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,{"id":70223987,"text":"fs20213043 - 2021 - Continuous water-quality and suspended-sediment transport monitoring in the San Francisco Bay, California, water years 2018–19","interactions":[],"lastModifiedDate":"2021-09-15T11:43:03.004281","indexId":"fs20213043","displayToPublicDate":"2021-09-14T13:37:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3043","displayTitle":"Continuous Water-Quality and Suspended-Sediment Transport Monitoring in the San Francisco Bay, California, Water Years 2018–19","title":"Continuous water-quality and suspended-sediment transport monitoring in the San Francisco Bay, California, water years 2018–19","docAbstract":"<h1>Water-Quality in San Francisco Bay</h1><p>The U.S. Geological Survey (USGS) monitors water quality and suspended-sediment transport in the San Francisco Bay (Bay) as part of a multi-agency effort to address estuary management, water supply, and ecological concerns. The San Francisco Bay area is home to millions of people, and the Bay teems with marine and terrestrial flora and fauna. Freshwater mixes with saltwater in the Bay and is subject to riverine influences (floods, droughts, managed reservoir releases, and freshwater diversions) and marine influences (tides, waves, and effects of saltwater). To understand this environment, the USGS, along with its cooperators (see “Acknowledgments” section), has been monitoring the Bay’s waters continuously since 1988.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213043","usgsCitation":"Einhell, D.C., Davila Olivera, S., and Palm, D.L., 2021, Continuous water-quality and suspended-sediment transport monitoring in the San Francisco Bay, California, water years 2018–19: U.S. Geological Survey Fact Sheet 2021-3043, 4 p., https://doi.org/10.3133/fs20213043.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129590","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":389209,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3043/covrthb.jpg"},{"id":389210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3043/fs20213043.pdf","text":"Report","size":"3. 5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389211,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2021/3043/fs20213043.xml"},{"id":389212,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2021/3043/images"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.98095703125,\n              37.17782559332976\n            ],\n            [\n              -121.4208984375,\n              37.17782559332976\n            ],\n            [\n              -121.4208984375,\n              38.28993659801203\n            ],\n            [\n              -122.98095703125,\n              38.28993659801203\n            ],\n            [\n              -122.98095703125,\n              37.17782559332976\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<p><br data-mce-bogus=\"1\"></p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-09-14","noUsgsAuthors":false,"publicationDate":"2021-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Einhell, Darin C. 0000-0002-3190-7727 deinhell@usgs.gov","orcid":"https://orcid.org/0000-0002-3190-7727","contributorId":220042,"corporation":false,"usgs":true,"family":"Einhell","given":"Darin","email":"deinhell@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davila Olivera, Selina M. 0000-0002-2574-2997","orcid":"https://orcid.org/0000-0002-2574-2997","contributorId":265761,"corporation":false,"usgs":true,"family":"Davila Olivera","given":"Selina","email":"","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palm, Danielle L. 0000-0003-3045-5287","orcid":"https://orcid.org/0000-0003-3045-5287","contributorId":265762,"corporation":false,"usgs":true,"family":"Palm","given":"Danielle","email":"","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823305,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70229079,"text":"70229079 - 2021 - Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data","interactions":[],"lastModifiedDate":"2022-02-28T15:25:39.969747","indexId":"70229079","displayToPublicDate":"2021-09-14T09:13:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":693,"text":"Alces","active":true,"publicationSubtype":{"id":10}},"title":"Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data","docAbstract":"<p><span>Moose (</span><i>Alces alces</i><span>) populations have experienced unprecedented declines along the southern periphery of their range, including Vermont, USA. Habitat management may be used to improve the status of the population and health of individuals. To date, however, Vermont wildlife managers have been challenged to effectively use this important tool due to the lack of fine-scale information on moose space use and habitat characteristics. To assess habitat use, we combined more than 40,000 moose locations collected from radio-collared individuals (n = 74), recent land cover data, and high resolution, 3-dimensional lidar (</span><i>light detection and ranging</i><span>) data to develop Resource Utilization Functions (RUF) by age (mature and young adult), season (dormant and growth), and sex. Each RUF linked home range use to average habitat conditions within 400 m or 1 km of each 30 m</span><sup>2</sup><span>&nbsp;pixel within the home range. Across analyses, the top RUF models included both composition (as measured through the National Land Cover Database) and structure (as measured through lidar) variables, and significantly outperformed models that excluded lidar variables. These findings support the notion that lidar is an effective tool for improving the ability of models to estimate patterns of habitat use, especially for larger bodied mammals. Generally speaking, female moose actively used areas with proportionally more regenerating forest (i.e., forage &lt; 3.0 m) and more mature forest (i.e., canopy structure &gt; 6.0 m), while males actively used more high elevation, mixed forest types. Further, moose exhibited important seasonal differences in habitat use that likely reflect temporal changes in energetic and nutritional requirements and behavior across the year. Moose used areas with proportionally more regenerating forest (i.e., forage &lt; 3.0 m) during the growth period and female moose had strong positive associations with lidar-derived canopy structure during the growth (but not the dormant) period. Ultimately, the resultant maps of habitat use provide a means of informing management activities (e.g., the restoration or alteration of habitats to benefit moose) and policies around land use that may contribute to population recovery.</span></p>","language":"English","publisher":"North American Moose Conference and Workshop","usgsCitation":"Blouin, J., Debow, J., Rosenblatt, E., Alexander, C., Gieder, K., Fortin, N., Murdoch, J., and Donovan, T.M., 2021, Modeling moose habitat use by age, sex, and season in Vermont, USA using high-resolution lidar and national land cover data: Alces, v. 57, p. 71-98.","productDescription":"28 p.","startPage":"71","endPage":"98","ipdsId":"IP-121680","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396550,"rank":1,"type":{"id":15,"text":"Index 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,{"id":70232168,"text":"70232168 - 2021 - Early growth and ecophysiological responses of Koa (Acacia koa A. Gray) seedlings to reduced water and phosphorus","interactions":[],"lastModifiedDate":"2022-06-09T13:18:41.942854","indexId":"70232168","displayToPublicDate":"2021-09-14T08:13:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5909,"text":"New Forests","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Early growth and ecophysiological responses of Koa (<i>Acacia koa</i> A. Gray) seedlings to reduced water and phosphorus","title":"Early growth and ecophysiological responses of Koa (Acacia koa A. Gray) seedlings to reduced water and phosphorus","docAbstract":"<p>Sites in need of restoration typically have one or more environmental factors that limit seedling establishment. Identifying ecophysiological responses to environmental stressors can provide important insights into mitigating measures that would allow seedlings to overcome such constraints to survival. Koa (<i>Acacia koa</i>&nbsp;A. Gray) is a nitrogen-fixing tree species endemic to Hawaiʻi that is highly valued in restoring degraded forest ecosystems, which are often limited in available water and phosphorus. This study examined how koa seedlings respond to conditions of reduced water (65&nbsp;W) and no phosphorus (0P). After 17&nbsp;weeks, seedlings subjected to 65&nbsp;W or 0P accumulated less biomass, smaller root-collar diameters, and lower nitrogen and phosphorus contents. Combined reductions in water and P resulted in seedlings with increased root to shoot dry biomass and shorter shoots. Seedlings subjected to 65&nbsp;W also had lower instantaneous rates of CO<sub>2</sub>&nbsp;assimilation, but higher instantaneous water-use efficiencies following irrigation, suggesting that koa responds to water deficits by decreasing water loss via reduced stomatal conductance. Seedlings subjected to 0P had similar rates of CO<sub>2</sub>&nbsp;assimilation relative to those grown with adequate P, suggesting that koa is able to employ strategies to avoid physiological impairment from conditions of inadequate P. Future research should assess whether subjecting koa seedlings to reduced water before planting on water-limited sites cues increased drought resistance and whether uptake and storage of P by seedlings in the nursery better supports growth following outplanting, particularly on sites with anticipated low plant-available water.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11056-021-09877-8","usgsCitation":"Gerber, K., Ross-Davis, A., Perakis, S.S., and Davis, A.S., 2021, Early growth and ecophysiological responses of Koa (Acacia koa A. 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 \"}}]}","volume":"2021","noUsgsAuthors":false,"publicationDate":"2021-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Gerber, Kaitlin","contributorId":292369,"corporation":false,"usgs":false,"family":"Gerber","given":"Kaitlin","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":844416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross-Davis, Amy","contributorId":292370,"corporation":false,"usgs":false,"family":"Ross-Davis","given":"Amy","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":844417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Anthony S.","contributorId":292372,"corporation":false,"usgs":false,"family":"Davis","given":"Anthony","email":"","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":844419,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70224926,"text":"70224926 - 2021 - Data management and interactive visualizations for the evolving marine biodiversity observation network","interactions":[],"lastModifiedDate":"2021-10-05T12:18:09.296304","indexId":"70224926","displayToPublicDate":"2021-09-14T07:16:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Data management and interactive visualizations for the evolving marine biodiversity observation network","docAbstract":"<p>Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information System to address these needs through collaboration, data standardization, and data sharing. Here, we describe the generalized MBON data processing flow, which includes several steps to ensure that data are findable, accessible, interoperable, and reusable. By following this flow, data collected and managed by MBON have contributed to our understanding of the Global Ocean Observing System Essential Ocean Variables and demonstrated the value of web-based, interactive tools to explore and better understand environmental change. Although the MBON’s generalized data processing flow is already in practice, work remains in building ontologies for biological concepts, improving processing scripts for data standardization, and speeding up the data collection-to-sharing timeframe.</p>","language":"English","publisher":"Oceanography Society","doi":"10.5670/oceanog.2021.220","usgsCitation":"Benson, A., Murray, T., Canonico, G., Montes, E., Muller-Karger, F., Kavanaugh, M.T., Trinanes, J., and deWitt, L.M., 2021, Data management and interactive visualizations for the evolving marine biodiversity observation network: Oceanography, v. 34, no. 2, 12 p., https://doi.org/10.5670/oceanog.2021.220.","productDescription":"12 p.","ipdsId":"IP-129399","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":450824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2021.220","text":"Publisher Index Page"},{"id":390231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":202078,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":824632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Tylar","contributorId":267183,"corporation":false,"usgs":false,"family":"Murray","given":"Tylar","email":"","affiliations":[{"id":55430,"text":"Institute for Marine Remote Sensing/IMaRS, College of Marine Science, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Canonico, Gabrielle","contributorId":217563,"corporation":false,"usgs":false,"family":"Canonico","given":"Gabrielle","email":"","affiliations":[{"id":39659,"text":"National Oceanographic and Atmospheric Administration, US Integrated Ocean Observing System, Silver Spring, MD, USA","active":true,"usgs":false}],"preferred":false,"id":824634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montes, Enrique","contributorId":217565,"corporation":false,"usgs":false,"family":"Montes","given":"Enrique","email":"","affiliations":[{"id":39661,"text":"University of South Florida, St Petersburg, FL USA","active":true,"usgs":false}],"preferred":false,"id":824635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muller-Karger, Frank","contributorId":218424,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","affiliations":[],"preferred":false,"id":824636,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kavanaugh, Maria T.","contributorId":200277,"corporation":false,"usgs":false,"family":"Kavanaugh","given":"Maria","email":"","middleInitial":"T.","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":824637,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trinanes, Joaquin","contributorId":44102,"corporation":false,"usgs":false,"family":"Trinanes","given":"Joaquin","email":"","affiliations":[{"id":34485,"text":"University of Santiago de Compostela, Santiago de Compostela, Spain","active":true,"usgs":false}],"preferred":false,"id":824638,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"deWitt, Lynn M.","contributorId":267184,"corporation":false,"usgs":false,"family":"deWitt","given":"Lynn","email":"","middleInitial":"M.","affiliations":[{"id":55431,"text":"National Oceanographic and Atmospheric Administration, National Marine Fisheries Service, Southwest Fisheries Science Center, Environmental Research Division","active":true,"usgs":false}],"preferred":false,"id":824639,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70225676,"text":"70225676 - 2021 - An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale","interactions":[],"lastModifiedDate":"2021-11-02T11:46:57.154677","indexId":"70225676","displayToPublicDate":"2021-09-14T06:44:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6503,"text":"Journal of Geophysical Research Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale","docAbstract":"<div class=\"article-section__content en main\"><p>Turbulence-resolving simulations elucidate key elements of fluid dynamics and sediment transport in fluvial environments. This research presents a feasible strategy for applying state-of-the-art computational fluid mechanics to the study of sediment transport and morphodynamic processes in lateral separation zones, which are common features in canyon rivers where massive lateral flow separation causes large-scale turbulence that controls sediment erosion and deposition. An eddy-resolving model was developed and tested at the field-scale, coupling a viscous flow and sediment transport solver using Detached Eddy Simulation techniques. A morphodynamic model was applied to the viscous flow/sediment solver to calculate erosion and deposition. A simulation of turbulence was performed at the grid resolution for a straight channel to determine the relative contributions of modeled and resolved diffusivity. The time-dependent, energetically important, correlative, non-stationary signals of the simulated quantities were captured at the lateral separation zone. Strong periodic signals featured by high amplitude were found at the separation zone, while low frequency pulsations were observed at the reattachment zone of the lateral separation zone. Interactions between the eddies and the loose bed boundaries resulted in erosion of sediment at the main channel followed by deposition at the primary eddy and eddy bars.</p></div><p>tions elucidate key elements of fluid dynamics and sediment transport in fluvial environments. This research presents a feasible strategy for applying state-of-the-art computational fluid mechanics to the study of sediment transport and morphodynamic processes in lateral separation zones, which are common features in canyon rivers where massive lateral flow separation causes large-scale turbulence that controls sediment erosion and deposition. An eddy-resolving model was developed and tested at the field scale, coupling viscous flow and sediment transport solver using Detached Eddy Simulation (DES) techniques. A morphodynamic model was applied to the viscous flow/sediment solver to calculate erosion and deposition. A simulation of turbulence was performed at the grid resolution for a straight channel to determine the relative contributions of modeled and resolved diffusivity. The time-dependent, energetically important, correlative non-stationary signals of the simulated quantities were captured at the lateral separation zone. Strong periodic signals featured by high amplitude were found at the separation zone, while low frequency pulsations were observed at the reattachment zone of the lateral separation zone. Interactions between the eddies and the loose bed boundaries resulted in massive erosion of sediment at the main channel followed by deposition at the primary eddy and eddy bars.</p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006149","usgsCitation":"Alvarez, L.V., and Grams, P.E., 2021, An eddy-resolving numerical model to study turbulent flow, sediment and bed evolution using detached eddy simulation in a lateral separation zone at the field-scale: Journal of Geophysical Research Earth Surface, v. 126, no. 10, e2021JF006149, 29 p., https://doi.org/10.1029/2021JF006149.","productDescription":"e2021JF006149, 29 p.","ipdsId":"IP-128083","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":391260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.1484375,\n              36.474306755095235\n            ],\n            [\n              -110.89599609375,\n              36.474306755095235\n            ],\n            [\n              -110.89599609375,\n              37.020098201368114\n            ],\n            [\n              -112.1484375,\n              37.020098201368114\n            ],\n            [\n              -112.1484375,\n              36.474306755095235\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Alvarez, Laura V.","contributorId":178431,"corporation":false,"usgs":false,"family":"Alvarez","given":"Laura","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":826186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826187,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70221220,"text":"sir20215053 - 2021 - Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018","interactions":[],"lastModifiedDate":"2021-09-13T16:54:19.222516","indexId":"sir20215053","displayToPublicDate":"2021-09-13T11:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5053","displayTitle":"Analysis of <i>Escherichia coli</i>, Total Recoverable Iron, and Dissolved Selenium Concentrations, Loading, and Identifying Data Gaps for Selected 303(d) Listed Streams, Grand Valley, Western Colorado, 1980–2018","title":"Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018","docAbstract":"<p>Tributaries to the Colorado River in the Grand Valley in western Colorado (segment COLCLC13b) have been placed on the State of Colorado 303(d) list as impaired for <i>Escherichia coli (E. coli)</i>, total recoverable iron, and dissolved selenium. The Colorado Department of Public Health and Environment Water Quality Control Division is required to develop total maximum daily loads for these constituents in these tributaries. The U.S. Geological Survey, in cooperation with the Grand Valley Drainage District and Colorado Water Conservation Board, conducted a study to (1) characterize concentrations, loads, and load reductions for <i>E. coli</i>, total recoverable iron, and dissolved selenium using existing data and (2) identify water-quality data gaps to inform future monitoring strategies. This study analyzed water-quality and streamflow data for 3 main-stem sites (2 sites along the Colorado River and 1 site along the Gunnison River) and 29 selected sites on tributaries to the Colorado River.</p><p>Sample data were available at five sites along Adobe Creek and at six sites along Leach Creek, the two tributaries in the study area that are impaired for <i>E. coli</i>. All geometric mean <i>E. coli</i> concentrations at sites along Adobe Creek and Leach Creek exceeded the State recreational use standard of 126 colony forming units per 100 milliliters (CFU/100 mL). In Adobe Creek, <i>E. coli</i> concentrations in samples ranged from 45.7 to more than 2,420 CFU/100 mL (method upper reporting limit for undiluted samples), and geometric mean concentrations at sites ranged from 301 to 1,180 CFU/100 mL. The <i>E. coli</i> concentrations generally increased in the downstream direction in Adobe Creek; however, increases were not seen between all sites. The largest downstream increase in <i>E. coli</i> concentration was measured between the two most upstream sites. In Leach Creek, concentrations of <i>E. coli</i> in samples ranged from 25.9 to more than 2,420 CFU/100 mL, and geometric mean concentrations at sites ranged from 160 to 259 CFU/100 mL. The <i>E. coli</i> concentrations showed no consistent downgradient increase in Leach Creek. In fact, some of the highest <i>E. coli</i> concentrations were measured at the most upstream site, Leach Creek at Summer Hill Drive.</p><p>Total recoverable iron concentrations and loads were evaluated at 15 tributary sites for samples collected from August 1993 to February 2018. Median total recoverable iron concentrations ranged from 211 to 4,670 micrograms per liter (µg/L). The chronic aquatic-life water-quality standard (1,000 µg/L) was exceeded in most irrigation season (April through October) samples but was rarely exceeded in nonirrigation season (November through March) samples. Concentrations were often an order of magnitude higher in samples collected during irrigation season than in samples collected during nonirrigation season. None of the sites had enough concurrent total recoverable iron and streamflow data to compute annual loads. As with <i>E. coli</i>, the lack of concurrent total recoverable iron and streamflow information represents a data gap, which needs to be addressed to compute annual loads.</p><p>Dissolved selenium concentrations and loads were evaluated at 20 tributary sites using discrete water-quality data collected 1991–2018. Dissolved selenium concentrations were higher during nonirrigation season than during irrigation season at tributary sites. However, irrigation season dissolved selenium loads were generally higher than nonirrigation selenium loads, because streamflows were higher during irrigation season. Regression analysis was used to estimate daily dissolved selenium concentrations and loads at three main-stem sites for water years (WYs) 1980–2018 (Gunnison River near Grand Junction and Colorado River near Colorado-Utah State Line) and WYs 2002–18 (Colorado River near Cameo). A trend analysis of dissolved selenium concentrations and loads was completed for these sites from the same respective starting dates but ending in 2017. A continuing downward trend in dissolved selenium concentration was observed at all sites and across all seasonal designations of the analysis. The dissolved selenium concentration decreased by 0.12 µg/L from WY 2002 to 2017 at Colorado River near Cameo, representing an 18-percent decrease during the time period. The dissolved selenium concentration at Gunnison River near Grand Junction decreased by 4.2 µg/L from WY 1980 to 2017, representing a 56-percent decrease overall. During the same time period, dissolved selenium concentration at Colorado River near Colorado-Utah State Line decreased by 3.8 µg/L, representing a 56-percent decrease overall. A downward trend in dissolved selenium load was also observed at all sites and across all seasonal designations of the analysis. The relative contribution of dissolved selenium from the Grand Valley near Grand Junction was estimated by comparing loads at main-stem sites bracketing the study area. The two upstream sites, Colorado River near Cameo and Gunnison River near Grand Junction, contributed 60,300 cumulative pounds and 251,000 cumulative pounds, respectively, during WYs 2002–18. At the furthest downstream site, Colorado River near Colorado-Utah State Line, 490,000 cumulative pounds were estimated during the same time period, indicating that the region between Whitewater and State line contributed approximately 179,000 cumulative pounds or a mean annual load of 10,500 lb/yr. Grand Valley dissolved selenium contributions appear to be stable during WYs 2002–18.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215053","collaboration":"Prepared in cooperation with the Grand Valley Drainage District and the  Colorado Water Conservation Board","usgsCitation":"Miller, L.D., Gidley, R.G., Day, N.K., and Thomas, J.C., 2021, Analysis of <i>Escherichia coli</i>, total recoverable iron, and dissolved selenium concentrations, loading, and identifying data gaps for selected 303(d) listed streams, Grand Valley, western Colorado, 1980–2018 (ver. 1.1, September  2021): U.S. Geological Survey Scientific Investigations Report 2021-5053, 37 p., https://doi.org/10.3133/sir20215053.","productDescription":"Report: vii, 37 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-106948","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":386290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5053/sir20215053.pdf","text":"Report","size":"2.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5053"},{"id":386289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5053/coverthb3.jpg"},{"id":388012,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5053/versionHist.txt","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":386291,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P6WI44","text":"USGS data release","linkHelpText":"Analysis of Escherichia coli, total recoverable iron, and dissolved selenium concentrations and loads for selected 303(d) listed segments in the Grand Valley, western Colorado, 1980–2018 (ver. 3.0, August 2021)"}],"country":"United States","state":"Colorado","otherGeospatial":"Grand Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.083251953125,\n              38.736946065676\n            ],\n            [\n              -107.99560546875,\n              38.736946065676\n            ],\n            [\n              -107.99560546875,\n              39.470125122358176\n            ],\n            [\n              -109.083251953125,\n              39.470125122358176\n            ],\n            [\n              -109.083251953125,\n              38.736946065676\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: June 9, 2021; Version 1.1: September 13, 2021","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/co-water\" data-mce-href=\"https://www.usgs.gov/centers/co-water\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-415<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Summary of Previous Work</li><li>Methods</li><li>Analysis of <i>E. coli</i>, Total Recoverable Iron, and Dissolved Selenium Concentrations and Loading and Data Gaps</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2021-06-09","revisedDate":"2021-09-13","noUsgsAuthors":false,"publicationDate":"2021-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Lisa D. 0000-0002-3523-0768 ldmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-3523-0768","contributorId":1125,"corporation":false,"usgs":true,"family":"Miller","given":"Lisa","email":"ldmiller@usgs.gov","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gidley, Rachel G. 0000-0002-9840-8252","orcid":"https://orcid.org/0000-0002-9840-8252","contributorId":259315,"corporation":false,"usgs":true,"family":"Gidley","given":"Rachel","email":"","middleInitial":"G.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Judith C. 0000-0001-7883-1419","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":202706,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817109,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70223869,"text":"sir20215081 - 2021 - Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019","interactions":[],"lastModifiedDate":"2021-09-14T16:44:19.744785","indexId":"sir20215081","displayToPublicDate":"2021-09-13T07:29:23","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5081","displayTitle":"Storage Capacity and Sedimentation Characteristics of Loch Lomond Reservoir, California, 2019","title":"Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019","docAbstract":"<p>In May of 2019, Loch Lomond Reservoir was surveyed by the U.S. Geological Survey (USGS) in cooperation with the city of Santa Cruz to assess the current storage capacity and sedimentation rates in the reservoir. Survey methods combined sonar soundings to measure bathymetry and lidar scans with GPS data to measure near-shore topography and sediment bed samples to understand reservoir bed-material<br>size. The survey data produced a bare-earth digital elevation model (DEM) of the reservoir at a resolution of 1 square meter or better to elevations at or above the reservoir spillway elevation, providing the coverage needed to estimate storage capacity. Additionally, the USGS compared the current survey to storage estimates from historical surveys—particularly the most recent survey in 2009—to evaluate storage capacity trends. Lastly, a hindcast estimate of scaled sediment yield using sediment yields from the San Lorenzo River (USGS station 11160500)—where the San Lorenzo River watershed encompasses the Loch Lomond Reservoir watershed—were used to compare indirect estimates of storage loss to direct storage loss.</p><p>The 2019 survey resulted in a measured storage capacity of 8,770±50 acre-feet. The differences in storage between 2009 and 2019 varied substantially by depth. In shallow areas with depths less than 30 ft (at full reservoir), such as the very upstream end of the reservoir, storage loss (sediment deposition) dominated with a loss of about 68 acre-feet from 2009 to 2019. In areas deeper than 30 ft, persistent small storage gains over a wide range of depths totaled 82 acre-feet from 2009 to 2019.</p><p>Storage loss estimates derived from estimated watershed sediment yields and reservoir characteristics were similar to storage losses computed from past surveys. This hindcasting produced an estimate of about 500 acre-feet of total storage loss for the history of the reservoir, or an average of about 8–9 acre-feet/year during the 60-year period. For the period 2009–2019, the hindcast produced an estimated total storage loss of 42 acre-feet, which is broadly consistent with the 68 acre-feet of storage loss computed for shallow areas based on the repeat surveys.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215081","collaboration":"Prepared in cooperation with the city of Santa Cruz","programNote":"Water Availability and Use Science Program","usgsCitation":"Whealdon-Haught, D.R., Wright, S.A., and Marineau, M.D., 2021, Storage capacity and sedimentation characteristics of Loch Lomond Reservoir, California, 2019: U.S. Geological Survey Scientific Investigations Report 2021-5081, 28 p., https://doi.org/10.3133/sir20215081.","productDescription":"Report: vii, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-120568","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":389073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5081/covrthb.jpg"},{"id":389074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5081/sir20215081.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389075,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5081/sir20215081.xml"},{"id":389076,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5081/images"},{"id":389147,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91BUQWP","linkHelpText":"Loch Lomond Reservoir 2019 Survey Data"}],"country":"United States","state":"California","otherGeospatial":"Loch Lomond Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.07509994506836,\n              37.10091974583046\n            ],\n            [\n              -122.05415725708008,\n              37.10091974583046\n            ],\n            [\n              -122.05415725708008,\n              37.130897691327746\n            ],\n            [\n              -122.07509994506836,\n              37.130897691327746\n            ],\n            [\n              -122.07509994506836,\n              37.10091974583046\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Data Availability&nbsp;&nbsp;</li><li>Results&nbsp;&nbsp;</li><li>Discussion of Storage-Capacity Changes from 2009 to 2019&nbsp;&nbsp;</li><li>Discussion of Long-Term Reservoir Storage and Watershed Sediment Yield&nbsp;&nbsp;</li><li>Conclusions&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Bowman and Williams 2012 Memo to the City of Santa Cruz&nbsp;&nbsp;</li><li>Appendix 2. Bowman and Williams 2017 Memo to the City of Santa Cruz&nbsp;</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-09-13","noUsgsAuthors":false,"publicationDate":"2021-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Whealdon-Haught, Daniel R. 0000-0002-8923-1512","orcid":"https://orcid.org/0000-0002-8923-1512","contributorId":193160,"corporation":false,"usgs":false,"family":"Whealdon-Haught","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":823045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70226498,"text":"70226498 - 2021 - Assessment of multiple ecosystem metabolism methods in an estuary","interactions":[],"lastModifiedDate":"2021-11-22T13:21:39.355414","indexId":"70226498","displayToPublicDate":"2021-09-13T07:12:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9929,"text":"Limnology & Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of multiple ecosystem metabolism methods in an estuary","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Ecosystem metabolism is a key ecological attribute and easy to describe, but quantifying metabolism in estuaries is challenging. Properly scaling measurements through time and space requires consideration of hydrodynamics and mixing water from heterogeneous sources, making any estimation uncertain. Here, we compared three methods for modeling ecosystem metabolism in a portion of the Sacramento-San Joaquin Delta. Metabolism estimates based on laboratory incubations, continuous in situ buoys, and an oxygen isotope approach all indicated the system was net heterotrophic, and calculated rates were comparable in magnitude when averaged over the 2-month study. Daily metabolic rates based on in situ buoys were the most variable, likely due to horizontal and vertical advection and poor portrayal of the dissolved oxygen budget. After temporally averaging in situ buoy estimates or smoothing the dissolved oxygen time series for tidal effects, rates were more comparable to the other methods, which may be necessary to account for tidal advection and unbalanced contributions from subhabitats within the metabolic footprint. Incubation-based rates represent the finest temporal and spatial scale and only account for pelagic processes, which may explain why incubation-based rates were lower than the other two methods. The oxygen isotope method provided temporally and spatially integrated rates that were bracketed by the other two methods and may be a valuable tool in systems matching the model requirements. Because uncertainty arises in each method from a number of assumptions and scaling calculations, the resolution of metabolic rates in estuaries is likely coarser and more variable than in other aquatic ecosystems.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10458","usgsCitation":"Loken, L.C., Van Nieuwenhuyse, E.E., Dahlgren, R.A., Kammel, L., Stumpner, P., Burau, J.R., and Sadro, S., 2021, Assessment of multiple ecosystem metabolism methods in an estuary: Limnology & Oceanography: Methods, v. 19, no. 11, p. 741-757, https://doi.org/10.1002/lom3.10458.","productDescription":"17 p.","startPage":"741","endPage":"757","ipdsId":"IP-128814","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":450828,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/05g263g3","text":"External Repository"},{"id":391974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.6953125,\n              37.735969208590504\n            ],\n            [\n              -121.124267578125,\n              37.735969208590504\n            ],\n            [\n              -121.124267578125,\n              39.47860556892209\n            ],\n            [\n              -122.6953125,\n              39.47860556892209\n            ],\n            [\n              -122.6953125,\n              37.735969208590504\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"19","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Nieuwenhuyse, Erwin E 0000-0002-9032-2681","orcid":"https://orcid.org/0000-0002-9032-2681","contributorId":269423,"corporation":false,"usgs":false,"family":"Van Nieuwenhuyse","given":"Erwin","email":"","middleInitial":"E","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":827109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahlgren, Randy A 0000-0002-8961-875X","orcid":"https://orcid.org/0000-0002-8961-875X","contributorId":269424,"corporation":false,"usgs":false,"family":"Dahlgren","given":"Randy","email":"","middleInitial":"A","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":827110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kammel, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":211840,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827112,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":827113,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":827114,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223698,"text":"sim3478 - 2021 - Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020","interactions":[],"lastModifiedDate":"2021-09-13T16:57:52.138458","indexId":"sim3478","displayToPublicDate":"2021-09-13T06:56:23","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3478","displayTitle":"Altitude of the Potentiometric Surface in the Mississippi River Valley Alluvial Aquifer, Spring 2020","title":"Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020","docAbstract":"<p>The purpose of this report is to present a potentiometric-surface map for the Mississippi River Valley alluvial aquifer (MRVA). The source data for the map were groundwater-altitude data from wells measured manually or continuously generally in spring 2020 and from the altitude of the top of the water surface measured generally on April 9, 2020, in rivers in the area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3478","programNote":"Water Availability and Use Science Program","usgsCitation":"McGuire, V.L., Seanor, R.C., Asquith, W.H., Strauch, K.R., Nottmeier, A.M., Thomas, J.C., Tollett, R.W., and Kress, W.H., 2021, Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2020: U.S. Geological Survey Scientific Investigations Map 3478, 5 sheets, includes 14-p. pamphlet, https://doi.org/10.3133/sim3478.","productDescription":"Pamphlet: vi, 14p.; 5 Sheets: 30.00 x 46.00 inches or smaller; Data Release; Dataset","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119302","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":388770,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":388769,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CXDIPL","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Datasets used to map the potentiometric surface, Mississippi River Valley alluvial aquifer, spring 2020"},{"id":388768,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_sheet5.pdf","text":"Sheet 5—Atchafalaya and Deltaic and Chenier Plain MAP regions","size":"6.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Sheet 5"},{"id":388762,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3478/coverthb2.jpg"},{"id":388767,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_sheet4.pdf","text":"Sheet 4—Delta MAP region","size":"4.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Sheet 4"},{"id":388763,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_pamphlet.pdf","text":"Pamphlet","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Pamphlet"},{"id":388764,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_sheet1.pdf","text":"Sheet 1—All Mississippi Alluvial Plain (MAP) regions","size":"14.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Sheet 1"},{"id":388765,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_sheet2.pdf","text":"Sheet 2—St. Francis and Cache MAP regions","size":"5.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Sheet 2"},{"id":388766,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3478/sim3478_sheet3.pdf","text":"Sheet 3—Boeuf and Grand Prairie MAP regions","size":"6.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3478 Sheet 3"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi River Valley Alluvial Aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.62597656249999,\n              29.152161283318915\n            ],\n            [\n              -88.76953125,\n              28.8831596093235\n            ],\n            [\n              -88.9453125,\n              29.726222319395504\n            ],\n            [\n              -90.439453125,\n              30.751277776257812\n            ],\n            [\n              -90,\n              33.247875947924385\n            ],\n            [\n              -88.857421875,\n              35.17380831799959\n            ],\n            [\n              -88.59374999999999,\n              36.421282443649496\n            ],\n            [\n              -89.12109375,\n              37.43997405227057\n            ],\n            [\n              -90.1318359375,\n              37.26530995561875\n            ],\n            [\n              -91.318359375,\n              35.10193405724606\n            ],\n            [\n              -91.845703125,\n              32.84267363195431\n            ],\n            [\n              -91.8896484375,\n              31.87755764334002\n            ],\n            [\n              -92.2412109375,\n              29.99300228455108\n            ],\n            [\n              -91.62597656249999,\n              29.152161283318915\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"mailto:%20dc_ne@usgs.gov\" href=\"mailto:%20dc_ne@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ne-water\" data-mce-href=\"https://www.usgs.gov/centers/ne-water\">Nebraska Water Science Center</a> <br>U.S. Geological Survey<br>5231 South 19th Street <br>Lincoln, NE 68512</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Introduction</li><li>Study Area Description</li><li>Data and Methods</li><li>Potentiometric-Surface Map, Spring 2020</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-09-13","noUsgsAuthors":false,"publicationDate":"2021-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Virginia L. 0000-0002-3962-4158 vlmcguir@usgs.gov","orcid":"https://orcid.org/0000-0002-3962-4158","contributorId":404,"corporation":false,"usgs":true,"family":"McGuire","given":"Virginia","email":"vlmcguir@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seanor, Ronald C. 0000-0001-5735-5580","orcid":"https://orcid.org/0000-0001-5735-5580","contributorId":218443,"corporation":false,"usgs":true,"family":"Seanor","given":"Ronald","email":"","middleInitial":"C.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strauch, Kellan R. 0000-0002-7218-2099","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":208562,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Judith C. 0000-0001-7883-1419","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":202706,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822374,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tollett, Roland W. 0000-0002-4726-5845 rtollett@usgs.gov","orcid":"https://orcid.org/0000-0002-4726-5845","contributorId":1896,"corporation":false,"usgs":true,"family":"Tollett","given":"Roland","email":"rtollett@usgs.gov","middleInitial":"W.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822375,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kress, Wade H. 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":223007,"corporation":false,"usgs":true,"family":"Kress","given":"Wade H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822376,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70248974,"text":"70248974 - 2021 - Synchronous emplacement of the anorthosite xenolith-bearing Beaver River diabase and one of the largest lava flows on Earth","interactions":[],"lastModifiedDate":"2023-09-27T11:59:24.552923","indexId":"70248974","displayToPublicDate":"2021-09-13T06:52:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Synchronous emplacement of the anorthosite xenolith-bearing Beaver River diabase and one of the largest lava flows on Earth","docAbstract":"<div class=\"article-section__content en main\"><p>New geochronologic and paleomagnetic data from the North American Midcontinent Rift (MCR) reveal the synchronous emplacement of the Beaver River diabase, the anorthosite xenoliths within it, and the Greenstone Flow—one of the largest lava flows on Earth. A U-Pb zircon date of 1091.83&nbsp;<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/835cc8ce-e5a1-4954-a6d6-c7b578c5e17c/ggge22632-math-0001.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/835cc8ce-e5a1-4954-a6d6-c7b578c5e17c/ggge22632-math-0001.png\">&nbsp;0.21&nbsp;Ma (2<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/bb4c3fab-e424-4fdd-bd15-29863639a746/ggge22632-math-0002.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0002\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/bb4c3fab-e424-4fdd-bd15-29863639a746/ggge22632-math-0002.png\">) from one of the anorthosite xenoliths is consistent with the anorthosite cumulate forming as part of the MCR and provides a maximum age constraint for the Beaver River diabase. Paired with the minimum age constraint of a cross-cutting Silver Bay intrusion (1091.61&nbsp;<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/b05c5aa4-956f-453e-ba10-381b109e0133/ggge22632-math-0003.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0003\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/b05c5aa4-956f-453e-ba10-381b109e0133/ggge22632-math-0003.png\">&nbsp;0.14&nbsp;Ma; 2<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/74d8c674-e7c9-491f-8561-e29a40e5ad6a/ggge22632-math-0004.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0004\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/74d8c674-e7c9-491f-8561-e29a40e5ad6a/ggge22632-math-0004.png\">), these data tightly bracket the age of the Beaver River diabase to be 1091.7&nbsp;<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/bfd7167e-2210-44f4-b9da-85fc7b8ffc11/ggge22632-math-0005.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0005\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/bfd7167e-2210-44f4-b9da-85fc7b8ffc11/ggge22632-math-0005.png\">&nbsp;0.2&nbsp;Ma (95% CI), coeval with the eruption of the Greenstone Flow (1091.59&nbsp;<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/58c6a54a-166d-44a3-bb92-1018e100d9ea/ggge22632-math-0006.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0006\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/58c6a54a-166d-44a3-bb92-1018e100d9ea/ggge22632-math-0006.png\">&nbsp;0.27&nbsp;Ma; 2<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/d7ad8f69-09ad-43e2-8ce2-a25ebfb23bfc/ggge22632-math-0007.png\" alt=\"urn:x-wiley:15252027:media:ggge22632:ggge22632-math-0007\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/d7ad8f69-09ad-43e2-8ce2-a25ebfb23bfc/ggge22632-math-0007.png\">)—which is further supported by indistinguishable tilt-corrected paleomagnetic pole positions. Geochronological, paleomagnetic, mineralogical and geochemical data are consistent with a hypothesis that the Beaver River diabase was the feeder system for the Greenstone Flow. The large areal extent of the intrusives and large estimated volume of the volcanics suggest that they represent a rapid and voluminous ca. 1,092&nbsp;Ma magmatic pulse near the end of the main stage of MCR magmatism.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC009909","usgsCitation":"Zhang, Y., Swanson-Hysell, N.L., Schmitz, M.D., Miller, J.D., and Avery, M.S., 2021, Synchronous emplacement of the anorthosite xenolith-bearing Beaver River diabase and one of the largest lava flows on Earth: Geochemistry, Geophysics, Geosystems, v. 22, no. 10, e2021GC009909, 22 p., https://doi.org/10.1029/2021GC009909.","productDescription":"e2021GC009909, 22 p.","ipdsId":"IP-129694","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450832,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gc009909","text":"External Repository"},{"id":421243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.90577234555566,\n              48.06224901293339\n            ],\n            [\n              -91.07032312680569,\n              48.01817567781583\n            ],\n            [\n              -92.30079187680585,\n              47.41949253986752\n            ],\n            [\n              -92.67432703305536,\n              46.934088430510485\n            ],\n            [\n              -92.42164148618046,\n              46.678416429667834\n            ],\n            [\n              -91.79542078305555,\n              46.663339052891985\n            ],\n            [\n              -90.2282388480374,\n              46.33984071282008\n            ],\n            [\n              -88.52149500180556,\n              46.94909012060117\n            ],\n            [\n              -87.75584248312727,\n              47.553729299542994\n            ],\n            [\n              -87.46099845631785,\n              48.31365303404988\n            ],\n            [\n              -87.78288626075643,\n              48.818624883339\n            ],\n            [\n              -88.2158152170627,\n              48.78531971959853\n            ],\n            [\n              -88.98592529428336,\n              48.68686039499511\n            ],\n            [\n              -89.36852550678222,\n              48.46528639990822\n            ],\n            [\n              -89.90577234555566,\n              48.06224901293339\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"22","issue":"10","noUsgsAuthors":false,"publicationDate":"2021-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Yiming 0000-0002-1407-302X","orcid":"https://orcid.org/0000-0002-1407-302X","contributorId":330186,"corporation":false,"usgs":false,"family":"Zhang","given":"Yiming","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":884401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swanson-Hysell, Nicholas L. 0000-0003-3215-4648","orcid":"https://orcid.org/0000-0003-3215-4648","contributorId":330223,"corporation":false,"usgs":false,"family":"Swanson-Hysell","given":"Nicholas","email":"","middleInitial":"L.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":884402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmitz, Mark D.","contributorId":292886,"corporation":false,"usgs":false,"family":"Schmitz","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":884403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, James D.","contributorId":330239,"corporation":false,"usgs":false,"family":"Miller","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":55466,"text":"University of Minnesota, Duluth","active":true,"usgs":false}],"preferred":false,"id":884404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avery, Margaret Susan 0000-0002-8504-7072","orcid":"https://orcid.org/0000-0002-8504-7072","contributorId":329991,"corporation":false,"usgs":true,"family":"Avery","given":"Margaret","email":"","middleInitial":"Susan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884405,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226194,"text":"70226194 - 2021 - First record of Najas marina (Hydrocharitaceae) for Montana and an update on the North American distribution","interactions":[],"lastModifiedDate":"2021-11-16T12:41:33.938688","indexId":"70226194","displayToPublicDate":"2021-09-13T06:39:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9916,"text":"Phytoneuron","active":true,"publicationSubtype":{"id":10}},"title":"First record of Najas marina (Hydrocharitaceae) for Montana and an update on the North American distribution","docAbstract":"Three recent collections of Najas marina (spiny water-nymph) from Missoula County, Montana are documented and illustrated. These collections are the first records for Montana and for the Pacific Northwest region. The occurrence of N. marina in Montana reflects a significant northward expansion of this species in the Mountain West. The North American distribution of this species is also updated.","language":"English","publisher":"Phytoneuron","usgsCitation":"Freeman, S.L., and Pfingsten, I., 2021, First record of Najas marina (Hydrocharitaceae) for Montana and an update on the North American distribution: Phytoneuron, v. 51, p. 1-7.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-129148","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":391725,"type":{"id":15,"text":"Index Page"},"url":"https://www.phytoneuron.net/wp-content/uploads/2021/09/51PhytoN-Najasmarina.pdf"},{"id":391732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -127.79296875,\n              5.61598581915534\n            ],\n            [\n              -58.71093750000001,\n              5.61598581915534\n            ],\n            [\n              -58.71093750000001,\n              50.958426723359935\n            ],\n            [\n              -127.79296875,\n              50.958426723359935\n            ],\n            [\n              -127.79296875,\n              5.61598581915534\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Freeman, Scott L. 0000-0002-4580-8885","orcid":"https://orcid.org/0000-0002-4580-8885","contributorId":268867,"corporation":false,"usgs":false,"family":"Freeman","given":"Scott","email":"","middleInitial":"L.","affiliations":[{"id":55706,"text":"Montana Fish, Wildlife & Parks Aquatic Invasive Species Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":826838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pfingsten, Ian 0000-0002-9456-9905","orcid":"https://orcid.org/0000-0002-9456-9905","contributorId":213997,"corporation":false,"usgs":true,"family":"Pfingsten","given":"Ian","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":826839,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70225650,"text":"70225650 - 2021 - Isolating detrital and diagenetic signals in magnetic susceptibility records from methane-bearing marine sediments","interactions":[],"lastModifiedDate":"2021-10-29T13:53:44.169617","indexId":"70225650","displayToPublicDate":"2021-09-12T08:48:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Isolating detrital and diagenetic signals in magnetic susceptibility records from methane-bearing marine sediments","docAbstract":"<p><span>Volume-dependent magnetic susceptibility (κ) is commonly used for paleoenvironmental reconstructions in both terrestrial and marine sedimentary environments where it reflects a mixed signal between primary deposition and secondary diagenesis. In the marine environment, κ is strongly influenced by the abundance of ferrimagnetic minerals regulated by sediment transport processes. Post-depositional alteration by H</span><sub>2</sub><span>S, however, can dissolve titanomagnetite, releasing reactive Fe that promotes pyritization and subsequently decreases κ. Here, we provide a new approach for isolating the detrital signal in κ and identifying intervals of diagenetic alteration of κ driven by organoclastic sulfate reduction (OSR) and the anaerobic oxidation of methane (AOM) in methane-bearing marine sediments offshore India. Using the correlation of a heavy mineral proxy from X-ray fluorescence data (Zr/Rb) and κ in unaltered sediments, we predict the primary detrital κ signal and identify intervals of decreased κ, which correspond to increased total sulfur content. Our approach is a rapid, high-resolution method that can identify overprinted κ resulting from pyritization of titanomagnetite due to H</span><sub>2</sub><span>S production in marine sediments. In addition, total organic carbon, total sulfur, and authigenic carbonate δ</span><sup>13</sup><span>C measurements indicate that both OSR and AOM can drive the observed κ loss, but AOM drives the greatest decreases in κ. Overall, our approach can enhance paleoenvironmental reconstructions and provide insight into paleo-positions of the sulfate-methane transition zone, past enhancements of OSR or paleo-methane seepage, and the role of detrital iron oxide minerals on the marine sediment sulfur sink, with consequences influencing the development of chemosynthetic biological communities at methane seeps.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC009867","usgsCitation":"Johnson, J.P., Phillips, S.C., Clyde, W., Giosan, L., and Torres, M.E., 2021, Isolating detrital and diagenetic signals in magnetic susceptibility records from methane-bearing marine sediments: Geochemistry, Geophysics, Geosystems, v. 22, no. 9, e2021GC009867, 21 p., https://doi.org/10.1029/2021GC009867.","productDescription":"e2021GC009867, 21 p.","ipdsId":"IP-129227","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gc009867","text":"Publisher Index Page"},{"id":391152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Krishna-Godavari Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              86.8798828125,\n              21.12549763660628\n            ],\n            [\n              80.6396484375,\n              16.003575733881327\n            ],\n            [\n              80.37597656249999,\n              14.221788628397572\n            ],\n            [\n              79.8486328125,\n              10.790140750321738\n            ],\n            [\n              87.5390625,\n              -0.04394530819134536\n            ],\n            [\n              92.63671875,\n              2.1967272417616712\n            ],\n            [\n              94.130859375,\n              7.972197714386879\n            ],\n            [\n              96.416015625,\n              10.617418067950293\n            ],\n            [\n              95.09765625,\n              15.241789855961722\n            ],\n            [\n              93.955078125,\n              16.551961721972525\n            ],\n            [\n              94.21875,\n              18.22935133838668\n            ],\n            [\n              92.021484375,\n              20.756113874762082\n            ],\n            [\n              86.8798828125,\n              21.12549763660628\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              73.740234375,\n              -1.5818302639606454\n            ],\n            [\n              72.99316406249999,\n              15.623036831528264\n            ],\n            [\n              70.751953125,\n              19.518375478601566\n            ],\n            [\n              65.830078125,\n              19.062117883514652\n            ],\n            [\n              65.2587890625,\n              9.709057068618208\n            ],\n            [\n              62.75390625,\n              0.4394488164139768\n            ],\n            [\n              68.9501953125,\n              -2.591888984149953\n            ],\n            [\n              73.740234375,\n              -1.5818302639606454\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"22","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Joel P. L.","contributorId":138502,"corporation":false,"usgs":false,"family":"Johnson","given":"Joel","email":"","middleInitial":"P. L.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":826063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clyde, William","contributorId":268178,"corporation":false,"usgs":false,"family":"Clyde","given":"William","email":"","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":826065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giosan, Liviu","contributorId":147870,"corporation":false,"usgs":false,"family":"Giosan","given":"Liviu","email":"","affiliations":[],"preferred":false,"id":826066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Torres, Marta E.","contributorId":196035,"corporation":false,"usgs":false,"family":"Torres","given":"Marta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":826067,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70243718,"text":"70243718 - 2021 - Modeling watershed carbon dynamics as affected by land cover change and soil erosion","interactions":[],"lastModifiedDate":"2024-05-16T15:35:29.430932","indexId":"70243718","displayToPublicDate":"2021-09-11T08:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling watershed carbon dynamics as affected by land cover change and soil erosion","docAbstract":"<p><span>Process-based ecosystem carbon cycle models typically incorporate vegetation growth, vegetation mortality, and soil respiration as well as the biotic and environmental drivers that influence these variables. However, few spatially explicit process models can efficiently incorporate the influence of land cover change and carbon lateral movement at regional scales or high spatial resolution. This study uses the Land Use and Carbon Scenario Simulator (LUCAS) to demonstrate the development of a fast ecosystem model that not only considers the basic carbon cycle but also incorporates the impact of land cover change, soil erosion, and soil deposition. As input to the LUCAS modeling framework, we used the integrated biosphere simulator (IBIS) to simulate a non-spatial reference carbon cycling scenario without considering land cover change for the Nisqually River watershed in the northwestern United States. We then used the Land Change Monitoring, Assessment, and Projection (LCMAP) remotely sensed 30-m sequential land cover data to generate annual land change history for the Nisqually River area from 1985 to 2017 and used the Unit Stream Powered Erosion and Deposition model (USPED) to estimate annual soil carbon lateral movement. Finally, we combined the annual carbon outputs from IBIS, the land change history from LCMAP, and the soil erosion and deposition from USPED within the LUCAS simulation framework. Results showed that from 1985 to 2017, along with the dynamic land cover changes, total ecosystem biomass carbon increased from 11.4 to 18.6 TgC, mainly due to forest growth. Total ecosystem soil carbon declined from 31.7 to 29.7 TgC, but the overall loss in soil carbon was not uniform across land cover types. Forestland (forest sector) and grassland lost carbon, while wetland, developed land and agricultural land gained carbon. Forest, grassland, and developed land lost 0.0553 TgC during the study period (1.73 Gg of C per year; 1 Gg&nbsp;=&nbsp;0.001 Tg) from erosion, while wetland gained 0.0071 TgC (0.22 Gg C per year) from deposition. Agricultural land was neutral in terms of soil erosion.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109724","usgsCitation":"Liu, J., Sleeter, B.M., Selmants, P., Diao, J., Zhou, Q., Worstell, B., and Moritsch, M.M., 2021, Modeling watershed carbon dynamics as affected by land cover change and soil erosion: Ecological Modelling, v. 459, 109724, 11 p., https://doi.org/10.1016/j.ecolmodel.2021.109724.","productDescription":"109724, 11 p.","ipdsId":"IP-129044","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450838,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109724","text":"Publisher Index Page"},{"id":436201,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A27GFH","text":"USGS data release","linkHelpText":"Simulated Nisqually River Watershed 30-m resolution 2017 ecosystem carbon variables from the LUCAS model"},{"id":417208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.16253640390157,\n              47.168168689027254\n            ],\n            [\n              -123.16253640390157,\n              46.28394294633836\n            ],\n            [\n              -121.7181395192194,\n              46.28394294633836\n            ],\n            [\n              -121.7181395192194,\n              47.168168689027254\n            ],\n            [\n              -123.16253640390157,\n              47.168168689027254\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"459","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":873046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selmants, Paul 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":192591,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul","email":"pselmants@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diao, Jiaojiao","contributorId":305505,"corporation":false,"usgs":false,"family":"Diao","given":"Jiaojiao","email":"","affiliations":[{"id":33416,"text":"Nanjing Forestry University, China","active":true,"usgs":false}],"preferred":false,"id":873048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhou, Qiang 0000-0002-1282-8177","orcid":"https://orcid.org/0000-0002-1282-8177","contributorId":265886,"corporation":false,"usgs":false,"family":"Zhou","given":"Qiang","affiliations":[{"id":54817,"text":"AFDS, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":873049,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Worstell, Bruce 0000-0001-8927-3336","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":305506,"corporation":false,"usgs":false,"family":"Worstell","given":"Bruce","affiliations":[{"id":66235,"text":"SGT Inc. Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":873050,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":873051,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70226208,"text":"70226208 - 2021 - Foraging behavior in a generalist snake (brown treesnake, Boiga irregularis) with implications for avian reintroduction and recovery","interactions":[],"lastModifiedDate":"2021-11-17T13:58:59.105732","indexId":"70226208","displayToPublicDate":"2021-09-11T07:50:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9922,"text":"Applied Animal Behavior Science","active":true,"publicationSubtype":{"id":10}},"title":"Foraging behavior in a generalist snake (brown treesnake, Boiga irregularis) with implications for avian reintroduction and recovery","docAbstract":"<div id=\"ab0010\" class=\"abstract author\"><div id=\"abs0010\"><p id=\"sp0045\">Broad foraging classifications, such as generalist or specialist forager, are generally beneficial for population management in defining expectations of typical behavior. However, better understanding as to how individual variance in behavior interfaces with management actions, such as control of an invasive predator (such as brown treesnakes;<span>&nbsp;</span><span><i><a class=\"topic-link\" title=\"Learn more about Boiga irregularis from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/boiga-irregularis\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/boiga-irregularis\">Boiga irregularis</a></i></span><span>) responsible for ecological collapse of a taxonomic group (birds), may affect conservation goals. In the context of predator control, better understanding of foraging ecology and prey specificity helps to ensure that food-based control programs are removing the target individuals. We sought to quantify whether differences in a dietary generalist snake species was measurable during captive trials using mice or birds as the prey choice. We presented snakes with prey choices that could be or are integrated with tools deployed by managers for control to directly relate choice or preference to management action. We collected wild brown treesnakes and classified them as bird eaters or of unknown diet based on food items present in their&nbsp;<a class=\"topic-link\" title=\"Learn more about digestive tract from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/digestive-tract\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/digestive-tract\">digestive tract</a>&nbsp;at the time of capture. In experimental tests, we used live birds and live mice in traps, as well as bird and mouse carrion presented on platforms, to measure interest, take rates, and repeatability (preference) by snakes. We found that all individuals spent more time investigating live birds than they did mice, independent of dietary history, which resulted in twice as many snakes being captured in traps with live birds compared to live mice. There was, however, roughly equal interest in mouse and bird carrion. Within individuals, there was evidence for decreased interest in mouse carrion, if individuals ate birds in the wild. Choice of carrion type was repeatable across trials, suggesting preference may exist. Overall, interest in both live mice and mouse carrion was greatest for medium-bodied snakes, while interest in bird carrion was independent of snake size. Our results indicate that management of invasive predators, including reptiles, may more rapidly achieve conservation targets when managers consider individual heterogeneity in behavior. For brown treesnakes more interested in birds, managers may remove more snakes if they use avian food lures; increased removal of avian specialists may facilitate avian recovery.</span></p></div></div><div id=\"ab0015\" class=\"abstract graphical\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.applanim.2021.105450","usgsCitation":"Nafus, M.G., Xiong, P.X., Paxton, E.H., Yackel Adams, A.A., and Goetz, S.M., 2021, Foraging behavior in a generalist snake (brown treesnake, Boiga irregularis) with implications for avian reintroduction and recovery: Applied Animal Behavior Science, v. 243, 105450, 8 p., https://doi.org/10.1016/j.applanim.2021.105450.","productDescription":"105450, 8 p.","ipdsId":"IP-122003","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":450841,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.applanim.2021.105450","text":"Publisher Index Page"},{"id":436202,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IPLH58","text":"USGS data release","linkHelpText":"Data on dietary preference by brown treesnakes on Guam"},{"id":391795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"243","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiong, Peter X.","contributorId":268881,"corporation":false,"usgs":false,"family":"Xiong","given":"Peter","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":826876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":826877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, Scott Michael 0000-0002-8705-5316","orcid":"https://orcid.org/0000-0002-8705-5316","contributorId":228868,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223695,"text":"sir20215084 - 2021 - Forecasting drought probabilities for streams in the northeastern United States","interactions":[],"lastModifiedDate":"2021-09-13T12:01:34.031419","indexId":"sir20215084","displayToPublicDate":"2021-09-10T14:10:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5084","displayTitle":"Forecasting Drought Probabilities for Streams in the Northeastern United States","title":"Forecasting drought probabilities for streams in the northeastern United States","docAbstract":"<p>Maximum likelihood logistic regression (MLLR) models for the northeastern United States forecast drought probability estimates for water flowing in rivers and streams using methods previously identified and developed. Streamflow data from winter months are used to estimate chances of hydrological drought during summer months. Daily streamflow data collected from 1,143 streamgages from April 1, 1877, through October 31, 2018, are used to provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February. This allows estimates of outcomes from 5 to 11 months ahead of their occurrence. Models specific to the northeastern United States were investigated and updated. The MLLR models of drought stream-flow probabilities utilize the explanatory power of temporally linked water flows. Models with strong drought streamflow probability correct-classification rates were produced for streams throughout the northeastern United States. A test of northeastern United States drought streamflow probability predictions found that overall correct-classification rates for drought streamflow probabilities in the northeastern United States exceeded 97 percent when predicting July 2019 drought probability using February 2019 monthly mean streamflow data. Using hydrological drought probability estimates in a water-management context informs understandings of possible future streamflow drought conditions in the northeastern United States, provides warnings of potential future drought conditions, and aids water-management decision making and responses to changing circumstances.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215084","usgsCitation":"Austin, S.H., 2021, Forecasting drought probabilities for streams in the northeastern United States: U.S. Geological Survey Scientific Investigations Report 2021–5084, 11 p., https://doi.org/10.3133/sir20215084.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"11","ipdsId":"IP-113685","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":388741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5084/sir20215084.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5084"},{"id":388740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5084/coverthb.jpg"},{"id":388742,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E3SK56","text":"USGS data release","linkHelpText":"Terms, statistics, and performance measures for maximum likelihood logistic regression models estimating hydrological drought probabilities in the northeastern United States (2019)"}],"country":"United States","state":"Connecticut, Delaware, Massachusetts, Maine, New Hampshire, New Jersey, New  York, Pennsylvania, Rhode Island, Virginia, Vermont, West Virginia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-71.860513,41.320248],[-72.983751,41.235364],[-73.643478,41.002171],[-73.785964,40.800862],[-72.245348,41.161217],[-72.273657,41.051533],[-72.116368,40.999796],[-71.869558,41.075046],[-72.39585,40.86666],[-73.23914,40.6251],[-74.206731,40.594569],[-74.209788,40.447407],[-73.995683,40.468707],[-73.971381,40.371709],[-74.090945,39.799978],[-74.850748,38.954538],[-74.933571,38.928519],[-74.905181,39.174945],[-75.165979,39.201842],[-75.542894,39.470447],[-75.511743,39.674313],[-75.587147,39.651012],[-75.401193,39.088762],[-75.06551,38.66103],[-75.057288,38.404738],[-75.87767,37.135604],[-76.023664,37.268971],[-75.712065,37.936082],[-75.846621,37.925785],[-75.938577,38.272329],[-76.188644,38.267434],[-76.320843,38.459862],[-76.190902,38.621092],[-76.308922,38.813346],[-76.205063,38.892726],[-76.333703,38.984607],[-76.168332,38.996546],[-76.27566,39.160304],[-75.986298,39.510398],[-76.497977,39.204697],[-76.438845,39.0529],[-76.559697,38.767443],[-76.329433,38.073986],[-77.040638,38.444618],[-77.256412,38.396755],[-77.175969,38.604113],[-77.26443,38.582845],[-77.286202,38.347025],[-77.024866,38.386791],[-76.910832,38.197073],[-76.265998,37.91138],[-76.339892,37.655966],[-76.722156,37.83668],[-76.252415,37.447274],[-76.475927,37.250543],[-76.300352,37.00885],[-76.780532,37.209336],[-76.482407,36.917364],[-76.058154,36.916947],[-75.867044,36.550754],[-83.645586,36.600002],[-82.895445,36.882145],[-82.722097,37.120168],[-81.968297,37.537798],[-82.39968,37.829935],[-82.638398,38.152157],[-82.595382,38.382712],[-82.181967,38.599384],[-82.068864,38.984878],[-81.759995,38.925828],[-81.814155,39.073478],[-81.692203,39.236091],[-80.865575,39.662751],[-80.602895,40.327869],[-80.652436,40.562544],[-80.52566,40.636068],[-80.519345,41.929168],[-78.868556,42.770258],[-79.061388,43.251349],[-78.370221,43.376505],[-76.952174,43.270692],[-76.235834,43.529256],[-76.133697,43.940356],[-76.360306,44.070907],[-76.312647,44.199044],[-74.946686,44.984665],[-71.502487,45.013367],[-71.443882,45.235462],[-70.898482,45.244088],[-70.684614,45.395071],[-70.688214,45.563981],[-70.259117,45.890755],[-70.290896,46.185838],[-70.057061,46.415036],[-69.997086,46.69523],[-69.22442,47.459686],[-69.066715,47.43024],[-69.0402,47.2451],[-68.893204,47.182974],[-68.292679,47.359476],[-67.991871,47.212042],[-67.790515,47.067921],[-67.803148,45.696127],[-67.476704,45.604157],[-67.489464,45.282653],[-67.390579,45.154114],[-67.145652,45.146667],[-66.986318,44.820657],[-68.049334,44.33073],[-68.22939,44.463496],[-68.191924,44.306675],[-68.339498,44.222893],[-68.3791,44.430049],[-68.529905,44.39907],[-68.528153,44.241263],[-68.982449,44.426195],[-69.031878,44.079036],[-69.259838,43.921427],[-69.851297,43.703581],[-70.026193,43.822587],[-70.176023,43.76079],[-70.810999,42.892375],[-70.772267,42.711064],[-70.595474,42.660336],[-70.996097,42.271222],[-70.754488,42.228673],[-70.471552,41.761563],[-70.008462,41.800786],[-70.169781,42.059736],[-70.082624,42.054657],[-69.935952,41.809422],[-69.976478,41.603664],[-70.329924,41.634578],[-70.902763,41.421061],[-70.658659,41.543385],[-70.708193,41.730959],[-71.19302,41.457931],[-71.21616,41.62549],[-71.304394,41.454502],[-71.19564,41.67509],[-71.342786,41.728506],[-71.455371,41.407962],[-71.860513,41.320248]],[[-77.038598,38.791513],[-77.002498,38.96541],[-77.0915,38.95651],[-77.038598,38.791513]]],[[[-70.59628,41.471905],[-70.450431,41.420703],[-70.496162,41.346452],[-70.802083,41.314207],[-70.59628,41.471905]]],[[[-70.092142,41.297741],[-69.960277,41.278731],[-70.256164,41.288123],[-70.092142,41.297741]]],[[[-74.144428,40.53516],[-74.219787,40.502603],[-74.120186,40.642201],[-74.144428,40.53516]]]]},\"properties\":{\"name\":\"Connecticut\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_va@usgs.gov\" data-mce-href=\"mailto:dc_va@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Summary</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-09-02","noUsgsAuthors":false,"publicationDate":"2021-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":822358,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70228957,"text":"70228957 - 2021 - Impacts of neonicotinoid seed treatments on the wild bee community in agricultural field margins","interactions":[],"lastModifiedDate":"2022-02-25T16:49:03.561846","indexId":"70228957","displayToPublicDate":"2021-09-10T10:32:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of neonicotinoid seed treatments on the wild bee community in agricultural field margins","docAbstract":"<p id=\"sp0035\"><span>Wild bees support global agroecosystems via&nbsp;pollination&nbsp;of agricultural crops and maintaining diverse plant communities. However, with an increased reliance on pesticides to enhance crop production, wild bee communities may inadvertently be affected through exposure to chemical residues. Laboratory and semi-field studies have demonstrated lethal and&nbsp;sublethal effects&nbsp;of neonicotinoids on limited genera (e.g.,&nbsp;</span><i>Apis</i>,<span>&nbsp;</span><i>Bombus</i>,<span>&nbsp;</span><i>Megachile</i>), yet full field studies evaluating impacts to wild bee communities remain limited. Here, we conducted a two-year field study to assess whether neonicotinoid seed treatment and presence in environmental media (e.g., soil, flowers) influenced bee nest and diet guild abundance and richness. In 2017 and 2018, we planted 23 Missouri agricultural fields to soybeans (<i>Glycine</i><span>&nbsp;</span>max) using one of three seed treatments: untreated (no insecticide), treated (imidacloprid), or previously-treated (untreated, but neonicotinoid use prior to 2017). During both years, wild bees were collected in study field margins monthly (May to September) in tandem with soil and flowers from fields and field margins that were analyzed for neonicotinoid residues. Insecticide presence in soils and flowers varied over the study with neonicotinoids infrequently detected in both years within margin flowers (0%), soybean flowers (&lt;1%), margin soils (&lt;8%), and field soils (~39%). Wild bee abundance and species richness were not significantly different among field treatments. In contrast, neonicotinoid presence in field soils was associated with significantly lower richness (ground- and aboveground-nesting, diet generalists) of wild bee guilds. Our findings support that soil remains an underexplored route of exposure and long-term persistence of neonicotinoids in field soils may lead to reduced diversity in regional bee communities. Future reduction or elimination of neonicotinoid seed treatment use on areas managed for wildlife may facilitate conservation goals to sustain viable, diverse wild bee populations.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147299","usgsCitation":"Main, A., Webb, E.B., Goyne, K.W., Abney, R., and Mengel, D.C., 2021, Impacts of neonicotinoid seed treatments on the wild bee community in agricultural field margins: Science of the Total Environment, v. 786, p. 1-9, https://doi.org/10.1016/j.scitotenv.2021.147299.","productDescription":"147299, 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-119464","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.147299","text":"Publisher Index 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,{"id":70229010,"text":"70229010 - 2021 - Estimating the effects of fish quality and size on the economic value of fishing in Oklahoma streams and rivers: A revealed preference and contingent behavior approach","interactions":[],"lastModifiedDate":"2022-02-25T15:14:48.652424","indexId":"70229010","displayToPublicDate":"2021-09-10T09:11:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the effects of fish quality and size on the economic value of fishing in Oklahoma streams and rivers: A revealed preference and contingent behavior approach","docAbstract":"<p><span>Fishing in Oklahoma’s rivers and streams provides a unique experience for anglers in the state. Despite its popularity, information on total demand and economic benefits associated with stream fishing is limited in the state. Research on the role of site quality indicators, such as fish size and quantity, on recreational fishing has shown mixed results. Whether fish size or quantity plays an important role in determining fishing demand and economic value may have important management implications. We estimated the demand and economic value of fishing under varying scenarios by using anglers’ responses to hypothetical behavioral questions related to fishing in Ozark Highland streams and rivers in Oklahoma. We asked how intended number of trips might change in the future given hypothetical increases in catch rates of fish, catch rates of trophy-sized fish, and catch rates of preferred fish species, in combination with anglers’ trip-related data. Under current conditions, we estimated consumer surplus per person per trip to be $55 and aggregate value across all stream anglers in Oklahoma to be $68.51 million. Changes in marginal benefits varied among hypothetical scenarios of fish size and abundance but was maximized with a 25% increase in catch rates of trophy-sized fish. The study findings contribute to the understanding of the economic benefit of fishing in streams and suggest that fish size, rather than fish quantity, is more important to stream anglers in the area.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2021.106116","usgsCitation":"Joshi, O., Chapagain, B., Long, J.M., York, B., and Taylor, A., 2021, Estimating the effects of fish quality and size on the economic value of fishing in Oklahoma streams and rivers: A revealed preference and contingent behavior approach: Fisheries Research, v. 244, 106116, 9 p., https://doi.org/10.1016/j.fishres.2021.106116.","productDescription":"106116, 9 p.","ipdsId":"IP-120278","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450846,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.fishres.2021.106116","text":"External 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Atlanta","active":true,"usgs":true}],"preferred":true,"id":836119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"York, B.","contributorId":280239,"corporation":false,"usgs":false,"family":"York","given":"B.","email":"","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":836120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, A.T.","contributorId":275887,"corporation":false,"usgs":false,"family":"Taylor","given":"A.T.","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":836121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224960,"text":"70224960 - 2021 - Understanding grass invasion, fire severity, and Acacia koa regeneration for forest restoration in Hawaiʻi Volcanoes National Park","interactions":[],"lastModifiedDate":"2021-10-08T12:02:25.032881","indexId":"70224960","displayToPublicDate":"2021-09-10T06:57:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Understanding grass invasion, fire severity, and Acacia koa regeneration for forest restoration in Hawaiʻi Volcanoes National Park","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">With invasive grasses increasing wildfire occurrence worldwide, a better understanding of the relationships between native plants, fire, and invasive grass is needed to help restoration plans facilitate ecosystem resilience. Invasive grasses are particularly problematic for altering fire regimes in the tropics, yet in Hawaiʻi, restoration sites are often planted with monocultures of the native tree<span>&nbsp;</span><span class=\"html-italic\">Acacia koa,</span><span>&nbsp;</span>which can promote grass growth via nitrogen fixation. This, combined with the difficulty of estimating pre-fire grass cover under thick canopies, complicates attempts to restore Hawaiian ecosystems. We studied the 2018 Keauhou Ranch Fire in Hawaiʻi to investigate three questions: (1) at what level of precision can pre-fire grass cover be accurately estimated from oblique aerial photos? (2) how are post-fire<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>regeneration densities affected by fire severity? and (3) how are post-fire<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>regeneration densities affected by pre-fire grass cover and its interaction with fire severity? We collected burn severity and post-fire regeneration data from 30 transects stratified across mid-elevation woodland, montane woodland, and montane shrubland communities. We evaluated visual estimates of pre-fire grass cover from oblique aerial imagery with quantitative in situ data from 60 unburned transects of the same cover types. Pre-fire estimates of grass cover categories were 67% accurate in montane woodland (<span class=\"html-italic\">n</span><span>&nbsp;</span>= 9) and 100% accurate in montane shrubland (<span class=\"html-italic\">n</span><span>&nbsp;</span>= 11), but only 20% accurate in mid-elevation woodland (<span class=\"html-italic\">n</span><span>&nbsp;</span>= 10). In montane woodlands with low pre-fire tree densities,<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>regeneration densities were higher with increased fire severity, but this trend reversed when pre-fire tree densities were high. We detected no effect of pre-fire grass cover, nor its interaction with fire severity, on<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>regeneration density. This indicates that restoration through the planting of<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>may be successful in promoting fire-resilient<span>&nbsp;</span><span class=\"html-italic\">A. koa</span><span>&nbsp;</span>forest, although there are potential issues to consider regarding the effects that<span>&nbsp;</span><span class=\"html-italic\">A. koa</span>’s grass promotion may have on other species within the ecosystem.<span>&nbsp;</span></div>","language":"English","publisher":"MDPI","doi":"10.3390/land10090962","usgsCitation":"Natalia, H., Yelenik, S.G., Durboraw, T., Cox, R., and Gill, N.S., 2021, Understanding grass invasion, fire severity, and Acacia koa regeneration for forest restoration in Hawaiʻi Volcanoes National Park: Land, v. 10, no. 9, 962, 20 p., https://doi.org/10.3390/land10090962.","productDescription":"962, 20 p.","ipdsId":"IP-131050","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":450851,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land10090962","text":"Publisher Index Page"},{"id":436203,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B3V59U","text":"USGS data release","linkHelpText":"Hawaii Volcanoes National Park plant community and fire severity data, 2018-2020"},{"id":390328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Volcanoes National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.53482055664062,\n              19.123112024698735\n            ],\n            [\n              -154.88388061523438,\n              19.123112024698735\n            ],\n            [\n              -154.88388061523438,\n              19.52355289169168\n            ],\n            [\n              -155.53482055664062,\n              19.52355289169168\n            ],\n            [\n              -155.53482055664062,\n              19.123112024698735\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Natalia, Hamilton","contributorId":267266,"corporation":false,"usgs":false,"family":"Natalia","given":"Hamilton","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":824865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":824866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durboraw, Tara","contributorId":267267,"corporation":false,"usgs":false,"family":"Durboraw","given":"Tara","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":824867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, Robert","contributorId":267268,"corporation":false,"usgs":false,"family":"Cox","given":"Robert","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":824868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gill, Nathan S.","contributorId":211061,"corporation":false,"usgs":false,"family":"Gill","given":"Nathan","email":"","middleInitial":"S.","affiliations":[{"id":38177,"text":"Department of Integrative Biology, University of Wisconsin-Madison, Madison","active":true,"usgs":false}],"preferred":false,"id":824869,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259936,"text":"70259936 - 2021 - A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano","interactions":[],"lastModifiedDate":"2024-10-30T22:43:56.097024","indexId":"70259936","displayToPublicDate":"2021-09-10T06:54:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano","docAbstract":"<p>Mayon is a basaltic andesitic, open-vent volcano characterized by persistent passive degassing from the summit at 2463&nbsp;m above sea level. Mid-size (&lt;0.1 km3) and mildly explosive eruptions and occasional phreatic eruptions have occurred approximately every 10&nbsp;years for over a hundred years. Mayon’s plumbing system structure, processes, and time scales driving its eruptions are still not well-known, despite being the most active volcano in the Philippines. We investigated the petrology and geochemistry of its crystal-rich lavas (~50 vol% phenocrysts) from nine historical eruptions between 1928 and 2009 and propose a conceptual model of the processes and magmatic architecture that led to the eruptions. The whole-rock geochemistry and mineral assemblage (plagioclase + orthopyroxene + clinopyroxene + Fe-Ti oxide ± olivine) of the lavas have remained remarkably homogenous (54 wt% SiO2,~4 wt% MgO) from 1928 to 2009. However, electron microscope images and microprobe analyses of the phenocrysts and the existence of three types of glomerocrysts testify to a range of magmatic processes, including long-term magma residence, magma mixing, crystallization, volatile fluxing, and degassing. Multiple mineral-melt geothermobarometers suggest a relatively thermally buffered system at 1050±25&nbsp;°C, with several magma residence zones, ranging from close to the surface, through reservoirs at ~4–5&nbsp;km, and as deep as ~ 20&nbsp;km. Diffusion chronometry on &gt;200 orthopyroxene crystals reveal magma mixing timescales that range from a few days to about 65&nbsp;years, but the majority are shorter than the decadal inter-eruptive repose period. This implies that magma intrusion at Mayon has been nearly continuous over the studied time period, with limited crystal recycling from one eruption to the next. The variety of plagioclase textures and zoning patterns reflect fluxing of volatiles from depth to shallower melts through which they eventually reach the atmosphere through an open conduit. The crystal-rich nature of the erupted magmas may have developed during each inter-eruptive period. We propose that Mayon has behaved over almost 100&nbsp;years as a steady state system, with limited variations in eruption frequency, degassing flux, magma composition, and crystal content that are mainly determined by the amount and composition of deep magma and volatile input in the system. We explore how Mayon volcano’s processes and working model can be related to other open-vent mafic and water-rich systems such as Etna, Stromboli, Villarrica, or Llaima. Finally, our understanding of open-vent, persistently active volcanoes is rooted in historical observations, but volcano behavior can evolve over longer time frames. We speculate that these volcanoes produce specific plagioclase textures that can be used to identify similar volcanic behavior in the geologic record.</p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-021-01486-9","usgsCitation":"Ruth, D.C., and Costa, F., 2021, A petrological and conceptual model of Mayon volcano (Philippines) as an example of an open-vent volcano: Bulletin of Volcanology, v. 83, 62, 28 p., https://doi.org/10.1007/s00445-021-01486-9.","productDescription":"62, 28 p.","ipdsId":"IP-123082","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467226,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-021-01486-9","text":"Publisher Index Page"},{"id":463239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Philippines","otherGeospatial":"Mayon volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              123.5101731400274,\n              13.501020877721444\n            ],\n            [\n              123.5101731400274,\n              13.33999591750549\n            ],\n            [\n              123.70654204522504,\n              13.33999591750549\n            ],\n            [\n              123.70654204522504,\n              13.501020877721444\n            ],\n            [\n              123.5101731400274,\n              13.501020877721444\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruth, Dawn Catherine Sweeney 0000-0001-9369-9364","orcid":"https://orcid.org/0000-0001-9369-9364","contributorId":334908,"corporation":false,"usgs":true,"family":"Ruth","given":"Dawn","email":"","middleInitial":"Catherine Sweeney","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":916875,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227783,"text":"70227783 - 2021 - The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting","interactions":[],"lastModifiedDate":"2022-01-31T16:09:37.311812","indexId":"70227783","displayToPublicDate":"2021-09-09T09:54:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting","docAbstract":"While growth history of vegetation within upland systems is well studied, plant phenology within coastal tidal systems is less understood. Landscape-scale, satellite-derived indicators of plant greenness may not adequately represent seasonality of vegetation biomass and productivity within tidal wetlands due to limitations of cloud cover, satellite temporal frequency and attenu-ation of plant signals by tidal flooding. However, understanding plant phenology is necessary to gain insight into aboveground biomass, photosynthetic activity, and carbon sequestration. In this study we use a modeling approach to estimate plant greenness throughout a year in tidal wet-lands located within the San Francisco Bay Area, USA. We used variables such as EVI history, temperature, and elevation to predict plant greenness on a 14-day timestep. We found this ap-proach accurately estimated plant greenness, with larger error observed within more dynamic restored wetlands, particularly at early post-restoration stages. We also found modeled EVI can be used as an input variable into greenhouse gas models, allowing for an estimate of carbon se-questration and gross primary production. Our strategy can be further developed in future re-search by assessing restoration and management effects on wetland phenological dynamics and through incorporating the entire Sentinel-2 time-series once it becomes available within Google Earth Engine.","language":"English","publisher":"MDPI","doi":"10.3390/rs13183589","collaboration":"=","usgsCitation":"Miller, G.J., Dronova, I., Oikawa, P., Knox, S., Windham-Myers, L., Shahan, J., and Stuart-Haëntjens, E., 2021, The potential of satellite remote sensing time series to uncover wetland phenology under unique challenges of tidal setting: Remote Sensing, v. 13, no. 18, p. 1-28, https://doi.org/10.3390/rs13183589.","productDescription":"3589, 28 p.","startPage":"1","endPage":"28","ipdsId":"IP-133045","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450854,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13183589","text":"Publisher Index Page"},{"id":395144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Francisco Bay Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.728271484375,\n              37.276238364942955\n            ],\n            [\n              -121.75872802734375,\n              37.276238364942955\n            ],\n            [\n              -121.75872802734375,\n              38.26406296833961\n            ],\n            [\n              -122.728271484375,\n              38.26406296833961\n            ],\n            [\n              -122.728271484375,\n              37.276238364942955\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"18","noUsgsAuthors":false,"publicationDate":"2021-09-09","publicationStatus":"PW","contributors":{"editors":[{"text":"Bostater, Charles R. Jr.","contributorId":272837,"corporation":false,"usgs":false,"family":"Bostater","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832310,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Miller, Gwendolyn Joelle 0000-0002-5712-945X","orcid":"https://orcid.org/0000-0002-5712-945X","contributorId":272606,"corporation":false,"usgs":false,"family":"Miller","given":"Gwendolyn","email":"","middleInitial":"Joelle","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":832226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dronova, Iryna 0000-0003-3339-3704","orcid":"https://orcid.org/0000-0003-3339-3704","contributorId":272607,"corporation":false,"usgs":false,"family":"Dronova","given":"Iryna","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":832227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oikawa, Patricia","contributorId":272608,"corporation":false,"usgs":false,"family":"Oikawa","given":"Patricia","affiliations":[{"id":56387,"text":"CSU East Bay","active":true,"usgs":false}],"preferred":false,"id":832228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Sara Helen 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":272609,"corporation":false,"usgs":false,"family":"Knox","given":"Sara Helen","affiliations":[{"id":56388,"text":"U. British Columbia","active":true,"usgs":false}],"preferred":false,"id":832229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Windham-Myers, Lisamarie","contributorId":272610,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shahan, Julie","contributorId":272611,"corporation":false,"usgs":false,"family":"Shahan","given":"Julie","email":"","affiliations":[{"id":56387,"text":"CSU East Bay","active":true,"usgs":false}],"preferred":false,"id":832231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stuart-Haëntjens, Ellen 0000-0001-9901-7643","orcid":"https://orcid.org/0000-0001-9901-7643","contributorId":265857,"corporation":false,"usgs":true,"family":"Stuart-Haëntjens","given":"Ellen","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832232,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231624,"text":"70231624 - 2021 - Impacts of climate changes and amplified natural disturbance on global ecosystems","interactions":[],"lastModifiedDate":"2022-05-17T14:37:03.37095","indexId":"70231624","displayToPublicDate":"2021-09-09T09:33:56","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Impacts of climate changes and amplified natural disturbance on global ecosystems","docAbstract":"<p><span>Natural disturbances maintain biological diversity and landscape heterogeneity and initiate ecosystem renewal and reorganization. However, the severity, frequency, and extent of many disturbances have increased substantially in recent decades as the result of anthropogenic climate change. Disturbances can be discrete, short-duration events, such as wildfires or hurricanes, or can exert persistent, cumulative stresses on an ecosystem (for example, ongoing warming of ocean or land surface temperatures). Landscape and ecosystem impacts can occur from a single disturbance, from several disturbances acting independently, or from the interactions of multiple, linked disturbances. Key, climate-related disturbances affecting global biomes and ecosystems include shifting temperature and hydrologic regimes (for example, warming surface temperatures and increasing aridity), increased frequency and magnitude of extreme events such as heatwaves, severe droughts, storms, and hurricanes, warming-induced permafrost thaw, and heightened wildfire activity and insect-caused tree mortality. For ecosystems and landscapes, the consequences of climate-amplified disturbance include forced poleward and upward movement of plant and animal species, widespread tree mortality and reduced forest productivity, changes in plant community structure and species distributions, reduced biodiversity, increased erosion, debris flows, wetland dynamism, declining sea ice extent, more frequent storm-driven tides and saltwater intrusion, and increased landscape flammability.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Routledge handbook of landscape ecology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge","doi":"10.4324/9780429399480-11","usgsCitation":"Loehman, R.A., Friggens, M., Sherriff, R., Keyser, A.R., and Riley, K.L., 2021, Impacts of climate changes and amplified natural disturbance on global ecosystems, chap. <i>of</i> Routledge handbook of landscape ecology, p. 175-198, https://doi.org/10.4324/9780429399480-11.","productDescription":"24 p.","startPage":"175","endPage":"198","ipdsId":"IP-108658","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":400700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":843150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friggens, Megan","contributorId":219865,"corporation":false,"usgs":false,"family":"Friggens","given":"Megan","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":843151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherriff, Rosemary L.","contributorId":243263,"corporation":false,"usgs":false,"family":"Sherriff","given":"Rosemary L.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":843152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keyser, Alisa R.","contributorId":248331,"corporation":false,"usgs":false,"family":"Keyser","given":"Alisa","email":"","middleInitial":"R.","affiliations":[{"id":49860,"text":"Univ. of New Mexico","active":true,"usgs":false}],"preferred":false,"id":843153,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Karin L.","contributorId":169453,"corporation":false,"usgs":false,"family":"Riley","given":"Karin","email":"","middleInitial":"L.","affiliations":[{"id":25512,"text":"US Forest Service Fire Science Lab","active":true,"usgs":false}],"preferred":false,"id":843154,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223887,"text":"70223887 - 2021 - Phenotypic variation in Brook Trout Salvelinus fontinalis (Mitchill) at broad spatial scales makes morphology an insufficient basis for taxonomic reclassification of the species","interactions":[],"lastModifiedDate":"2021-09-13T14:09:17.279058","indexId":"70223887","displayToPublicDate":"2021-09-09T09:01:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9341,"text":"Ichthyology & Herpetology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Phenotypic variation in Brook Trout <i>Salvelinus fontinalis</i> (Mitchill) at broad spatial scales makes morphology an insufficient basis for taxonomic reclassification of the species","title":"Phenotypic variation in Brook Trout Salvelinus fontinalis (Mitchill) at broad spatial scales makes morphology an insufficient basis for taxonomic reclassification of the species","docAbstract":"<p><span>It was recently proposed that there are three new species of&nbsp;</span><i>Salvelinus</i><span>&nbsp;with microendemic distributions in the Great Smoky Mountains National Park, Tennessee, USA. The three species of&nbsp;</span><i>Salvelinus</i><span>&nbsp;were hypothesized to be distinct from their congener Brook Trout&nbsp;</span><i>S. fontinalis</i><span>&nbsp;based on three meristic traits—pored lateral-line scales, vertebral counts, and number of basihyal teeth. After analyses that included specimens sampled from a larger portion of the geographic range of&nbsp;</span><i>S. fontinalis</i><span>, we conclude that the three populations of&nbsp;</span><i>Salvelinus</i><span>&nbsp;recently described as new species are not morphometrically distinct from Brook Trout and consider all three to be synonyms of&nbsp;</span><i>S. fontinalis</i><span>. Moreover, the low number of specimens originally examined conflates morphological differences among populations with sexual dimorphism and/or phenotypic plasticity, both of which are documented extensively in Brook Trout but were not controlled for in the species descriptions. While there is currently insufficient phenotypic or genotypic evidence to support the hypothesis of three new species that are distinct from&nbsp;</span><i>S. fontinalis</i><span>, we acknowledge the need to understand the unique selection pressures that shape evolutionary trajectories in small, isolated populations of Brook Trout and to conserve evolutionarily significant sources of genotypic and phenotypic diversity. To that end, we provide comments on research opportunities to support Brook Trout conservation, including the importance of collaborative, range-wide phylogenetic studies to identify the most appropriate scales of management efforts.</span></p>","language":"English","publisher":"American Society of Ichthyologists and Herpetologists","doi":"10.1643/i2020154","usgsCitation":"White, S.L., Kazyak, D., Harrington, R.C., Kulp, M.A., Rash, J.M., Weathers, T.C., and Near, T.J., 2021, Phenotypic variation in Brook Trout Salvelinus fontinalis (Mitchill) at broad spatial scales makes morphology an insufficient basis for taxonomic reclassification of the species: Ichthyology & Herpetology, v. 109, no. 3, p. 743-751, https://doi.org/10.1643/i2020154.","productDescription":"9 p.","startPage":"743","endPage":"751","ipdsId":"IP-124765","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1643/i2020154","text":"Publisher Index Page"},{"id":389145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Tennessee","otherGeospatial":"Great Smoky Mountains Park, Long Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.38317871093749,\n              40.72644570551446\n            ],\n            [\n              -72.88330078125,\n              40.72644570551446\n            ],\n            [\n              -72.88330078125,\n              40.925964939514294\n            ],\n            [\n              -73.38317871093749,\n              40.925964939514294\n            ],\n            [\n              -73.38317871093749,\n              40.72644570551446\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.111328125,\n              35.36217605914681\n            ],\n            [\n              -82.93853759765625,\n              35.36217605914681\n            ],\n            [\n              -82.93853759765625,\n              35.871246850027966\n            ],\n            [\n              -84.111328125,\n              35.871246850027966\n            ],\n            [\n              -84.111328125,\n              35.36217605914681\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"109","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":823091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":823092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, Richard C","contributorId":265606,"corporation":false,"usgs":false,"family":"Harrington","given":"Richard","email":"","middleInitial":"C","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":823093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulp, Matt A.","contributorId":196801,"corporation":false,"usgs":false,"family":"Kulp","given":"Matt","email":"","middleInitial":"A.","affiliations":[{"id":35484,"text":"National Park Service, Great Smoky Mountains National Park","active":true,"usgs":false}],"preferred":false,"id":823094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rash, Jacob M","contributorId":218128,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","email":"","middleInitial":"M","affiliations":[{"id":39760,"text":"Division of Inland Fisheries, North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":823095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weathers, T. Casey","contributorId":218129,"corporation":false,"usgs":false,"family":"Weathers","given":"T.","email":"","middleInitial":"Casey","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":823155,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Near, Thomas J","contributorId":265607,"corporation":false,"usgs":false,"family":"Near","given":"Thomas","email":"","middleInitial":"J","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":823096,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70224262,"text":"70224262 - 2021 - If you give a clam an estuary: The story of potamocorbula","interactions":[],"lastModifiedDate":"2021-09-16T13:06:17.362712","indexId":"70224262","displayToPublicDate":"2021-09-09T08:04:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9348,"text":"Frontiers for Young Minds","active":true,"publicationSubtype":{"id":10}},"title":"If you give a clam an estuary: The story of potamocorbula","docAbstract":"When you look at San Francisco Bay, what animals do you see? You may see lots of fish swimming around and birds flying above. What you DON’T see is Potamocorbula, a little clam that has had a big impact. Many years ago, ships accidentally brought Potamocorbula into the Bay. Pretty soon, Potamocorbula spread out all over in large numbers! Clams pump water over their gills and eat small particles of food, like phytoplankton, that pass through with the water. Potamocorbula can pump water much faster than other clams that live in the Bay, and they can eat more than their share of phytoplankton. Sometimes Potamocorbula eats phytoplankton faster than phytoplankton can grow! What problems does that cause for other animals, like birds and fish, that also need phytoplankton? Does Potamocorbula’s invasion only have negative impacts? In this article, we dive to the bottom of the Bay to find some answers.\n\nBook series publishing the chapter: https://kids.frontiersin.org/collection/13528/where-the-river-meets-the-ocean-stories-from-san-francisco-estuary","language":"English","publisher":"Frontiers","doi":"10.3389/frym.2021.599289","usgsCitation":"Shrader, K., Zierdt Smith, E.L., Parchaso, F., and Thompson, J.K., 2021, If you give a clam an estuary: The story of potamocorbula: Frontiers for Young Minds, https://doi.org/10.3389/frym.2021.599289.","ipdsId":"IP-120502","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":450858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frym.2021.599289","text":"Publisher Index Page"},{"id":389334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.134765625,\n              37.405073750176925\n            ],\n            [\n              -121.55273437499999,\n              37.405073750176925\n            ],\n            [\n              -121.55273437499999,\n              38.37611542403604\n            ],\n            [\n              -123.134765625,\n              38.37611542403604\n            ],\n            [\n              -123.134765625,\n              37.405073750176925\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2021-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Shrader, Kelly H. 0000-0001-6550-7425","orcid":"https://orcid.org/0000-0001-6550-7425","contributorId":215872,"corporation":false,"usgs":true,"family":"Shrader","given":"Kelly H.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":823393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zierdt Smith, Emily L. 0000-0003-0787-1856 ezierdtsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0787-1856","contributorId":220320,"corporation":false,"usgs":true,"family":"Zierdt Smith","given":"Emily","email":"ezierdtsmith@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":823394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":823395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":823396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70223891,"text":"70223891 - 2021 - The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits","interactions":[],"lastModifiedDate":"2021-10-06T15:58:41.800728","indexId":"70223891","displayToPublicDate":"2021-09-09T07:50:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\"><div id=\"as0005\"><p id=\"sp0075\">Siliceous sinter is formed by biogenic and abiogenic opal deposition around hot springs and geysers. Using Structure-from-Motion photogrammetry we generated three-dimensional models of Giant and Castle Geysers from the Upper Geyser Basin of Yellowstone National Park. We use these models to calculate an approximate mass of sinter for each (~2 and ~ 5 kton, respectively) and estimate a range of plausible long-term deposition rates for Castle Geyser (470 to 940 kg·yr<sup>−1</sup>). We estimate ~2% of the silica discharged from Castle Geyser is deposited as sinter in the cone and proximal terraces. We collected 15 sinter samples following the stratigraphy of each geyser from an older terrace to a younger cone and examined them using a variety of analytical methods. We find that young opaline sinter with a water content of &lt;12 wt% (from loss on ignition) contains higher concentrations of major and trace elements, notably As, Sb, Rb, Ga and Cs, relative to older dehydrated sinter. Rare earth element (REE) concentrations in sinter are 2–3 orders of magnitude higher than in the thermal water from which they are deposited. Sinter deposits are enriched in light REE, Gd and Yb when normalized to concentrations in thermal water and enriched in Eu, Tm, and Yb when normalized to the underlying rhyolite. Sinter samples with the highest REE concentrations are also enriched in organic material, implying either microbial uptake of REE, or that organic molecules are efficient ligands that form metal complexes.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107391","usgsCitation":"Churchill, D., Manga, M., Hurwitz, S., Peek, S., Damby, D., Conrey, R., Wood, J.R., McCleskey, R., Keller, W.E., Hosseini, B., and Hungerford, J.D., 2021, The structure and volume of large geysers in Yellowstone National Park, USA and the mineralogy and chemistry of their silica sinter deposits: Journal of Volcanology and Geothermal Research, v. 419, 107391, 17 p., https://doi.org/10.1016/j.jvolgeores.2021.107391.","productDescription":"107391, 17 p.","ipdsId":"IP-130151","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":450859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107391","text":"Publisher Index Page"},{"id":389139,"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              -111.03881835937499,\n              43.43696596521823\n            ],\n            [\n              -108.69873046875,\n              43.43696596521823\n            ],\n            [\n              -108.69873046875,\n              45.01918507438176\n            ],\n            [\n              -111.03881835937499,\n              45.01918507438176\n            ],\n            [\n              -111.03881835937499,\n              43.43696596521823\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Churchill, Dakota 0000-0003-3382-5562","orcid":"https://orcid.org/0000-0003-3382-5562","contributorId":265639,"corporation":false,"usgs":false,"family":"Churchill","given":"Dakota","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":823143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael 0000-0003-3286-4682","orcid":"https://orcid.org/0000-0003-3286-4682","contributorId":265640,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":823144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Conrey, Richard","contributorId":265641,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","affiliations":[{"id":54747,"text":"Hamilton College","active":true,"usgs":false}],"preferred":false,"id":823148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, John R.","contributorId":265642,"corporation":false,"usgs":false,"family":"Wood","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","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":823150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keller, William E.","contributorId":265643,"corporation":false,"usgs":false,"family":"Keller","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hosseini, Behnaz","contributorId":265644,"corporation":false,"usgs":false,"family":"Hosseini","given":"Behnaz","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hungerford, Jefferson D.G.","contributorId":265645,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","email":"","middleInitial":"D.G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
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