n [\n -117.68554687499999,\n 51.781435604431195\n ],\n [\n -127.96875,\n 50.680797145321655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gottardi, Raphael 0000-0002-6774-1343","orcid":"https://orcid.org/0000-0002-6774-1343","contributorId":194320,"corporation":false,"usgs":false,"family":"Gottardi","given":"Raphael","email":"","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":799192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":799193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casale, Gabriele 0000-0003-1371-753X","orcid":"https://orcid.org/0000-0003-1371-753X","contributorId":192726,"corporation":false,"usgs":false,"family":"Casale","given":"Gabriele","email":"","affiliations":[{"id":27675,"text":"Appalachian State University, Boone, NC","active":true,"usgs":false}],"preferred":false,"id":799194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borel, Megan 0000-0002-5651-0603","orcid":"https://orcid.org/0000-0002-5651-0603","contributorId":240974,"corporation":false,"usgs":false,"family":"Borel","given":"Megan","email":"","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":799195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iriondo, Alexander 0000-0002-5129-9378","orcid":"https://orcid.org/0000-0002-5129-9378","contributorId":240977,"corporation":false,"usgs":false,"family":"Iriondo","given":"Alexander","email":"","affiliations":[{"id":48178,"text":"Universidad Nacional Autonoma de Mexico-Campus Juriquilla","active":true,"usgs":false}],"preferred":false,"id":799196,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jepson, Gilby 0000-0003-0151-3062","orcid":"https://orcid.org/0000-0003-0151-3062","contributorId":240978,"corporation":false,"usgs":false,"family":"Jepson","given":"Gilby","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":799197,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70211979,"text":"70211979 - 2020 - A global hybrid VS30 map with a topographic slope–based default and regional map insets","interactions":[],"lastModifiedDate":"2020-09-01T19:56:33.482891","indexId":"70211979","displayToPublicDate":"2020-06-09T17:53:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A global hybrid VS30 map with a topographic slope–based default and regional map insets","title":"A global hybrid VS30 map with a topographic slope–based default and regional map insets","docAbstract":"Time-averaged shear wave velocity over the upper 30 m of the earth’s surface (VS30) is a key parameter for estimating ground motion amplification as both a predictive and a diagnostic tool for earthquake hazards. The first-order approximation of VS30 is commonly obtained through a topographic slope–based or terrain proxy due to the widely available nature of digital elevation models. However, better-constrained VS30 maps have been developed in many regions. Such maps preferentially employ various combinations of VS30 measurements, higher-resolution elevation models, lithologic, geologic, geomorphic, and other proxies and often utilize refined interpolation schemes. We develop a new hybrid global VS30 map database that defaults to the global slope-based VS30 map, but smoothly inserts regional VS30 maps where available. In addition, we present comparisons of the default slope-based proxy maps against the new hybrid version in terms of VS30 and amplification ratio maps, and uncertainties in assigned VS30 values.
","language":"English","publisher":"Sage","doi":"10.1177/8755293020911137","usgsCitation":"Heath, D.C., Wald, D.J., Worden, C., Thompson, E.M., and Smoczyk, G.M., 2020, A global hybrid VS30 map with a topographic slope–based default and regional map insets: Earthquake Spectra, v. 36, no. 3, p. 1570-1584, https://doi.org/10.1177/8755293020911137.","productDescription":"15 p.","startPage":"1570","endPage":"1584","ipdsId":"IP-117706","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":377458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.35351562499999,\n 21.37124437061831\n ],\n [\n -90.52734374999999,\n 21.37124437061831\n ],\n [\n -90.52734374999999,\n 48.8936153614802\n ],\n [\n -127.35351562499999,\n 48.8936153614802\n ],\n [\n -127.35351562499999,\n 21.37124437061831\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Heath, David C. 0000-0002-6645-422X","orcid":"https://orcid.org/0000-0002-6645-422X","contributorId":238114,"corporation":false,"usgs":false,"family":"Heath","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":796075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worden, C. Bruce 0000-0003-1181-685X","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":189051,"corporation":false,"usgs":false,"family":"Worden","given":"C. Bruce","affiliations":[],"preferred":false,"id":796077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smoczyk, Gregory M. 0000-0002-6591-4060 gsmoczyk@usgs.gov","orcid":"https://orcid.org/0000-0002-6591-4060","contributorId":5239,"corporation":false,"usgs":true,"family":"Smoczyk","given":"Gregory","email":"gsmoczyk@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":796079,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211905,"text":"70211905 - 2020 - Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria","interactions":[],"lastModifiedDate":"2020-08-11T19:04:49.848316","indexId":"70211905","displayToPublicDate":"2020-06-09T14:02:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2255,"text":"Journal of Environmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of SELDM simulated total-phosphorus concentrations with ecological impervious-area criteria","docAbstract":"Ecological studies indicate that impervious cover (IC) greater than approximately 5%–20% may have adverse effects on receiving-stream ecology. It is difficult to separate the effects of runoff quality from other effects of urbanization on receiving streams. This study presents the results of a numerical experiment to assess the effects of increasing IC on water quality using the Stochastic Empirical Loading and Dilution Model (SELDM). Hydrologic and physiographic variables representative of southern New England were used to simulate receiving water quality in a basin with IC ranging from 0.1% to 30%. Simulation results mirror the results of ecological studies; event mean concentrations (EMCs) of total phosphorus (TP) increase proportionally to the logarithms of imperviousness for a given risk percentile. Simulation results indicated that commonly used stormwater treatment methods may be insufficient for mitigating the effects of imperviousness. Therefore, disconnection, rather than treatment, may be needed to protect water quality, and efforts to preserve undeveloped stream basins may be more effective than efforts to remediate conditions in highly developed basins. Results also indicate that commonly used water-quality criteria may be too restrictive for stormwater because TP EMCs frequently exceed these criteria, even in minimally developed basins.
Groundwater-level conditions, generalized groundwater potentiometric surfaces, and generalized flow directions at the decommissioned Naval Air Warfare Center in West Trenton, New Jersey, were evaluated for calendar year 2018. Groundwater levels measured continuously in five on-site wells and one nearby off-site well were plotted as hydrographs for January 1, 2018, through December 31, 2018. Groundwater levels measured in 110 wells on June 18, 2018, were contoured as generalized potentiometric surfaces on maps and sections. Generalized groundwater-flow directions inferred from the June 2018 data are shown in the maps and sections.
Groundwater levels in six monitoring wells fluctuated in response to seasonal changes, precipitation, and pumping from “pump-and-treat” (P&T) wells. Record high precipitation totals in November, combined with a shutdown of three P&T wells in November, resulted in annual high water levels in late November for five of the six wells monitored. Annual high groundwater levels that occur during the fall are uncharacteristic of the typical timing of annual high water levels, which usually occur in the spring following low evapotranspiration during the winter months, compared to annual low water levels, which usually occur in fall because of high evapotranspiration during the summer months. The annual high water levels occurred following a 3-day precipitation event totaling 3.50 inches from November 24-26, which also caused the largest 1-day water-level increase for five of the six wells in 2018.
The groundwater-level contour maps and sections include generalized flow directions. Given the heterogeneity of the site’s fractured rock aquifers, contours and associated groundwater-flow directions shown on the maps and sections should be considered as broad conceptualizations. A nearly vertical fault striking southwest to northeast separates the northwestern part of the site underlain by the Lockatong Formation from the southeastern part, which is underlain by the Stockton Formation. In the Lockatong Formation, general groundwater-flow directions were toward P&T wells. The P&T wells limited the flow of groundwater in the Lockatong Formation from the site into the adjacent areas and contained most groundwater contamination within the site. A groundwater divide bisected the site; groundwater in the western part generally flowed to P&T wells 8BR, 15BR, 20BR, 29BR, 56BR, 91BR, and BRP-2, and groundwater in the eastern part generally flowed to P&T well 48BR. A groundwater divide also was present in the Stockton Formation. Groundwater west of the divide in the Stockton Formation generally flowed toward P&T well 22BR, and groundwater east of the divide generally flowed south and southeast, away from the site. Saprolite and fill from land surface to depths of 25 feet below land surface exhibit similar properties to those of porous media, and water levels in surficial wells were contoured using a porous media aquifer approach. Water levels in these surficial wells indicate that groundwater in the saprolite and fill flowed predominantly toward Gold Run and, to a lesser extent, the West Ditch spring that drains to Gold Run. In addition, some shallow groundwater was captured by the cone of depression in the fractured bedrock and was attributed to P&T well 48BR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201016","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., and Lacombe, P.J., 2020, Groundwater levels and generalized potentiometric surfaces, former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2020–1016, 28 p., https://doi.org/10.3133/ofr20201016.","productDescription":"Report: v, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104199","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1016/ofr20201016.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1016"},{"id":375285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1016/coverthb.jpg"},{"id":375288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98N1GWV","text":"USGS data release","linkHelpText":"Reported groundwater levels and groundwater pump-and-treat withdrawals, former Naval Air Warfare Center, West Trenton, New Jersey, 2018"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81613278388977,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.26694411855267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The hydrogeology below large surface water features such as rivers and estuaries is universally under-informed at the long reach to basin scales (tens of km+). This challenge inhibits the accurate modeling of fresh/saline groundwater interfaces and groundwater/surface water exchange patterns at management-relevant spatial extents. Here we introduce a towed, floating transient electromagnetic (TEM) system (i.e. FloaTEM) for rapid (up to 15 km/h) high resolution electrical mapping of the subsurface below large water bodies to depths often a factor of 10 greater than other towed instruments. The novel FloaTEM system is demonstrated at a range of diverse 4th through 6th-order riverine settings across the United States including 1) the Farmington River, near Hartford, Connecticut; 2) the Upper Delaware River near Barryville, New York; 3) the Tallahatchie River near Shellmound, Mississippi; and, 4) the Eel River estuary, on Cape Cod, near Falmouth, Massachusetts. Airborne frequency-domain electromagnetic and land-based towed TEM data are also compared at the Tallahatchie River site, and streambed geologic scenarios are explored with forward modeling. A range of geologic structures and pore water salinity interfaces were identified. Process-based interpretation of the case study data indicated FloaTEM can resolve varied sediment-water interface materials, such as the accumulation of fines at the bottom of a reservoir and permeable sand/gravel riverbed sediments that focus groundwater discharge. Bedrock layers were mapped at several sites, and aquifer confining units were defined at comparable resolution to airborne methods. Terrestrial fresh groundwater discharge with flowpaths extending hundreds of meters from shore was also imaged below the Eel River estuary, improving on previous hydrogeological characterizations of that nutrient-rich coastal exchange zone. In summary, the novel FloaTEM system fills a critical gap in our ability to characterize the hydrogeology below surface water features and will support more accurate prediction of groundwater/surface water exchange dynamics and fresh-saline groundwater interfaces.
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