{"pageNumber":"316","pageRowStart":"7875","pageSize":"25","recordCount":41075,"records":[{"id":70215325,"text":"70215325 - 2019 - Population characteristics and the potential suppression of common carp in Lake Spokane, Washington","interactions":[],"lastModifiedDate":"2020-10-16T14:10:58.363964","indexId":"70215325","displayToPublicDate":"2019-12-01T09:06:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population characteristics and the potential suppression of common carp in Lake Spokane, Washington","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>Common Carp<span>&nbsp;</span><i>Cyprinus carpio</i><span>&nbsp;</span>is a nonnative species that often has deleterious effects on aquatic systems. As such, there is interest in suppressing nonnative Common Carp populations in areas where humans have introduced them. The objectives of this study were to 1) provide insight on efficient techniques for capturing Common Carp, 2) describe their population demographics and dynamics, 3) evaluate whether temperature and water elevation were related to growth and recruitment, and 4) develop an age-structured population model for evaluating different management scenarios of Common Carp removal in Lake Spokane, Washington. Catch rates of Common Carp varied among sampling gears with slightly higher catch rates in monofilament (mean ± SD; 15.5 ± 9.8 fish/net night) vs. multifilament (12.7 ± 7.3 fish/net night) gill nets. Catch rates of Common Carp with nighttime electrofishing (0.3 ± 0.4 fish/min) were higher than daytime electrofishing (0.1 ± 0.2 fish/min). Common Carp in Lake Spokane exhibited variable recruitment, rapid growth, large-length structure, high longevity (i.e., age 18 y), and low total annual mortality (17.0%). Air temperature was positively associated with annual growth increments (<i>R</i><sup>2</sup><span>&nbsp;</span>≤ 0.25). Neither air temperature nor water elevation was highly correlated (<i>R</i><sup>2</sup><span>&nbsp;</span>≤ 0.20) to recruitment of Common Carp. A Beverton–Holt yield-per-recruit model suggested that yield declined with increasing exploitation. Recruitment overfishing would occur at exploitation rates of 20–40% for all targeted minimum length categories (i.e., 150, 300, 450 mm) except 600 mm. Results from this study provide important information on the ecology of Common Carp that can be used to guide management efforts (e.g., suppression) in western systems.</p></div>","language":"English","publisher":"Allen Press","doi":"10.3996/122018-JFWM-114","usgsCitation":"Feeken, S., Klein, Z.B., Quist, M.C., and Horner, N., 2019, Population characteristics and the potential suppression of common carp in Lake Spokane, Washington: Journal of Fish and Wildlife Management, v. 10, no. 2, p. 362-374, https://doi.org/10.3996/122018-JFWM-114.","productDescription":"13 p.","startPage":"362","endPage":"374","ipdsId":"IP-103296","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":459068,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/122018-jfwm-114","text":"Publisher Index Page"},{"id":379465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Spokane","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.87094116210936,\n              47.75917578613814\n            ],\n            [\n              -117.52143859863281,\n              47.75917578613814\n            ],\n            [\n              -117.52143859863281,\n              47.91542163178686\n            ],\n            [\n              -117.87094116210936,\n              47.91542163178686\n            ],\n            [\n              -117.87094116210936,\n              47.75917578613814\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Feeken, Stacey","contributorId":243200,"corporation":false,"usgs":false,"family":"Feeken","given":"Stacey","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":801726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klein, Zachary B.","contributorId":171709,"corporation":false,"usgs":false,"family":"Klein","given":"Zachary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":801727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":801725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horner, Ned","contributorId":243201,"corporation":false,"usgs":false,"family":"Horner","given":"Ned","affiliations":[{"id":48661,"text":"Private","active":true,"usgs":false}],"preferred":false,"id":801728,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70207160,"text":"70207160 - 2019 - Managing effects of drought in Hawai’i and U.S.-affiliated Pacific Islands","interactions":[],"lastModifiedDate":"2020-12-08T16:49:59.298008","indexId":"70207160","displayToPublicDate":"2019-12-01T08:14:15","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"WO-98","chapter":"5","title":"Managing effects of drought in Hawai’i and U.S.-affiliated Pacific Islands","docAbstract":"<p>How is drought expressed in Hawai‘i &amp; USAPI? Drought is a significant climate feature in Hawai‘i and the U.S.-Affiliated Pacific Islands (USAPI), at times causing severe impacts across multiple sectors. Below average precipitation anomalies are often accompanied by higher than average temperatures and reduced cloud cover. The resulting higher insolation and evapotranspiration can magnify the effects of rainfall deficits. These altered meteorological conditions lead to decreased soil moisture, which, depending on the persistence and severity of the conditions, can cause plant stress, affecting both agricultural and natural systems. The hydrological effects of drought include reductions in streamflow, groundwater recharge, and groundwater discharge to springs, streams, and the ocean. Drought also has socioeconomic impacts, where reduced water supply and other effects of drought have negative financial consequences. For these reasons, drought has been defined from at least five different perspectives: meteorological, ecological, agricultural, hydrological, and socioeconomic drought. In this chapter, we explore how these five faces of drought are expressed in Hawai‘i and the USAPI, and how managers operating within one or more these five perspectives address drought-related stressors to their systems. Not all droughts are the same, varying with respect to duration, frequency, extent, and severity. For example, the region receives severe episodic droughts during which an area will have little or no rainfall for months, even in areas that normally have no dry season. El Niño events fall into this category, and these moderate frequency events are typically responsible for shorter-lived but intense drought events that affect large areas. Drought can also be expressed as infrequent but long duration events of moderate severity, or long-term rainfall decline where the baseline condition appears to be changing when examined on longer time scales. From the perspective of the manager, understanding drought duration, frequency, extent, and severity is critical to understanding the duration, frequency, extent and severity of the response. For example, how an agency responds to El Niño events, with a focus on large-scale but short-lived emergency response campaigns, may differ from how an agency responds to baseline change or an increase in the frequency of extended dry periods, with a focus on longer-lived institutional, infrastructure, and personnel responses. The legislative and policy environment will also respond differently to different types of drought. Understanding and characterizing meteorological drought relies on a long-term network of climate stations. Rainfall has been extensively monitored in Hawai‘i since the early 1900s owing to the expansion of plantation agriculture (Giambelluca and others 1986), while rainfall monitoring for most of the USAPI began in earnest after World War II (Polhemus 2017). Due to prevailing winds, most of Hawai‘i’s land area is characterized by a wet season from November to April and a dry season from May to October. However, important dynamic features affect climate systems of the Pacific. For example, due to their tropical location, rainfall patterns in both Hawai‘i and the USAPI are strongly controlled by large-scale modes of climate variability, including the El Niño-Southern Oscillation (ENSO). El Niño events are typically associated with drier than average winter wet seasons and wetter dry seasons, while La Niña events often result in a wetter than average wet season and a drier dry season. Many historical drought events have been attributed to El Niño events, which produce atmospheric conditions that are unfavorable for rainfall (Chu 1995). However, not all El Niño events result in drought, and effects differ depending on whether the El Niño is classified as Central Pacific (CP) or Eastern Pacific (EP) (Bai 2017; Polhemus 2017).&nbsp;</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of drought on forests and rangelands in the United States: Translating science into management responses","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"USDA","doi":"10.2737/WO-GTR-98","usgsCitation":"Frazier, A.G., Deenik, J., Fujii, N., Funderburk, G., Giambelluca, T., Giardina, C., Helweg, D., Keener, V., Mair, D., Marra, J., McDaniel, S., Ohye, L., Oki, D.S., Parsons, E., Strauch, A., and Trauernicht, C., 2019, Managing effects of drought in Hawai’i and U.S.-affiliated Pacific Islands: General Technical Report WO-98, 27 p., https://doi.org/10.2737/WO-GTR-98.","productDescription":"27 p.","startPage":"95","endPage":"121","ipdsId":"IP-105580","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":467312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2737/wo-gtr-98","text":"Publisher Index Page"},{"id":370145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"U.S. Pacific Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -161.7626953125,\n              17.895114303749143\n            ],\n            [\n              -153.5009765625,\n              17.895114303749143\n            ],\n            [\n              -153.5009765625,\n              23.52370005882413\n            ],\n            [\n              -161.7626953125,\n              23.52370005882413\n            ],\n            [\n              -161.7626953125,\n              17.895114303749143\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Frazier, Abby G.","contributorId":221112,"corporation":false,"usgs":false,"family":"Frazier","given":"Abby","email":"","middleInitial":"G.","affiliations":[{"id":40321,"text":"USDA Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":777050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deenik, Jonathan","contributorId":221113,"corporation":false,"usgs":false,"family":"Deenik","given":"Jonathan","email":"","affiliations":[{"id":40322,"text":"East-West Center, Honolulu, HI","active":true,"usgs":false}],"preferred":false,"id":777051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujii, Neal","contributorId":221114,"corporation":false,"usgs":false,"family":"Fujii","given":"Neal","email":"","affiliations":[{"id":40323,"text":"University of Hawai‘i at Mānoa, Department of Tropical Plant and Soil Sciences","active":true,"usgs":false}],"preferred":false,"id":777052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funderburk, Greg","contributorId":221115,"corporation":false,"usgs":false,"family":"Funderburk","given":"Greg","email":"","affiliations":[{"id":40324,"text":"Hawai‘i Volcanoes National Park, Hawai‘i, USA","active":true,"usgs":false}],"preferred":false,"id":777053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giambelluca, Thomas ","contributorId":221116,"corporation":false,"usgs":false,"family":"Giambelluca","given":"Thomas ","affiliations":[{"id":40325,"text":"University of Hawai‘i at Mānoa, Department of Geography","active":true,"usgs":false}],"preferred":false,"id":777054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giardina, Christian ","contributorId":221117,"corporation":false,"usgs":false,"family":"Giardina","given":"Christian ","affiliations":[{"id":40321,"text":"USDA Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":777055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Helweg, David A. 0000-0002-8640-9856","orcid":"https://orcid.org/0000-0002-8640-9856","contributorId":221111,"corporation":false,"usgs":true,"family":"Helweg","given":"David A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":777049,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keener, Victoria ","contributorId":196013,"corporation":false,"usgs":false,"family":"Keener","given":"Victoria ","affiliations":[],"preferred":false,"id":777056,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mair, Donald","contributorId":221118,"corporation":false,"usgs":true,"family":"Mair","given":"Donald","email":"","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777057,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marra, John ","contributorId":221119,"corporation":false,"usgs":false,"family":"Marra","given":"John ","affiliations":[{"id":40326,"text":"NOAA, National Environmental Satellite, Data, and Information Service","active":true,"usgs":false}],"preferred":false,"id":777058,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McDaniel, Sierra","contributorId":221120,"corporation":false,"usgs":false,"family":"McDaniel","given":"Sierra","email":"","affiliations":[{"id":40324,"text":"Hawai‘i Volcanoes National Park, Hawai‘i, USA","active":true,"usgs":false}],"preferred":false,"id":777059,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ohye, Lenore","contributorId":221121,"corporation":false,"usgs":false,"family":"Ohye","given":"Lenore","email":"","affiliations":[{"id":40327,"text":"State of Hawai‘i, Department of Land and Natural Resources, Commission on Water Resource Management","active":true,"usgs":false}],"preferred":false,"id":777060,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oki, Delwyn S. 0000-0002-6913-8804","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":221122,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777061,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Parsons, Elliott","contributorId":221123,"corporation":false,"usgs":false,"family":"Parsons","given":"Elliott","affiliations":[{"id":40328,"text":"State of Hawai‘i Division of Forestry and Wildlife, Pu‘u Wa‘awa‘a Forest Reserve","active":true,"usgs":false}],"preferred":false,"id":777062,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Strauch, Ayron","contributorId":221124,"corporation":false,"usgs":false,"family":"Strauch","given":"Ayron","email":"","affiliations":[{"id":40327,"text":"State of Hawai‘i, Department of Land and Natural Resources, Commission on Water Resource Management","active":true,"usgs":false}],"preferred":false,"id":777063,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Trauernicht, Clay","contributorId":221125,"corporation":false,"usgs":false,"family":"Trauernicht","given":"Clay","email":"","affiliations":[{"id":40329,"text":"University of Hawai‘i at Mānoa, Department of Natural Resources and Environmental Management","active":true,"usgs":false}],"preferred":false,"id":777064,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70216464,"text":"70216464 - 2019 - A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","interactions":[],"lastModifiedDate":"2020-11-20T14:11:15.783736","indexId":"70216464","displayToPublicDate":"2019-12-01T07:59:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3310,"text":"Rocky Mountain Geology","active":true,"publicationSubtype":{"id":10}},"title":"A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.","docAbstract":"<p><span>Interpretation of gravity, magnetotelluric, and aeromagnetic data in conjunction with geologic constraints reveals details of basin geometry, thickness, and spatiotemporal evolution of the southern San Luis Basin, one of the major basins of the northern Rio Grande rift. Spatial variations of low-density basin-fill thickness are estimated primarily using a 3D gravity inversion method that improves on previous modeling efforts by separating the effects of the low-density basin fill from the effects of pre-rift rocks. The basin is found to be significantly narrower—and more complex in the subsurface—than indicated or implied by previous modeling efforts. The basin is also estimated to be significantly shallower than previously estimated. Five distinct subbasins are recognized within the broader southern San Luis Basin. The oldest and shallowest subbasin is the Las Mesitas graben along the northwestern basin margin, formed during the Oligocene transition from Southern Rocky Mountain volcanic field magmatism to rifting. In this subbasin, sediments are estimated to reach a maximum thickness of ~400 m within a north–south elongated structural depression. Other subbasins that likely initially developed during the Miocene are the dominant tectonic features in the southern San Luis Basin. This includes the Tres Orejas subbasin, which formed in the southwestern portion of the basin by the Embudo fault zone and a hypothesized fault zone along its western margin. This subbasin reaches a maximum thickness of ~2 km, as indicated by magnetotelluric and gravity modeling. The Sunshine Valley, Questa, and Taos subbasins occupy the eastern part of the southern San Luis Basin. The southern Sangre de Cristo fault zone is the dominant tectonic feature that controlled their development after ~20 Ma. The east-down Gorge fault zone controlled the western margins of significant parts of these eastern subbasins, although much of the Taos subbasin may be superimposed on the Tres Orejas subbasin. Maximum low-density basin-fill thicknesses are estimated to be 1.2 km for the Sunshine Valley subbasin, 800 m for the Questa subbasin, and 1.8 km for the Taos subbasin. Subbasin-forming tectonic activity along the Gorge fault zone and within the Tres Orejas subbasin ceased by the end of the development of the largely Pliocene Taos Plateau volcanic field. After that, rift-related subsidence became more narrowly centered on the eastern margin of the basin, controlled mainly by the linked Embudo and southern Sangre de Cristo fault zones.</span></p>","language":"English","publisher":"Rocky Mountain Geology","doi":"10.24872/rmgjournal.54.2.97","usgsCitation":"Drenth, B.J., Grauch, V.J., Turner, K.J., Rodriguez, B.D., Thompson, R., and Bauer, P.W., 2019, A shallow rift basin segmented in space and time: The southern San Luis Basin, Rio Grande rift, northern New Mexico, U.S.A.: Rocky Mountain Geology, v. 54, no. 2, p. 97-131, https://doi.org/10.24872/rmgjournal.54.2.97.","productDescription":"35 p.","startPage":"97","endPage":"131","ipdsId":"IP-104797","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":459077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24872/rmgjournal.54.2.97","text":"Publisher Index Page"},{"id":380645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"New Mexico","otherGeospatial":"San Luis Basin, Rio Grande rift","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.45751953125,\n              35.817813158696616\n            ],\n            [\n              -104.78759765625,\n              35.817813158696616\n            ],\n            [\n              -104.78759765625,\n              37.01132594307015\n            ],\n            [\n              -106.45751953125,\n              37.01132594307015\n            ],\n            [\n              -106.45751953125,\n              35.817813158696616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":805198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":805199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":805200,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208734,"text":"70208734 - 2019 - Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni)","interactions":[],"lastModifiedDate":"2020-02-27T06:44:37","indexId":"70208734","displayToPublicDate":"2019-12-01T06:43:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni)","docAbstract":"The  Hawaiian Stilt, or Ae’o (Himantopus mexicanus knudseni), is an endangered waterbird endemic to the Hawaiian Islands. Loss of suitable wetland habitats due to anthropogenic development is a leading cause for decline, as well as the introduction of non-native predators and invasive wetland plants. This study fitted four Hawaiian Stilts with GPS satellite tags to document their use of wetland and surrounding habitats on Oahu Island. While other Hawaiian waterbirds are largely restricted to wetlands, we detected Hawaiian Stilts using heavily modified upland habitats, including developed areas, undeveloped fields, sports fields, as well as wetland habitats over a 6-month period. Overall, a high use of non-wetland habitat was observed (up to 58%), with significant differences in habitat occupancy among individual stilts and across different times of day. Wetlands were the dominant habitat occupied from morning to early afternoon, but non-wetland habitats were occupied at higher frequencies in the evening and early morning hours. Although only four birds were tracked, the extensive use of non-wetland habitat by these individuals indicates management of non-wetland habitats may be important for the conservation of this subspecies. However, more research is needed to understand how applicable these results are to other stilt popualtions across the Hawaiian Islands, and better understand the potential risks and benefits of these non-wetland habitats to stilt populations.","language":"English","publisher":"BioOne","doi":"10.1675/063.042.0408","usgsCitation":"Kawasaki, M., Hart, P.J., and Paxton, E., 2019, Frequent use of upland habitats by the endangered Hawaiian stilt (Himantopus mexicanus knudseni): Waterbirds, v. 42, no. 4, p. 431-438, https://doi.org/10.1675/063.042.0408.","productDescription":"8 p.","startPage":"431","endPage":"438","ipdsId":"IP-106610","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437271,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RPU1X1","text":"USGS data release","linkHelpText":"Oahu Island Hawaiian stilt GPS satellite tracking data, 2017-2018"},{"id":372676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"42","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kawasaki, Martha","contributorId":222802,"corporation":false,"usgs":false,"family":"Kawasaki","given":"Martha","email":"","affiliations":[{"id":37485,"text":"University of Hawai‘i - Hilo","active":true,"usgs":false}],"preferred":false,"id":783211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":783212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":783210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182770,"text":"70182770 - 2019 - Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa","interactions":[],"lastModifiedDate":"2024-05-17T14:50:31.723618","indexId":"70182770","displayToPublicDate":"2019-12-01T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa","docAbstract":"<p id=\"Par1\" class=\"Para\">The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March–May (MAM), July–September (JAS), and October–December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5) [5] months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill.</p>","language":"English","publisher":"Springer","doi":"10.1007/s00382-016-3296-z","usgsCitation":"Shukla, S., Roberts, J., Hoell. Andrew, Funk, C., Robertson, F.R., and Kirtmann, B., 2019, Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa: Climate Dynamics, v. 15, no. 12, p. 7411-7427, https://doi.org/10.1007/s00382-016-3296-z.","productDescription":"17 p.","startPage":"7411","endPage":"7427","ipdsId":"IP-069889","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":336787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"East Africa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              22,\n             -8\n            ],\n            [\n              52,\n              -8\n            ],\n            [\n              52,\n              23\n            ],\n            [\n              22,\n              23\n            ],\n            [\n              22,\n              -8\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-29","publicationStatus":"PW","scienceBaseUri":"58b7eba3e4b01ccd5500bae3","chorus":{"doi":"10.1007/s00382-016-3296-z","url":"http://dx.doi.org/10.1007/s00382-016-3296-z","publisher":"Springer Nature","authors":"Shukla Shraddhanand, Roberts Jason, Hoell Andrew, Funk Christopher C., Robertson Franklin, Kirtman Ben","journalName":"Climate Dynamics","publicationDate":"7/29/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"7/29/2016"},"contributors":{"authors":[{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":673688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Jason B.","contributorId":145808,"corporation":false,"usgs":false,"family":"Roberts","given":"Jason B.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":673689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoell. Andrew","contributorId":145831,"corporation":false,"usgs":false,"family":"Hoell. Andrew","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":673690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":673687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Franklin R.","contributorId":145809,"corporation":false,"usgs":false,"family":"Robertson","given":"Franklin","email":"","middleInitial":"R.","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":673691,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirtmann, Benjamin","contributorId":184160,"corporation":false,"usgs":false,"family":"Kirtmann","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":673692,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228105,"text":"70228105 - 2019 - Public access for pheasant hunters: Understanding an emerging need","interactions":[],"lastModifiedDate":"2022-02-04T20:44:13.320011","indexId":"70228105","displayToPublicDate":"2019-11-30T14:35:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Public access for pheasant hunters: Understanding an emerging need","docAbstract":"<p><span>Ring-necked pheasant (</span><i>Phasianus colchicus</i><span>; i.e., pheasant) hunting participation is declining across North America, reflecting a larger downward trend in American hunting participation and threatening benefits to grassland conservation and rural economies. To stabilize and expand the pheasant hunting population, we must first identify factors that influence pheasant hunter participation. We used an extensive in-person hunter survey to test the hypothesis that hunter demographics interact with social-ecological traits of hunting locations to affect hunter decisions, outcomes, and perceptions. We built a series of Bayesian mixed effects models to parse variation in demographics, perceptions, and hunt outcomes of pheasant hunters interviewed at public access hunting sites across 3 regions in Nebraska, USA, that varied in pheasant abundance and proximity to urban population centers. Among pheasant hunters in Nebraska, access to private lands was negatively related to the human population density of a pheasant hunter's home ZIP code and the distance a hunter had traveled to reach a hunting location. Pheasant hunters interviewed closer to metropolitan areas tended to be more urban and travel shorter distances, and their parties were more likely to include youth but less likely to include dogs. Hunter satisfaction was positively associated with seeing and harvesting pheasants and hunting with youth. Whereas youth participation and the number of pheasants seen varied by study region, hunter satisfaction did not differ across regions, suggesting that hunters may calibrate their expectations and build their parties based on where they plan to hunt. The variation in hunter demographics across hunting locations and disconnects between social and ecological correlates of hunter satisfaction suggests that diverse pheasant hunting constituencies will be best served by diverse pheasant hunting opportunities.</span></p>","language":"English","doi":"10.1002/jwmg.21785","usgsCitation":"Wszola, L., Madsen, A., Stuber, E., Chizinski, C., Lusk, J., Taylor, J., Pope, K.L., and Fontaine, J.J., 2019, Public access for pheasant hunters: Understanding an emerging need: Journal of Wildlife Management, v. 84, no. 1, p. 45-55, https://doi.org/10.1002/jwmg.21785.","productDescription":"11 p.","startPage":"45","endPage":"55","ipdsId":"IP-097657","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -101.90917968749999,\n              39.9434364619742\n            ],\n            [\n              -95.712890625,\n              39.9434364619742\n            ],\n            [\n              -95.712890625,\n              40.68063802521456\n            ],\n            [\n              -101.90917968749999,\n              40.68063802521456\n            ],\n            [\n              -101.90917968749999,\n              39.9434364619742\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wszola, L.S.","contributorId":274556,"corporation":false,"usgs":false,"family":"Wszola","given":"L.S.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":833126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madsen, A.L.","contributorId":274557,"corporation":false,"usgs":false,"family":"Madsen","given":"A.L.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":833127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuber, E.F.","contributorId":205137,"corporation":false,"usgs":false,"family":"Stuber","given":"E.F.","email":"","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":833128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chizinski, Christopher J.","contributorId":274559,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":833129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lusk, J.J.","contributorId":205141,"corporation":false,"usgs":false,"family":"Lusk","given":"J.J.","email":"","affiliations":[{"id":18961,"text":"Nebraska Game and Parks Commission, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":833130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, J.S.","contributorId":274563,"corporation":false,"usgs":false,"family":"Taylor","given":"J.S.","email":"","affiliations":[{"id":56624,"text":"Pheasants Forever Inc. & Midwest Association of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":833131,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":833132,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833133,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70214574,"text":"70214574 - 2019 - Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","interactions":[],"lastModifiedDate":"2020-09-30T14:08:22.311228","indexId":"70214574","displayToPublicDate":"2019-11-29T09:03:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2426,"text":"Journal of Physical Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream","docAbstract":"Hurricanes interact with the Gulf Stream in the South Atlantic Bight (SAB) through a wide variety of processes, which are crucial to understand for prediction of open-ocean and coastal hazards during storms. However, it remains unclear how waves are modified by large-scale ocean currents under storm conditions, when waves are aligned with the storm-driven circulation and tightly coupled to the overlying wind field. Hurricane Matthew (2016) impacted the US southeast coast, causing extensive coastal change due to large waves and elevated water levels. The hurricane traveled on the continental shelf parallel to the SAB coastline, with the right side of the hurricane directly over the Gulf Stream. Using the Coupled Ocean Atmosphere Wave Sediment Transport Modeling System, we investigate wave-current interaction between Hurricane Matthew and the Gulf Stream. The model simulates ocean currents and waves over a grid encompassing the US east coast, with varied coupling of the hydrodynamic and wave components to isolate the effect of the currents on the waves, and the effect of the Gulf Stream relative to storm-driven circulation. The Gulf Stream modifies the direction of the storm-driven currents beneath the right side of the hurricane. Waves transitioned from following currents that result in wave lengthening, through negative current gradients that result in wave steepening and dissipation. Wave-current interaction over the Gulf Stream modified maximum coastal total water levels, and changed incident wave directions at the coast by up to 20°, with strong implications for the morphodynamic response and stability of the coast to the hurricane.","language":"English","publisher":"American Meteorology Society","doi":"10.1175/JPO-D-19-0124.1","usgsCitation":"Hegermiller, C., Warner, J., Olabarrieta, M., and Sherwood, C.R., 2019, Wave-current interaction between Hurricane Matthew wave fields and the Gulf Stream: Journal of Physical Oceanography, v. 49, no. 11, p. 2883-2900, https://doi.org/10.1175/JPO-D-19-0124.1.","productDescription":"18 p.","startPage":"2883","endPage":"2900","ipdsId":"IP-109198","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":459087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jpo-d-19-0124.1","text":"Publisher Index Page"},{"id":378900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"East Coast, Gulf Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.12109375,\n              16.97274101999902\n            ],\n            [\n              -78.046875,\n              24.5271348225978\n            ],\n            [\n              -73.47656249999999,\n              36.1733569352216\n            ],\n            [\n              -65.390625,\n              44.213709909702054\n            ],\n            [\n              -68.73046875,\n              46.07323062540835\n            ],\n            [\n              -80.85937499999999,\n              34.016241889667015\n            ],\n            [\n              -92.63671875,\n              32.24997445586331\n            ],\n            [\n              -101.77734374999999,\n              25.799891182088334\n            ],\n            [\n              -97.3828125,\n              19.145168196205297\n            ],\n            [\n              -90.17578124999999,\n              16.29905101458183\n            ],\n            [\n              -89.12109375,\n              16.97274101999902\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hegermiller, Christie 0000-0002-6383-7508","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":241895,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":true,"id":800130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":800132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":800133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215197,"text":"70215197 - 2019 - Separating sea and slow slip signals on the seafloor","interactions":[],"lastModifiedDate":"2020-10-12T13:02:09.265924","indexId":"70215197","displayToPublicDate":"2019-11-29T08:00:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5999,"text":"Journal of Geophysical Research- Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Separating sea and slow slip signals on the seafloor","docAbstract":"<div class=\"article-section__content en main\"><p>Seafloor pressure measurements hold promise for estimating vertical displacements from transient slow slip events on submarine faults. We assess the accuracy of pressure offset estimates that evolve over days to weeks and the confidence with which they may be attributed to tectonic deformation or to the ocean water column. One common approach to resolve this ambiguity assumes water column pressures vary insignificantly over the study region and are represented by stable reference site pressures. Assessing the validity of this assumption requires independent evidence. Correlations between pressures and colocated temperatures collected during the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip experiment suggest temperatures might provide a useful independent proxy for water column pressures. We compared offsets estimated using several methods, with temperature and other proxies. The use of a temperature proxy was unsuccessful, because seafloor temperatures did not track the seasonal signal that contributes significantly to seafloor pressure changes over the slow slip event period. Regardless of the&nbsp;estimation method, offsets varied within a few cm around some uncertain reference level. Commonly used statistical measures are shown not to be reliable indicators of offset accuracy since offsets contribute minimally to the total variance. Offsets estimated using identical methods but with seafloor pressures simulated using a regional ocean model were larger than those derived from the data but had a similar pattern. Since the model simulates only water column processes, this suggests a significant fraction of the estimated pressure offsets are due to seasonal water column signal and are&nbsp;not of tectonic origin.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB018285","usgsCitation":"Gomberg, J.S., Hautala, S., Johnson, P., and Chiswell, S., 2019, Separating sea and slow slip signals on the seafloor: Journal of Geophysical Research- Solid Earth, v. 124, no. 12, p. 13486-13503, https://doi.org/10.1029/2019JB018285.","productDescription":"18 p.","startPage":"13486","endPage":"13503","ipdsId":"IP-109456","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":498872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb018285","text":"Publisher Index Page"},{"id":379298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              177.418212890625,\n              -39.82541310342477\n            ],\n            [\n              179.219970703125,\n              -39.82541310342477\n            ],\n            [\n              179.219970703125,\n              -38.54816542304657\n            ],\n            [\n              177.418212890625,\n              -38.54816542304657\n            ],\n            [\n              177.418212890625,\n              -39.82541310342477\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":801139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hautala, Susan","contributorId":194235,"corporation":false,"usgs":false,"family":"Hautala","given":"Susan","email":"","affiliations":[],"preferred":false,"id":801140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Paul","contributorId":189150,"corporation":false,"usgs":false,"family":"Johnson","given":"Paul","email":"","affiliations":[],"preferred":false,"id":801141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chiswell, Steve","contributorId":242932,"corporation":false,"usgs":false,"family":"Chiswell","given":"Steve","email":"","affiliations":[{"id":48587,"text":"National Institute of Water & Atmospheric Research Ltd","active":true,"usgs":false}],"preferred":false,"id":801142,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70211034,"text":"70211034 - 2019 - The 2018 update of the US National Seismic Hazard Model: Overview of model and implications","interactions":[],"lastModifiedDate":"2020-07-13T12:34:13.1599","indexId":"70211034","displayToPublicDate":"2019-11-28T15:52:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Overview of model and implications","docAbstract":"<p><span>During 2017–2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associated epistemic uncertainties and aleatory variabilities, and new soil amplification factors; (3) in the western United States (WUS), amplified shaking estimates of long-period ground motions at sites overlying deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas were incorporated; and (4) in the conterminous United States, seismic hazard is calculated for 22 periods (from 0.01 to 10 s) and 8 uniform V</span><sub>S30</sub><span>&nbsp;maps (ranging from 1500 to 150 m/s). We also include a description of updated computer codes and modeling details. Results show increased ground shaking in many (but not all) locations across the CEUS (up to ~30%), as well as near the four urban areas overlying deep sedimentary basins in the WUS (up to ~50%). Due to population growth and these increased hazard estimates, more people live or work in areas of high or moderate seismic hazard than ever before, leading to higher risk of undesirable consequences from forecasted future ground shaking.</span></p>","language":"English","publisher":"Sage","doi":"10.1177/8755293019878199","usgsCitation":"Petersen, M.D., Shumway, A., Powers, P.M., Mueller, C., Moschetti, M.P., Frankel, A.D., Rezaeian, S., McNamara, D.E., Luco, N., Boyd, O.S., Rukstales, K.S., Jaiswal, K.S., Thompson, E.M., Hoover, S.M., Clayton, B., Field, E., and Zeng, Y., 2019, The 2018 update of the US National Seismic Hazard Model: Overview of model and implications: Earthquake Spectra, v. 36, no. 1, p. 5-41, https://doi.org/10.1177/8755293019878199.","productDescription":"37 p.","startPage":"5","endPage":"41","ipdsId":"IP-109680","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437273,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RQMREV","text":"USGS data release","linkHelpText":"Data Release for Additional Period and Site Class Data for the 2018 National Seismic Hazard Model for the Conterminous United States (ver. 1.1, February 2020)"},{"id":437272,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WT5OVB","text":"USGS data release","linkHelpText":"Data Release for 2018 Update of the U.S. National Seismic Hazard Model"},{"id":376269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n      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field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":792523,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":792524,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70208420,"text":"70208420 - 2019 - Increases in life-safety risks to building occupants from induced earthquakes in the central United States","interactions":[],"lastModifiedDate":"2020-02-09T13:19:55","indexId":"70208420","displayToPublicDate":"2019-11-28T13:16:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Increases in life-safety risks to building occupants from induced earthquakes in the central United States","docAbstract":"Earthquake occurrence rates in some parts of the central United States have been elevated for a number of years; this increase has been widely attributed to deep wastewater injection associated with oil and gas activities. This induced seismicity has caused damage to buildings and infrastructure and substantial public concern. In March 2016, the U.S. Geological Survey (USGS) published its first earthquake ground motion hazard model that accounts for the elevated seismicity, producing a one-year forecast encompassing both induced and natural earthquakes. To assess the potential impacts of the elevated seismicity on buildings and the public, this paper quantifies forecasted risks of a) building collapse and b) falling of nonstructural building components, by combining the 2016 USGS hazard model with fragility curves for generic modern code-compliant buildings. The assessment shows significant increases in both types of risk compared to that due to non-induced earthquakes alone; the magnitudes of the increases vary from a few times to more than a 100 times, depending on location, building period (which is correlated to building height), alternatives for the hazard model, and the type of risk of interest. For exploratory purposes only, we also estimate revised values of the risk-targeted ground motion that are currently used for designing buildings.","language":"English","publisher":"SAGE","doi":"10.1193/041618EQS095M","usgsCitation":"Liu, T., Luco, N., and Liel, A.B., 2019, Increases in life-safety risks to building occupants from induced earthquakes in the central United States: Earthquake Spectra, v. 35, no. 2, p. 471-488, https://doi.org/10.1193/041618EQS095M.","productDescription":"18 p.","startPage":"471","endPage":"488","ipdsId":"IP-103586","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":372173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas, Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.26123046875,\n              32.08257455954592\n            ],\n            [\n              -94.46044921875,\n              32.08257455954592\n            ],\n            [\n              -94.46044921875,\n              36.94989178681327\n            ],\n            [\n              -100.26123046875,\n              36.94989178681327\n            ],\n            [\n              -100.26123046875,\n              32.08257455954592\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Taojun","contributorId":201798,"corporation":false,"usgs":false,"family":"Liu","given":"Taojun","email":"","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":781813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":781812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liel, Abbie B.","contributorId":184158,"corporation":false,"usgs":false,"family":"Liel","given":"Abbie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":781814,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70223764,"text":"70223764 - 2019 - Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments","interactions":[],"lastModifiedDate":"2021-09-07T15:09:15.564186","indexId":"70223764","displayToPublicDate":"2019-11-28T10:04:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"title":"Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments","docAbstract":"<p><span>Spatial and temporal variability characterize submerged aquatic vegetation (SAV) assemblages, but understanding the complex interactions of environmental drivers of SAV assemblages remains elusive. We documented SAV composition and biomass across a salinity gradient in a coastal estuary over 12 mo. Ten macrophyte species were identified. The dominant species,&nbsp;</span><i>Ceratophyllum demersum</i><span>&nbsp;and&nbsp;</span><i>Myriophyllum spicatum,</i><span>&nbsp;accounted for over 40% of total biomass. Only&nbsp;</span><i>Ruppia maritima</i><span>&nbsp;occurred across the salinity gradient. Salinity, water depth and clarity delineated 3 assemblages: a saline assemblage, and 2 groups of fresher-water species, one associated with deeper water and lower water clarity and the other associated with shallow water and higher water clarity. These assemblages exhibited intra-annual variation, with at least 5 times more biomass in late spring/mid-summer compared to early winter. This pattern was consistent across the estuary, although the difference between peak and low biomass varied by habitat type; brackish exhibited the greatest magnitude. This variation is likely due to higher variation in salinity and the species composition of this habitat. As climate change and coastal restoration impact timing and range of salinity, water depth and clarity in this region, these data can be used to help inform predictive models and management decisions.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/ab00719","usgsCitation":"Hillmann, E.R., DeMarco, K., and La Peyre, M., 2019, Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments: Aquatic Biology, v. 28, p. 175-186, https://doi.org/10.3354/ab00719.","productDescription":"12 p.","startPage":"175","endPage":"186","ipdsId":"IP-105293","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00719","text":"Publisher Index Page"},{"id":388877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.483154296875,\n              28.748396571187406\n            ],\n            [\n              -88.956298828125,\n              28.748396571187406\n            ],\n            [\n              -88.956298828125,\n              30.330212685432734\n            ],\n            [\n              -91.483154296875,\n              30.330212685432734\n            ],\n            [\n              -91.483154296875,\n              28.748396571187406\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hillmann, Eva R.","contributorId":200686,"corporation":false,"usgs":false,"family":"Hillmann","given":"Eva","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":822573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":822574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822576,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70216102,"text":"70216102 - 2019 - The behavior of the Salesforce Tower, the tallest building in San Francisco, California inferred from earthquake and ambient shaking","interactions":[],"lastModifiedDate":"2020-11-05T13:39:35.933412","indexId":"70216102","displayToPublicDate":"2019-11-28T07:31:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The behavior of the Salesforce Tower, the tallest building in San Francisco, California inferred from earthquake and ambient shaking","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>The newly constructed tallest building designed in conformance with performance-based design procedure in San Francisco, California is a 61-story building equipped with an accelerometric array that recorded the January 4, 2018 M4.4 Berkeley earthquake. The building is designed with concrete core shear walls and perimeter gravity steel columns. The earthquake records as well as on-demand recorded ambient responses of the building are studied to determine its dynamic characteristics and building-specific behavior. At the level of shaking of either the earthquake or ambient excitation, the frequencies and low modal damping ratios (&lt;2%) are similar. The building exhibits torsional behavior most likely due to abrupt asymmetrical changes in the size of the core shear wall. The translational and torsional modes during the earthquake are closely coupled, which leads to a beating effect, the period of which is calculable. Due to the relatively low-amplitude shaking during the earthquake, the drift ratios were small and did not cause any damage. It is expected that during stronger shaking levels, these characteristics may change.</p></div></div>","language":"English","publisher":"Sage Journals","doi":"10.1193/112918EQS273M","usgsCitation":"Celebi, M., Haddadi, H., Huang, M., Valley, M., Hooper, J., and Klemencic, R., 2019, The behavior of the Salesforce Tower, the tallest building in San Francisco, California inferred from earthquake and ambient shaking: Earthquake Spectra, v. 35, no. 4, p. 1711-1737, https://doi.org/10.1193/112918EQS273M.","productDescription":"27 p.","startPage":"1711","endPage":"1737","ipdsId":"IP-114320","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":380183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.52639770507812,\n              37.667516276171426\n            ],\n            [\n              -122.32864379882811,\n              37.667516276171426\n            ],\n            [\n              -122.32864379882811,\n              37.820632846207864\n            ],\n            [\n              -122.52639770507812,\n              37.820632846207864\n            ],\n            [\n              -122.52639770507812,\n              37.667516276171426\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":804095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haddadi, H.","contributorId":12673,"corporation":false,"usgs":false,"family":"Haddadi","given":"H.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":804096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Moh","contributorId":146970,"corporation":false,"usgs":false,"family":"Huang","given":"Moh","email":"","affiliations":[],"preferred":false,"id":804097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valley, Michael","contributorId":48464,"corporation":false,"usgs":true,"family":"Valley","given":"Michael","affiliations":[],"preferred":false,"id":804129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooper, John","contributorId":146972,"corporation":false,"usgs":false,"family":"Hooper","given":"John","affiliations":[],"preferred":false,"id":804130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klemencic, Ron","contributorId":146973,"corporation":false,"usgs":false,"family":"Klemencic","given":"Ron","email":"","affiliations":[],"preferred":false,"id":804131,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206787,"text":"ofr20191081 - 2019 - 3D geologic framework for use with the U.S. Geological Survey National Crustal Model, Phase 1—Western United States","interactions":[],"lastModifiedDate":"2022-04-21T18:33:47.275626","indexId":"ofr20191081","displayToPublicDate":"2019-11-27T11:10:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1081","displayTitle":"3D Geologic Framework for Use with the U.S. Geological Survey National Crustal Model, Phase 1—Western United States","title":"3D geologic framework for use with the U.S. Geological Survey National Crustal Model, Phase 1—Western United States","docAbstract":"<p>A 3D geologic framework is presented here as part of the U.S. Geological Survey National Crustal Model for the western United States, which will be used to improve seismic hazard assessment. The framework is based on 1:250,000 to 1:1,000,000-scale state geologic maps and depths of multiple subsurface unit boundaries. The geology at or near the Earth’s surface is based on published maps with modifications to remove discontinuities across state borders. Extrapolation of rock type and age in the subsurface is achieved by iterative stripping of units of a given age, nearest neighbor interpolation of the remaining units, and constraints on basement geology. The subsurface depth of the interfaces between units is determined by a range of models with varying quantity and quality of constraints. Bedrock depth is derived primarily from a proxy model with added geophysical constraint in some areas. The depths to the base of Cenozoic and Phanerozoic sedimentary and extrusive volcanic rocks are constrained by geophysical methods in many areas. Elsewhere, a simple method is used to estimate their subsurface depth based on the distance to the edge of the geologic units. The remaining continental units are evenly distributed above, below, and between depending on age. The oceanic crust is treated as a simple four-layer model with the added complexity of subduction beneath the North American plate along the Cascadia subduction zone.</p><p>Refinements to this technique may be accomplished in future versions of the model with more specific information including the location of faults to produce discontinuities in geologic structure and additional information obtained from boreholes and geophysical studies. Further improvements to the geologic framework may be made by incorporating information from more local studies, for example, hydrogeologic studies.</p><p><br data-mce-bogus=\"1\"></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191081","usgsCitation":"Boyd, O.S., 2019, 3D Geologic framework for use with the U.S. Geological Survey National Crustal Model, Phase 1—Western United States: U.S. Geological Survey Open-File Report 2019–1081, 36 p., https://doi.org/10.3133/ofr20191081.","productDescription":"Report: vii, 36 p.; Data Release","onlineOnly":"Y","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437274,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94MGWUR","text":"USGS data release","linkHelpText":"GeoFram"},{"id":399412,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109580.htm"},{"id":369408,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SBQENM","text":"USGS data release","linkHelpText":"3D Geologic Framework for use with the U.S. Geological Survey National Crustal Model, Phase 1: Western United States"},{"id":369407,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1081/ofr20191081.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1081"},{"id":369405,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1081/coverthb2.jpg"},{"id":370582,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1081/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2019-1081 version history"}],"otherGeospatial":"Western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125,\n              31.3289\n            ],\n            [\n              -100,\n              31.3289\n            ],\n            [\n              -100,\n              49\n            ],\n            [\n              -125,\n              49\n            ],\n            [\n              -125,\n              31.3289\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/geohazards\" data-mce-href=\"https://www.usgs.gov/centers/geohazards\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-966<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Geology and Age of Rocks at or Near the Earth’s Surface</li><li>Lithology and Age of Subsurface Layers</li><li>Subsurface Layer Depth and Elevation</li><li>Model Cross Sections</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li><li>Appendix 1. Age Dictionary and Mapping</li><li>Appendix 2. Lithology Dictionary and Mapping</li><li>Appendix 3. Exceptions to Geologic Map Modification Rules</li></ul>","publishedDate":"2019-11-27","revisedDate":"2019-12-20","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":775750,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70206037,"text":"sir20195117 - 2019 - Groundwater-flow model and analysis of groundwater and surface-water interactions for the Big Sioux aquifer, Sioux Falls, South Dakota","interactions":[],"lastModifiedDate":"2019-11-27T09:54:48","indexId":"sir20195117","displayToPublicDate":"2019-11-27T06:42:07","publicationYear":"2019","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":"2019-5117","displayTitle":"Groundwater-Flow Model and Analysis of Groundwater and Surface-Water Interactions for the Big Sioux Aquifer, Sioux Falls, South Dakota","title":"Groundwater-flow model and analysis of groundwater and surface-water interactions for the Big Sioux aquifer, Sioux Falls, South Dakota","docAbstract":"<p>The city of Sioux Falls, in southeastern South Dakota, is the largest city in South Dakota. The U.S. Geological Survey (USGS), in cooperation with the city of Sioux Falls, completed a groundwater-flow model to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer in the model area.</p><p>The model area includes the Big Sioux aquifer and the underlying hydrogeologic units from Dell Rapids, South Dakota, to the confluence of the Big Sioux River and the outlet of the Sioux Falls Diversion Channel in eastern Sioux Falls, S. Dak. The Big Sioux aquifer is the primary aquifer in the model area and the focus of the groundwater-flow model. The Big Sioux River is the largest stream in the model area and is in hydraulic connection with the Big Sioux aquifer.</p><p>A conceptual model for the area was constructed and includes a characterization of the hydrogeologic framework, analysis and construction of potentiometric surfaces, and summary of estimated water budget components in the model area. The primary hydrogeologic units in the model area consist of (1) the Big Sioux aquifer, (2) a glacial till confining unit, and (3) bedrock aquifers (Split Rock Creek and Sioux Quartzite aquifers). Sources of groundwater recharge included infiltration of precipitation, stream seepage, and groundwater exchanges among the hydraulically connected Big Sioux aquifer, glacial till confining unit, and bedrock aquifers. Groundwater losses included evapotranspiration, groundwater discharge to streams, and groundwater withdrawal to supply water-use needs.</p><p>A numerical groundwater-flow model (numerical model) was constructed and was used to simulate all aspects of the conceptual model for predevelopment (steady-state) and time-varying (transient) monthly conditions for 1950–2017. The numerical model was constructed using the USGS modular hydrologic simulation program, MODFLOW–6, and was calibrated using the Parameter ESTimation software, PEST++.</p><p>The transient numerical model was calibrated for steady-state and transient monthly conditions for 1950–2017. Calibration targets were observations of hydraulic head, changes in hydraulic head, monthly mean streamflow (as a rate), and cumulative monthly stream discharge (as a volume). Parameters adjusted during model calibration were horizontal and vertical hydraulic conductivity, specific storage, specific yield, recharge and evapotranspiration multipliers, and streambed hydraulic conductivity. Horizontal and vertical hydraulic conductivity were estimated at pilot points distributed within the model area; specific storage and specific yield were assigned to uniform values in each layer in the model area; recharge and evapotranspiration multipliers were assigned uniformly for every stress period in the numerical model; and streambed hydraulic conductivity values were assigned uniformly between stream confluences.</p><p>The final calibrated parameter values of horizontal and vertical hydraulic conductivity, specific yield, specific storage, streambed hydraulic conductivity, recharge, and evapotranspiration were considered reasonable for the hydrogeologic materials and conditions in the model area for 1950–2017.</p><p>Overall, simulated hydraulic head altitudes had a linear regression coefficient of determination (R<sup>2</sup>) of 0.48. Hydraulic head altitude residuals for the glacial till confining unit and bedrock aquifers were typically greater in magnitude when compared to residuals in the Big Sioux aquifer, but simulated hydraulic head altitudes in the Big Sioux aquifer compared favorably with mean observed hydraulic head altitudes and had a linear regression R<sup>2</sup> of 0.93.</p><p>Simulated streamflow hydrographs matched the general trends of observed increases and decreases in streamflow for USGS streamgages 06482000 (Big Sioux River at Sioux Falls, S. Dak.) and 06482020 (Big Sioux River at North Cliff Avenue at Sioux Falls, S. Dak.), but larger streamflows were overestimated at the first streamgage and underestimated at the second streamgage. The numerical model reasonably estimated cumulative monthly stream discharge for the first 10–15 years of available streamflow records at both USGS streamgages. After the first 10–15 years of available streamflow record,&nbsp;cumulative monthly stream discharge was closely estimated for USGS streamgage 06482000 and underestimated at USGS streamgage 06482020.</p><p>Composite sensitivities without regularization were calculated by PEST++ for the calibrated numerical model parameters and were averaged by parameter group. The parameter group with the highest mean composite sensitivity was the recharge multiplier parameter group.</p><p>Model simplifications, assumptions, and limitations were necessary for construction of the conceptual and numerical models and for calibration efficiency. Spatial simplification of hydraulic properties could cause the numerical model to misrepresent reactions to changes in localized stresses, such as additional demands for groundwater withdrawal. The numerical model was temporally discretized into monthly periods and required scaling daily rates into representative monthly rates for model input and calibration targets. Based on the comparison between the observed and simulated groundwater levels, monthly mean streamflow and cumulative monthly stream discharge, and general groundwater distribution and flow, the numerical model favorably simulated the flow in the Big Sioux aquifer.</p><p>Eventual capture was calculated in the model area using a steady-state numerical groundwater-flow model. The eventual capture map shows areas of higher streamflow capture adjacent to the Big Sioux River north of the city of Sioux Falls and along the lower part of the Sioux Falls Diversion Channel, and areas of lower streamflow capture along aquifer boundaries and near the southern Sioux Quartzite barrier.</p><p>The timing of capture was determined using a transient numerical groundwater-flow model to determine the likely captured water sources for 30 years of groundwater withdrawal at three hypothetical wells using three continuous withdrawal rates (112.5, 450.0, and 900.0 gallons per minute). Supply for all three hypothetical wells became capture-dominated after only a short period of continuous withdrawal. Capture stabilized after about 10–15 years for well A, and after 20–25 years for well B, and after about 10–15 years for well C.</p><p>The groundwater-flow model is a suitable tool to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer near Sioux Falls, S. Dak. The numerical model can be used to simulate hydrologic scenarios, advance understanding of groundwater budgets, compute system response to stress, and determine likely sources of water supplied to wells.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195117","collaboration":"Prepared in cooperation with the city of Sioux Falls","usgsCitation":"Davis, K.W., Eldridge, W.G., Valder, J.F., and Valseth, K.J., 2019, Groundwater-flow model and analysis of groundwater and surface-water interactions for the Big Sioux aquifer, Sioux Falls, South Dakota: U.S. Geological Survey Scientific Investigations Report 2019–5117, 86 p., https://doi.org/10.3133/sir20195117.","productDescription":"Report: xi, 86 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-105956","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":369602,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20195013","text":"SIR 2019–5013","linkHelpText":"– Hydraulic conductivity estimates from slug tests in the Big Sioux aquifer near Sioux Falls, South Dakota"},{"id":369600,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3393","text":"SIM 3393","linkHelpText":"– Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data"},{"id":369601,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F79885XC","text":"USGS data release for SIM 3393","linkHelpText":"– Airborne electromagnetic and magnetic survey data, Big Sioux aquifer, October 2015, Sioux Falls, South Dakota"},{"id":369603,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P9LUB44J","text":"USGS data release for SIR 2019–5013","linkHelpText":"– Water-level data and AQTESOLV Pro analysis results for slug tests in the Big Sioux Aquifer, Sioux Falls, South Dakota, 2017"},{"id":369535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5117/coverthb.jpg"},{"id":369536,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5117/sir20195117.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5117"},{"id":369537,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O59RO0","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-6 model of the Big Sioux aquifer, Sioux Falls, South Dakota"}],"country":"United States","state":"South Dakota","city":"Sioux Falls","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.06146240234375,\n              43.29919735147067\n            ],\n            [\n              -96.42425537109375,\n              43.29919735147067\n            ],\n            [\n              -96.42425537109375,\n              43.757208878849376\n            ],\n            [\n              -97.06146240234375,\n              43.757208878849376\n            ],\n            [\n              -97.06146240234375,\n              43.29919735147067\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/dakota-water\" href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503<br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Groundwater-Flow Model</li><li>Analysis of Groundwater and Surface-Water Interactions</li><li>Summary and Conclusions</li><li>References Cited</li><li>Appendix 1. Hydraulic Conductivity Estimates with Small-Diameter Nuclear Magnetic Resonance Logging Tool</li><li>Appendix 2. Analysis of Recharge and Evapotranspiration using a Soil-Water-Balance Model</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-11-27","noUsgsAuthors":false,"publicationDate":"2019-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Kyle W. 0000-0002-8723-0110","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":201549,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle W.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868 jvalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":139256,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua","email":"jvalder@usgs.gov","middleInitial":"F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":773380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valseth, Kristen J. 0000-0003-4257-6094","orcid":"https://orcid.org/0000-0003-4257-6094","contributorId":203447,"corporation":false,"usgs":true,"family":"Valseth","given":"Kristen","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773381,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70212716,"text":"70212716 - 2019 - Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA","interactions":[],"lastModifiedDate":"2020-08-27T15:33:34.188151","indexId":"70212716","displayToPublicDate":"2019-11-26T10:08:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2457,"text":"Journal of Soils and Sediments","active":true,"publicationSubtype":{"id":10}},"title":"Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Purpose</h3><p>The main purpose of this study was to demonstrate the utility of the sediment fingerprinting approach to apportion surface-derived sediment, and then age date that portion using short-lived fallout radionuclides. In systems where a large mass of mobile sediment is in channel storage, age dating provides an understanding of the transfer of sediment through the watershed and the time scales over which management actions to reduce sediment loadings may be effective.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Materials and methods</h3><p>In the agricultural Walnut Creek watershed, Iowa, the sediment-fingerprinting approach with elemental analysis was used to apportion the sources of fine-grained sediment (croplands, prairie, unpaved roads, and channel banks). Fallout radionuclides (<sup>7</sup>Be,<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub>) were used to age the portion of suspended sediment that was derived from agricultural topsoil. Age dating was performed at two different scales:<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>which can date sediment to ~ 85&nbsp;years and<span>&nbsp;</span><sup>7</sup>Be to ~ 1&nbsp;year.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results and discussion</h3><p>Sediment fingerprinting results indicated that the majority of suspended sediment is derived from cropland (62%) with streambanks contributing 36%, and prairie, pasture, and unpaved roads each contributing ≤ 1%. The topsoil–derived portion of sediment (primarily agriculture) dated using<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>has ages ranging from 1 to 58&nbsp;years, and using<span>&nbsp;</span><sup>7</sup>Be, a component of much younger sediment that yields ages ranging from 44 to 205&nbsp;days. The occurrence of<span>&nbsp;</span><sup>7</sup>Be indicates that some portion of the sediment is young, on the order of months, whereas the dating based on<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub><span>&nbsp;</span>indicates that some of the surface-derived sediment has been in channel storage for decades. Published studies in Walnut Creek indicate that a large component of sediment is stored in the channel bed.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>We conclude that the<span>&nbsp;</span><sup>210</sup>Pb<sub>ex</sub>-based ages are a reasonable estimate for the mean age of the surface-derived fraction and that<span>&nbsp;</span><sup>7</sup>Be activities are evidence that there is a smaller fraction of very young sediment in the stream. We propose a geomorphic model where agricultural soil is delivered to the channel and conveyed to the watershed outlet at three time scales: a geologic-millennial time scale, decades, and a young time scale (&lt; 1&nbsp;year).</p>","language":"English","publisher":"Springer","doi":"10.1007/s11368-018-2168-z","usgsCitation":"Gellis, A.C., Fuller, C.C., Van Metre, P.C., Filstrup, C.T., Cole, K., and Sabitov, T., 2019, Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA: Journal of Soils and Sediments, v. 19, p. 3374-3396, https://doi.org/10.1007/s11368-018-2168-z.","productDescription":"23 p.","startPage":"3374","endPage":"3396","ipdsId":"IP-090014","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":377887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Jasper County","otherGeospatial":"Walnut Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.234,41.8622],[-93.1187,41.8624],[-93.0035,41.8624],[-92.8845,41.8619],[-92.7674,41.8618],[-92.7683,41.776],[-92.768,41.6879],[-92.7683,41.6007],[-92.7567,41.6011],[-92.7564,41.509],[-92.8729,41.5082],[-92.9894,41.5083],[-93.1047,41.5078],[-93.2181,41.5076],[-93.3304,41.5074],[-93.3314,41.6004],[-93.3504,41.6004],[-93.3496,41.688],[-93.3494,41.7757],[-93.3492,41.8624],[-93.234,41.8622]]]},\"properties\":{\"name\":\"Jasper\",\"state\":\"IA\"}}]}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":797341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":797343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Kevin","contributorId":208183,"corporation":false,"usgs":false,"family":"Cole","given":"Kevin","email":"","affiliations":[{"id":37761,"text":"USDA-ARS, National Laboratory for Agriculture and the Environment, 1015 N. University Blvd, Ames. IA 50011","active":true,"usgs":false}],"preferred":false,"id":797344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sabitov, Timur","contributorId":236885,"corporation":false,"usgs":false,"family":"Sabitov","given":"Timur","email":"","affiliations":[{"id":47559,"text":"Geology and Geophysics, Academy of Science of Uzbekistan","active":true,"usgs":false}],"preferred":false,"id":797345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70220223,"text":"70220223 - 2019 - Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data","interactions":[],"lastModifiedDate":"2021-04-28T13:13:55.608928","indexId":"70220223","displayToPublicDate":"2019-11-26T08:11:29","publicationYear":"2019","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":"Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>During volcanic eruptions, model predictions of plume height are limited by the accuracy of entrainment coefficients used in many plume models. Typically, two parameters are used,<span>&nbsp;</span><i>α</i><span>&nbsp;</span>and<span>&nbsp;</span><i>β</i>, which relate the entrained air speed to the jet speed in the axial and cross‐flow directions, respectively. To improve estimates of these parameters, wind tunnel experiments have been conducted for a range of cross‐wind velocities and turbulence conditions. Measurements are compared directly to computations from the 1‐D plume model, Plumeria, in the near‐field, bending region of the jet. Entrainment coefficients are determined through regression analysis, demonstrating optimal combinations of effective<span>&nbsp;</span><i>α</i><span>&nbsp;</span>and<span>&nbsp;</span><i>β</i><span>&nbsp;</span>values. For turbulent conditions, all wind speeds overlapped at a single combination,<span>&nbsp;</span><i>α</i><span>&nbsp;</span>= 0.06 and<span>&nbsp;</span><i>β</i>=0.46, each of&nbsp;which are slightly reduced from standard values. Refined coefficients were used to model plume heights for 20 historical eruptions. Model accuracy improves modestly in most cases, agreeing to within 3&nbsp;km with observed plume heights. For weak eruptions, uncertainty in field measurements can outweigh the effects of these refinements, illustrating the challenge of applying plume models in practice.</p></div></div></div></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018jb017224","usgsCitation":"McNeal, J., Mastin, L.G., Cal, R., and Solovitz, S.A., 2019, Investigating the accuracy of one‐dimensional volcanic plume models using laboratory experiments and field data: Journal of Volcanology and Geothermal Research, v. 124, no. 11, p. 11290-11304, https://doi.org/10.1029/2018jb017224.","productDescription":"15 p.","startPage":"11290","endPage":"11304","ipdsId":"IP-101393","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":459113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb017224","text":"Publisher Index Page"},{"id":385350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McNeal, James S.","contributorId":257656,"corporation":false,"usgs":false,"family":"McNeal","given":"James S.","affiliations":[{"id":52077,"text":"Washington State University, Vancouver","active":true,"usgs":false}],"preferred":false,"id":814847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":814850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cal, Raul B.","contributorId":257658,"corporation":false,"usgs":false,"family":"Cal","given":"Raul B.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":814849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solovitz, Stephen A. 0000-0001-7019-2958","orcid":"https://orcid.org/0000-0001-7019-2958","contributorId":257659,"corporation":false,"usgs":false,"family":"Solovitz","given":"Stephen","email":"","middleInitial":"A.","affiliations":[{"id":52077,"text":"Washington State University, Vancouver","active":true,"usgs":false}],"preferred":false,"id":814852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70209462,"text":"70209462 - 2019 - Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature","interactions":[],"lastModifiedDate":"2020-05-04T17:57:42.379102","indexId":"70209462","displayToPublicDate":"2019-11-26T07:58:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature","docAbstract":"How carbon cycles are regulated by environmental temperature remains a substantial uncertainty in our understanding of how watersheds will respond to ongoing climate change. Aquatic ecosystems are important components of carbon flux to the atmosphere and ocean, yet we have limited understanding of how temperature modifies ecosystem metabolic processes and, therefore, aquatic contributions to carbon cycles at watershed to global scales.  We propose that geomorphology controls the landscape-scale distribution and quality of organic material that forms the metabolic base of aquatic ecosystems and, therefore, how aquatic ecosystem metabolism responds to changes in temperature. Across 23 streams and four years in a boreal river basin, we estimated how temperature sensitivity of ecosystem respiration (ER) varied among streams draining watersheds with different geomorphic characteristics. We found that geomorphic conditions imposed strong ultimate controls on temperature sensitivity; ER in streams draining flat watersheds was up to six times more sensitive to temperature than streams draining steeper watersheds.  Further, we show that the link between watershed geomorphology and temperature sensitivity of ER was related to the quality of carbon substrates that changes systematically across the gradient in geomorphic conditions. These results suggest that geomorphology will ultimately control how carbon is transported, stored, and incorporated into river food webs as climate warms.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-53703-3","collaboration":"","usgsCitation":"Jankowski, K.J., and Schindler, D., 2019, Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature: Scientific Reports, v. 9, 17619, 10 p., https://doi.org/10.1038/s41598-019-53703-3.","productDescription":"17619, 10 p.","ipdsId":"IP-102157","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":459115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-53703-3","text":"Publisher Index Page"},{"id":373857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2019-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":786569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schindler, Daniel E.","contributorId":223885,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":786570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70206863,"text":"70206863 - 2019 - Employing an ecosystem services framework to deliver decision ready science","interactions":[],"lastModifiedDate":"2019-11-26T07:08:17","indexId":"70206863","displayToPublicDate":"2019-11-26T07:06:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5217,"text":"Advances in Ecological Research","active":true,"publicationSubtype":{"id":10}},"title":"Employing an ecosystem services framework to deliver decision ready science","docAbstract":"Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects.  In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework.  This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for  ecosystem services and supporting tools such as the dynamic ecosystem model.","language":"English","publisher":"Science Signpost Publishing","usgsCitation":"Pindilli, E., Hogan, D.M., and Zhu, Z., 2019, Employing an ecosystem services framework to deliver decision ready science: Advances in Ecological Research, v. 4, no. 11, p. 302-323.","productDescription":"22 p.","startPage":"302","endPage":"323","ipdsId":"IP-103007","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":369609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369560,"type":{"id":15,"text":"Index Page"},"url":"https://www.ss-pub.org/aeer/employing-an-ecosystem-services-framework-to-deliver-decision-ready-science/"}],"volume":"4","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pindilli, Emily 0000-0002-5101-1266 epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":776095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":776097,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70205808,"text":"sir20195111 - 2019 - Evaluating associations between environmental variables and Escherichia coli levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017","interactions":[],"lastModifiedDate":"2019-11-25T09:58:08","indexId":"sir20195111","displayToPublicDate":"2019-11-25T09:35:00","publicationYear":"2019","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":"2019-5111","displayTitle":"Evaluating Associations Between Environmental Variables and <i>Escherichia Coli</i> Levels for Predictive Modeling at Pawtuckaway Beach in Nottingham, New Hampshire, From 2015 to 2017","title":"Evaluating associations between environmental variables and Escherichia coli levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017","docAbstract":"<p>From 2015 through 2017, the U.S. Geological Survey in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services studied occurrences of high levels of <i>Escherichia coli</i> (<i>E. coli</i>) bacteria at the Pawtuckaway State Park Beach in Nottingham, New Hampshire. Historic data collected by the New Hampshire Department of Environmental Services indicated that <i>E. coli</i> concentrations in the water typically increased through the beach season to levels considered potentially harmful to beachgoers. During the three beach seasons that were studied, <i>E. coli</i> samples were collected three to four times per week, and water-quality and meteorological data were collected continuously. The Virtual Beach software was used to generate a predictive model for each year of the study (2015–2017), and the model for each of these years was tested with data from the other two. Additionally, data from all study years were combined to generate a comprehensive model to help identify independent variables that might characterize environmental conditions relative to <i>E. coli</i> levels during multiple seasons. The accuracy of the models in predicting the occurrence of high <i>E. coli</i> levels was marginal, but the models did provide insights into the likely mechanisms for increased <i>E. coli</i> levels during the seasons. Variables most important in explaining high <i>E. coli</i> levels were the presence of geese at the beach, the progression of the season, the number of visitors at the beach, and wind vectors relative to beach orientation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195111","collaboration":"Prepared in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services","usgsCitation":"Coles, J.F., and Bush, K.F., 2019, Evaluating associations between environmental variables and <i>Escherichia coli</i> levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017: U.S. Geological Survey Scientific Investigations Report 2019–5111, 28 p., https://doi.org/10.3133/sir20195111.","productDescription":"Report: vii, 28 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101776","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":369290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5111/coverthb.jpg"},{"id":369288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5cc70bf4e4b09b8c0b77e5b7","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Data collected at Pawtuckaway Beach in Nottingham, New Hampshire, 2015–2017"},{"id":369409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5111/sir20195111.pdf","text":"Report","size":"4.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5111"}],"country":"United States","state":"New Hampshire","city":"Nottingham","otherGeospatial":"Pawtuckaway Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.1595630645752,\n              43.08080002811761\n            ],\n            [\n              -71.14797592163086,\n              43.08080002811761\n            ],\n            [\n              -71.14797592163086,\n              43.08650455068649\n            ],\n            [\n              -71.1595630645752,\n              43.08650455068649\n            ],\n            [\n              -71.1595630645752,\n              43.08080002811761\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto: dc_nweng@usgs.gov\" data-mce-href=\"mailto: dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>331 Commerce Way, Suite 2<br>Pembroke, NH 03275</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Objectives and Approach</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Selected References</li><li>Appendix 1. The Virtual Beach Modeling Tool</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2019-11-25","noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Coles, James F. 0000-0002-1953-012X jcoles@usgs.gov","orcid":"https://orcid.org/0000-0002-1953-012X","contributorId":2239,"corporation":false,"usgs":true,"family":"Coles","given":"James","email":"jcoles@usgs.gov","middleInitial":"F.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":772439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bush, Kathleen F.","contributorId":219516,"corporation":false,"usgs":false,"family":"Bush","given":"Kathleen","email":"","middleInitial":"F.","affiliations":[{"id":40019,"text":"NH-Dept. Health and Human Services","active":true,"usgs":false}],"preferred":false,"id":772440,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70208559,"text":"70208559 - 2019 - Assessing the ecological impacts of biomass harvesting along a disturbance severity gradient","interactions":[],"lastModifiedDate":"2020-02-17T07:00:24","indexId":"70208559","displayToPublicDate":"2019-11-23T06:59:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the ecological impacts of biomass harvesting along a disturbance severity gradient","docAbstract":"Disturbance is a central driver of forest development and ecosystem processes with variable effects within and across ecosystems.  Despite the high levels of variation in disturbance severity often observed in forests following natural and anthropogenic disturbance, studies quantifying disturbance impacts often rely on categorical classifications, thus limiting opportunities to examine potential gradients in ecosystem response to a given disturbance or management regime.  Given the potential increases in disturbance severity associated with global change, as well as shifts in management regimes related to procurement of biofuel feedstocks, there is an increasing need to quantitatively describe disturbance severity and associated responses of forest development, soil processes, and structural conditions.  This study took advantage of two, replicated large-scale studies of forest biomass harvesting in Populus tremuloides and Pinus bansksiana forests, respectively, to develop and test the utility of a continuous, quantitative index of disturbance severity (DSI) for describing post-harvest response of plant communities and nutrient pools to different levels of biomass removal and legacy retention (i.e., live trees and coarse woody material). There was a high-degree of variability in DSI within categorical treatments associated with different levels of legacy retention and regression models using DSI as a predictor explained a portion of the variation (>50%) for many of the ecosystem- and community-level responses to biomass harvesting examined. Nutrient losses associated with biomass harvesting were positively related to disturbance severity, particularly in P. tremuloides forests, with post-harvest nutrient availability generally declining along the gradient of impacts. Consistent with expectations from ecological theory, species richness and diversity of woody plant communities were greatest at intermediate disturbance severities and regeneration densities of dominant trees species most abundant at highest levels of disturbance. Although categorical benchmarks will continue to be the primary way through which management guidelines are conveyed to practitioners, evaluation of their effectiveness at sustaining ecosystem functioning should be through continuous analyses, such as the DSI approach used in this study, to allow for the identification of minimum benchmarks that ensure a range of desirable outcomes exist across managed landscapes.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2042","usgsCitation":"Kurth, V.J., Amato, A.W., Bradford, J., Palik, B.J., and Looney, C.E., 2019, Assessing the ecological impacts of biomass harvesting along a disturbance severity gradient: Ecological Applications, e02042, 11 p., https://doi.org/10.1002/eap.2042.","productDescription":"e02042, 11 p.","ipdsId":"IP-101814","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":372378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Kurth, Valerie J.","contributorId":222542,"corporation":false,"usgs":false,"family":"Kurth","given":"Valerie","email":"","middleInitial":"J.","affiliations":[{"id":40556,"text":"University of Minnesota, Department of Forest Resources, Green Hall, 1530 Cleveland Avenue N, St. Paul, MN 55108","active":true,"usgs":false}],"preferred":false,"id":782483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amato, Anthony W.D.","contributorId":222543,"corporation":false,"usgs":false,"family":"Amato","given":"Anthony","email":"","middleInitial":"W.D.","affiliations":[{"id":40557,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources, 81 Carrigan Drive, Burlington, VT 05095, USA","active":true,"usgs":false}],"preferred":false,"id":782484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palik, Brian J.","contributorId":190301,"corporation":false,"usgs":false,"family":"Palik","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":782486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Looney, Christopher E.","contributorId":222544,"corporation":false,"usgs":false,"family":"Looney","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":40558,"text":"University of Minnesota, Department of Forest Resources, Green Hall, 1530 Cleveland Ave. N, St. Paul, MN 55108, USA","active":true,"usgs":false}],"preferred":false,"id":782487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70207039,"text":"70207039 - 2019 - Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization","interactions":[],"lastModifiedDate":"2019-12-05T06:36:50","indexId":"70207039","displayToPublicDate":"2019-11-21T15:26:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3649,"text":"Tree Physiology","active":true,"publicationSubtype":{"id":10}},"title":"Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization","docAbstract":"Drought frequency and intensity are projected to increase throughout the southeastern USA, the natural range of loblolly pine (Pinus taeda L.), and are expected to have major ecological and economic implications. We analyzed the carbon and oxygen isotopic compositions in tree ring cellulose of loblolly pine in a factorial drought (~30% throughfall reduction) and fertilization experiment, supplemented with trunk sap flow, allometry and microclimate data. We then simulated leaf temperature and applied a multi-dimensional sensitivity analysis to interpret the changes in the oxygen isotope data. This analysis found that the observed changes in tree ring cellulose could only be accounted for by inferring a change in the isotopic composition of the source water, indicating that the drought treatment increased the uptake of stored moisture from earlier precipitation events. The drought treatment also increased intrinsic water-use efficiency, but had no effect on growth, indicating that photosynthesis remained relatively unaffected despite 19% decrease in canopy conductance. In contrast, fertilization increased growth, but had no effect on the isotopic composition of tree ring cellulose, indicating that the fertilizer gains in biomass were attributable to greater leaf area and not to changes in leaf-level gas exchange. The multi-dimensional sensitivity analysis explored model behavior under different scenarios, highlighting the importance of explicit consideration of leaf temperature in the oxygen isotope discrimination (Δ18Oc) simulation and is expected to expand the inference space of the Δ18Oc models for plant ecophysiological studies.","language":"English","publisher":"Oxford Academic","doi":"10.1093/treephys/tpz096","usgsCitation":"Lin, W., Domec, J., Ward, E., Marshall, J.D., King, J.S., Laviner, M.A., Fox, T.R., West, J.B., Sun, G., McNulty, S., and Noormets, A., 2019, Using δ13C and δ18O to analyze loblolly pine (Pinus taeda L.) response to experimental drought and fertilization: Tree Physiology, tpz096, https://doi.org/10.1093/treephys/tpz096.","productDescription":"tpz096","ipdsId":"IP-109073","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459124,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/treephys/tpz096","text":"External Repository"},{"id":369919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Wen","contributorId":221015,"corporation":false,"usgs":false,"family":"Lin","given":"Wen","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":776600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Domec, Jean-Christophe","contributorId":146460,"corporation":false,"usgs":false,"family":"Domec","given":"Jean-Christophe","email":"","affiliations":[],"preferred":false,"id":776601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":221014,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":776599,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marshall, John D.","contributorId":176597,"corporation":false,"usgs":false,"family":"Marshall","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":776602,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, John S","contributorId":221017,"corporation":false,"usgs":false,"family":"King","given":"John","email":"","middleInitial":"S","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":776604,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laviner, Marshall A.","contributorId":221018,"corporation":false,"usgs":false,"family":"Laviner","given":"Marshall","email":"","middleInitial":"A.","affiliations":[{"id":40311,"text":"Virginia Polytechnic Institute and University","active":true,"usgs":false}],"preferred":false,"id":776605,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fox, Thomas R","contributorId":221016,"corporation":false,"usgs":false,"family":"Fox","given":"Thomas","email":"","middleInitial":"R","affiliations":[{"id":40311,"text":"Virginia Polytechnic Institute and University","active":true,"usgs":false}],"preferred":false,"id":776603,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"West, Jason B.","contributorId":221019,"corporation":false,"usgs":false,"family":"West","given":"Jason","email":"","middleInitial":"B.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":776606,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":776607,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McNulty, Steve G","contributorId":145897,"corporation":false,"usgs":false,"family":"McNulty","given":"Steve G","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":776608,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Noormets, Asko","contributorId":217423,"corporation":false,"usgs":false,"family":"Noormets","given":"Asko","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":776609,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70208996,"text":"70208996 - 2019 - General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud","interactions":[],"lastModifiedDate":"2020-03-10T13:53:55","indexId":"70208996","displayToPublicDate":"2019-11-21T13:47:56","publicationYear":"2019","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":"General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud","docAbstract":"The traditional practice to assess accuracy in lidar data involves calculating RMSEz (root mean square error of the vertical component). Accuracy assessment of lidar point clouds in full 3D (dimension) is not routinely performed. The main challenge in assessing accuracy in full 3D is how to identify a conjugate point of a ground-surveyed checkpoint in the lidar point cloud with the smallest possible uncertainty value.  Relatively coarse point-spacing in airborne lidar data makes it challenging to determine a conjugate point accurately. As a result, a substantial unwanted error is added to the inherent positional uncertainty of the lidar data. Unless we keep this additional error small enough, the 3D accuracy assessment result will not properly represent the inherent uncertainty. We call this added error “external uncertainty,” which is associated with conjugate point identification. This research developed a general external uncertainty model using three-plane intersections and accounts for several factors (sensor precision, feature dimension, and point density). This method can be used for lidar point cloud data from a wide range of sensor qualities, point densities, and sizes of the features of interest. The external uncertainty model was derived as a semi-analytical function that takes the number of points on a plane as an input. It is a normalized general function that can be scaled by smooth surface precision (SSP) of a lidar system. This general uncertainty model provides a quantitative guideline on the required conditions for the conjugate point based on the geometric features. Applications of external uncertainty model was demonstrated using various lidar point cloud data from US Geological Survey (USGS) 3D Elevation Program (3DEP) library to determine the valid conditions for a conjugate point from three-plane.","language":"English","publisher":"MDPI","doi":"10.3390/rs11232737","usgsCitation":"Kim, M., Park, S., Danielson, J.J., Irwin, J., Stensaas, G.L., Stoker, J.M., and Nimetz, J., 2019, General external uncertainty models of three-plane intersection point for 3D absolute accuracy assessment of lidar point cloud: Remote Sensing, v. 11, no. 23, 2737, 18 p., https://doi.org/10.3390/rs11232737.","productDescription":"2737, 18 p.","ipdsId":"IP-113404","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":459128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11232737","text":"Publisher Index Page"},{"id":373048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"23","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":784451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":784452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":784455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":784456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nimetz, Joshua 0000-0002-7132-9992","orcid":"https://orcid.org/0000-0002-7132-9992","contributorId":223183,"corporation":false,"usgs":true,"family":"Nimetz","given":"Joshua","email":"","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":784457,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70207442,"text":"70207442 - 2019 - Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","interactions":[],"lastModifiedDate":"2020-07-09T14:28:34.224535","indexId":"70207442","displayToPublicDate":"2019-11-21T13:12:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA","docAbstract":"The 72-km-long Teton normal fault bounds the eastern base of the Teton Range in northwestern Wyoming, USA. Although geomorphic surfaces along the fault record latest Pleistocene to Holocene fault movement, the postglacial earthquake history of the fault has remained enigmatic. We excavated a paleoseismic trench at the Buffalo Bowl site along the southernmost part of the fault to determine its Holocene rupture history and slip rate. At the site, ∼6.3 m of displacement postdates an early Holocene (ca. 10.5 ka) alluvial-fan surface. We document evidence of three surface-faulting earthquakes based on packages of scarp-derived colluvium that postdate the alluvial-fan units. Bayesian modeling of radiocarbon and luminescence ages yields earthquake times of ca. 9.9 ka, ca. 7.1 ka, and ca. 4.6 ka, forming the longest, most complete paleoseismic record of the Teton fault. We integrate these data with a displaced deglacial surface 4 km NE at Granite Canyon to calculate a postglacial to mid-Holocene (14.4−4.6 ka) slip rate of ∼1.1 mm/yr. Our analysis also suggests that the postglacial to early Holocene (14.4−9.9 ka) slip rate exceeds the Holocene (9.9−4.6 ka) rate by a factor of ∼2 (maximum of 3); however, a uniform rate for the fault is possible considering the 95% slip-rate errors. The ∼5 k.y. elapsed time since the last rupture of the southernmost Teton fault implies a current slip deficit of ∼4−5 m, which is possibly explained by spatially/temporally incomplete paleoseismic data, irregular earthquake recurrence, and/or variable per-event displacement. Our study emphasizes the importance of minimizing slip-rate uncertainties by integrating paleoseismic and geomorphic data sets and capturing multiple earthquake cycles.","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35363.1","usgsCitation":"DuRoss, C., Gold, R.D., Briggs, R.W., Delano, J.E., Ostenaa, D.A., Zellman, M., Cholewinski, N., Wittke, S., and Mahan, S.A., 2019, Holocene earthquake history and slip rate of the southern Teton fault, Wyoming, USA: Geological Society of America Bulletin, v. 132, no. 7-8, p. 1566-1586, https://doi.org/10.1130/B35363.1.","productDescription":"21 p.","startPage":"1566","endPage":"1586","ipdsId":"IP-111318","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"132","issue":"7-8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"DuRoss, Christopher B. 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Delano, Jaime E. 0000-0003-2601-2600","orcid":"https://orcid.org/0000-0003-2601-2600","contributorId":210604,"corporation":false,"usgs":true,"family":"Delano","given":"Jaime","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ostenaa, Dean A.","contributorId":39467,"corporation":false,"usgs":false,"family":"Ostenaa","given":"Dean","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":778055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zellman, Mark","contributorId":167020,"corporation":false,"usgs":false,"family":"Zellman","given":"Mark","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":778056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cholewinski, Nicole","contributorId":221401,"corporation":false,"usgs":false,"family":"Cholewinski","given":"Nicole","email":"","affiliations":[{"id":40365,"text":"GEI Consultants","active":true,"usgs":false}],"preferred":false,"id":778057,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wittke, Seth","contributorId":221402,"corporation":false,"usgs":false,"family":"Wittke","given":"Seth","email":"","affiliations":[{"id":40366,"text":"Wyoming State Geological  Survey","active":true,"usgs":false}],"preferred":false,"id":778058,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":778059,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70209051,"text":"70209051 - 2019 - Using age tracers and decadal sampling to discern trends in nitrate, arsenic and uranium in groundwater beneath irrigated cropland","interactions":[],"lastModifiedDate":"2020-03-12T13:16:44","indexId":"70209051","displayToPublicDate":"2019-11-21T13:06:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Using age tracers and decadal sampling to discern trends in nitrate, arsenic and uranium in groundwater beneath irrigated cropland","docAbstract":"Repeat sampling and age tracers were used to examine trends in nitrate, arsenic and uranium concentrations in groundwater beneath irrigated cropland. Much higher nitrate concentrations in shallow modern groundwater were observed at both the Columbia Plateau and High Plains sites (median values of 10.2 and 15.4 mg/L as N, respectively) than in groundwater that recharged prior to the onset of intensive irrigation (median values of <1 and <4 mg/L as N, respectively). Repeat sampling of these well networks indicates that high nitrate concentrations in modern, shallow groundwater have been sustained for decades, posing a future risk to older, deeper groundwater used for drinking water. In fact, nitrate concentrations in older modern water (30-60 years since recharge) at the High Plains site have increased in the last decade. Groundwater irrigated areas in the Columbia Plateau tend to have higher nitrate concentrations than surface-water irrigated areas suggesting that repeated dissolution of land applied fertilizer during recirculation may be an important factor causing high nitrate concentrations in groundwater. Mobilization of uranium and arsenic by land surface activities is suggested by the higher concentrations of these constituents in modern, shallow groundwater than in older, deeper groundwater at the Columbia Plateau site. Bicarbonate concentrations in modern groundwater are positively correlated with uranium (r=0.72, p<0.01), suggesting bicarbonate may mobilize uranium in this system. A positive correlation between arsenic and phosphorus concentrations in modern groundwater (r=0.55, p<0.01) suggests that phosphate from fertilizer outcompetes arsenate for sorption sites, mobilizing sorbed arsenic derived from past pesticide use or other sources.","language":"English","publisher":"ACS","doi":"10.1021/acs.est.9b03459","usgsCitation":"Tesoriero, A.J., Burow, K.R., Frans, L., Haynes, J.V., Hobza, C.M., Lindsey, B.D., and Solder, J.E., 2019, Using age tracers and decadal sampling to discern trends in nitrate, arsenic and uranium in groundwater beneath irrigated cropland: Environmental Science and Technology, v. 53, no. 24, p. 14152-14164, https://doi.org/10.1021/acs.est.9b03459.","productDescription":"13 p.","startPage":"14152","endPage":"14164","ipdsId":"IP-107801","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":437278,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UY8L30","text":"USGS data release","linkHelpText":"Dissolved gas and tracer concentrations from the Columbia Plateau Aquifer, Vertical Flowpath Study Network"},{"id":437277,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VLFXTM","text":"USGS data release","linkHelpText":"Dissolved Gas and Tracer Concentrations for the High Plains Aquifer, Vertical Flowpath Study Network"},{"id":373200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"24","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burow, Karen R. 0000-0001-6006-6667 krburow@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-6667","contributorId":1504,"corporation":false,"usgs":true,"family":"Burow","given":"Karen","email":"krburow@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frans, Lonna 0000-0002-3217-1862","orcid":"https://orcid.org/0000-0002-3217-1862","contributorId":210896,"corporation":false,"usgs":true,"family":"Frans","given":"Lonna","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haynes, Jonathan V. 0000-0001-6530-6252 jhaynes@usgs.gov","orcid":"https://orcid.org/0000-0001-6530-6252","contributorId":3113,"corporation":false,"usgs":true,"family":"Haynes","given":"Jonathan","email":"jhaynes@usgs.gov","middleInitial":"V.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784635,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784636,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Solder, John E. 0000-0002-0660-3326","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":201953,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784637,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70206758,"text":"70206758 - 2019 - Synergistic interaction of climate and land-use drivers alter the function of North American, Prairie-pothole Wetlands","interactions":[],"lastModifiedDate":"2019-11-22T11:05:51","indexId":"70206758","displayToPublicDate":"2019-11-21T11:03:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Synergistic interaction of climate and land-use drivers alter the function of North American, Prairie-pothole Wetlands","docAbstract":"Prairie-pothole wetlands provide the critical habitat necessary for supporting North American migratory waterfowl populations. However, climate and land-use change threaten the sustainability of these wetland ecosystems. Very few experiments and analyses have been designed to investigate the relative impacts of climate and land-use change drivers, as well as the antagonistic or synergistic interactions among these drivers on ecosystem processes. Prairie-pothole wetland water budgets are highly dependent on atmospheric inputs and especially surface runoff, which makes them especially susceptible to changes in climate and land use. Here, we present the history of prairie-pothole climate and land-use change research and address the following research questions: 1) What are the relative effects of climate and land-use change on the sustainability of prairie-pothole wetlands? and 2) Do the effects of climate and land-use change interact differently under different climatic conditions? To address these research questions, we modeled 25 wetland basins (1949–2018) and measured the response of the lowest wetland in the watershed to wetland drainage and climate variability. We found that during an extremely wet period (1993–2000) wetland drainage decreased the time at which the lowest wetland reached its spill point by four years, resulting in 10 times the amount of water spilling out of the watershed towards local stream networks. By quantifying the relative effects of both climate and land-use drivers on wetland ecosystems our findings can help managers cope with uncertainties about flooding risks and provide insight into how to manage wetlands to restore functionality","language":"English","publisher":"MDPI","doi":"10.3390/su11236581","usgsCitation":"McKenna, O.P., Kucia, S.R., Mushet, D.M., Anteau, M.J., and Wiltermuth, M.T., 2019, Synergistic interaction of climate and land-use drivers alter the function of North American, Prairie-pothole Wetlands: Sustainability, v. 11, no. 23, 6581, https://doi.org/10.3390/su11236581.","productDescription":"6581","ipdsId":"IP-112410","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":459133,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su11236581","text":"Publisher Index Page"},{"id":369465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.798828125,\n              52.32191088594773\n            ],\n            [\n              -103.88671875,\n              53.225768435790194\n            ],\n            [\n              -115.224609375,\n              54.521081495443596\n            ],\n            [\n              -113.99414062499999,\n              47.635783590864854\n            ],\n            [\n              -103.798828125,\n              41.83682786072714\n            ],\n            [\n              -94.39453125,\n              38.54816542304656\n            ],\n            [\n              -88.857421875,\n              38.95940879245423\n            ],\n            [\n              -89.736328125,\n              44.5278427984555\n            ],\n            [\n              -103.798828125,\n              52.32191088594773\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"23","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":775691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kucia, Samuel Richard","contributorId":220767,"corporation":false,"usgs":false,"family":"Kucia","given":"Samuel","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":775690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":775694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":775693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":775692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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