{"pageNumber":"426","pageRowStart":"10625","pageSize":"25","recordCount":40802,"records":[{"id":70189582,"text":"70189582 - 2017 - Allowable take of a population of red-winged blackbirds in the northern Great Plains","interactions":[],"lastModifiedDate":"2017-07-18T08:55:31","indexId":"70189582","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Allowable take of a population of red-winged blackbirds in the northern Great Plains","docAbstract":"<p>Red-winged blackbirds (<i>Agelaius phoeniceus</i>) are protected under the Migratory Bird Treaty Act (MBTA), which has provisions against take. Blackbirds may be taken legally without a Federal permit, however, under an existing Depredation Order (50 CFR 21.43), which allows for take of blackbirds that are in the process of doing, or about to do, agricultural damage. Modeling the effect of take on blackbird population allows us to balance the conservation protections of the MBTA with the protection of agricultural interests. A quantitative framework based on harvest theory, demography, and population status has been used to assess the allowable take of a number of species of birds under the MBTA. In this chapter, we calculate allowable levels of take for two populations of red-winged blackbirds in the northern Great Plains from estimates of intrinsic growth rate and population size.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecology and management of blackbirds (Icteridae) in North America","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","publisherLocation":"Boca Raton, FL","isbn":"9781498799614","usgsCitation":"Runge, M.C., and Sauer, J.R., 2017, Allowable take of a population of red-winged blackbirds in the northern Great Plains, chap. <i>of</i> Ecology and management of blackbirds (Icteridae) in North America, p. 191-206.","productDescription":"16 p.","startPage":"191","endPage":"206","ipdsId":"IP-080852","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":343970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343962,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Ecology-and-Management-of-Blackbirds-Icteridae-in-North-America/Linz-Avery-Dolbeer/p/book/9781498799614"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e22e4b0d1f9f0640750","contributors":{"authors":[{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":705298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":705299,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189377,"text":"70189377 - 2017 - The long-term legacy of geomorphic and riparian vegetation feedbacks on the dammed Bill Williams River, Arizona, USA","interactions":[],"lastModifiedDate":"2017-07-12T09:18:10","indexId":"70189377","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"The long-term legacy of geomorphic and riparian vegetation feedbacks on the dammed Bill Williams River, Arizona, USA","docAbstract":"<div class=\"article-section__content mainAbstract\"><p>On alluvial rivers, fluvial landforms and riparian vegetation communities codevelop as a result of feedbacks between plants and abiotic processes. The influence of vegetation on river channel and floodplain geomorphology can be particularly strong on dammed rivers with altered hydrology and reduced flood disturbance. We used a 56-year series of aerial photos on the dammed Bill Williams River (Arizona, USA) to investigate how (a) different woody riparian vegetation types influence river channel planform and (b) how different fluvial landforms drive the composition of riparian plant communities over time. We mapped vegetation types and geomorphic surfaces and quantified how relations between fluvial and biotic processes covaried over time using linear mixed models. In the decades after the dam was built, woody plant cover within the river's bottomland nearly doubled, narrowing the active channel by 60% and transforming its planform from wide and braided to a single thread and more sinuous channel. Compared with native cottonwood–willow vegetation, nonnative tamarisk locally induced a twofold greater reduction in channel braiding. Vegetation expanded at different rates depending on the type of landform, with tamarisk cover on former high-flow channels increasing 17% faster than cottonwood–willow. Former low-flow channels with frequent inundation supported a greater increase in cottonwood–willow relative to tamarisk. These findings give insight into how feedbacks between abiotic and biotic processes in river channels accelerate and fortify changes triggered by dam construction, creating river systems increasingly distinct from predam ecological communities and landforms, and progressively more resistant to restoration of predam forms and processes.</p></div><div class=\"accordion\"><div class=\"accordion__title\"><br data-mce-bogus=\"1\"></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/eco.1839","usgsCitation":"Kui, L., Stella, J.C., Shafroth, P.B., House, K., and Wilcox, A., 2017, The long-term legacy of geomorphic and riparian vegetation feedbacks on the dammed Bill Williams River, Arizona, USA: Ecohydrology, v. 10, no. 4, e1839, https://doi.org/10.1002/eco.1839.","productDescription":"e1839","ipdsId":"IP-073658","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":343642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"5967353fe4b0d1f9f05dd7c4","contributors":{"authors":[{"text":"Kui, Li","contributorId":194515,"corporation":false,"usgs":false,"family":"Kui","given":"Li","email":"","affiliations":[],"preferred":false,"id":704425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stella, John C.","contributorId":174328,"corporation":false,"usgs":false,"family":"Stella","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":27417,"text":"Department of Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY 13210 USA","active":true,"usgs":false}],"preferred":false,"id":704426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":704424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":704427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilcox, Andrew C.","contributorId":25064,"corporation":false,"usgs":true,"family":"Wilcox","given":"Andrew C.","affiliations":[],"preferred":false,"id":704428,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189424,"text":"70189424 - 2017 - Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii)","interactions":[],"lastModifiedDate":"2017-07-13T08:53:06","indexId":"70189424","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (<i>Gopherus agassizii</i>)","title":"Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii)","docAbstract":"<p><span>The analysis of blood constituents is a widely used tool to aid in monitoring of animal health and disease. However, classic blood diagnostics (i.e. hematologic and plasma biochemical values) often do not provide sufficient information to determine the state of an animal’s health. Field studies on wild tortoises and other reptiles have had limited success in drawing significant inferences between blood diagnostics and physiological and immunological condition. However, recent research using gene transcription profiling in the threatened Mojave desert tortoise (</span><i>Gopherus agassizii</i><span>) has proved useful in identifying immune or physiologic responses and overall health. To improve our understanding of health and immune function in tortoises, we evaluated both standard blood diagnostic (body condition, hematologic, plasma biochemistry values, trace elements, plasma proteins, vitamin A levels) and gene transcription profiles in 21 adult tortoises (11 clinically abnormal; 10 clinically normal) from Clark County, NV, USA. Necropsy and histology evaluations from clinically abnormal tortoises revealed multiple physiological complications, with moderate to severe rhinitis or pneumonia being the primary cause of morbidity in all but one of the examined animals. Clinically abnormal tortoises had increased transcription for four genes (SOD, MyD88, CL and Lep), increased lymphocyte production, biochemical enzymes and organics, trace elements of copper, and decreased numbers of leukocytes. We found significant positive correlations between increased transcription for SOD and increased trace elements for copper, as well as genes MyD88 and Lep with increased inflammation and microbial insults. Improved methods for health assessments are an important element of monitoring tortoise population recovery and can support the development of more robust diagnostic measures for ill animals, or individuals directly impacted by disturbance.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/cox037","usgsCitation":"Drake, K.K., Bowen, L., Lewison, R.L., Esque, T., Nussear, K., Braun, J., Waters-Dynes, S.C., and Miles, A.K., 2017, Coupling gene-based and classic veterinary diagnostics improves interpretation of health and immune function in the Agassiz’s desert tortoise (Gopherus agassizii): Conservation Physiology, v. 5, no. 1, Article cox037; 17 p., https://doi.org/10.1093/conphys/cox037.","productDescription":"Article cox037; 17 p.","ipdsId":"IP-083337","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/cox037","text":"Publisher Index Page"},{"id":343761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-16","publicationStatus":"PW","scienceBaseUri":"5967353ce4b0d1f9f05dd7b6","contributors":{"authors":[{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewison, Rebecca L.","contributorId":194537,"corporation":false,"usgs":false,"family":"Lewison","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":704586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":168763,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":704581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":704587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Braun, Josephine","contributorId":194539,"corporation":false,"usgs":false,"family":"Braun","given":"Josephine","affiliations":[{"id":17905,"text":"San Diego Zoo Global, San Diego, CA, USA","active":true,"usgs":false}],"preferred":false,"id":704588,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":704585,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70189422,"text":"70189422 - 2017 - Ecohydrological role of biological soil crusts across a gradient in levels of development","interactions":[],"lastModifiedDate":"2017-10-08T11:50:25","indexId":"70189422","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrological role of biological soil crusts across a gradient in levels of development","docAbstract":"<p><span>Though biological soil crusts (biocrusts) form abundant covers in arid and semiarid regions, their competing effects on soil hydrologic conditions are rarely accounted for in models. This study presents the modification of a soil water balance model to account for the presence of biocrusts at different levels of development (LOD) and their impact on one-dimensional hydrologic processes during warm and cold seasons. The model is developed, tested, and applied to study the hydrologic controls of biocrusts in context of a long-term manipulative experiment equipped with meteorological and soil moisture measurements in a Colorado Plateau ecosystem near Moab, Utah. The climate manipulation treatments resulted in distinct biocrust communities, and model performance with respect to soil moisture was assessed in experimental plots with varying LOD as quantified through a field-based roughness index (</span><i>RI</i><span>). Model calibration and testing yielded excellent comparisons to observations and smooth variations of biocrust parameters with<span>&nbsp;</span></span><i>RI</i><span><span>&nbsp;</span>approximated through simple regressions. The model was then used to quantify how LOD affects soil infiltration, evapotranspiration, and runoff under calibrated conditions and in simulation experiments with gradual modifications in biocrust porosity and hydraulic conductivity. Simulation results show that highly developed biocrusts modulate soil moisture nonlinearly with LOD by altering soil infiltration and buffering against evapotranspiration losses, with small impacts on runoff. The nonlinear and threshold variations of the soil water balance in the presence of biocrusts of varying LOD helps explain conflicting outcomes of various field studies and sheds light on the ecohydrological role of biocrusts in arid and semiarid ecosystems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eco.1875","usgsCitation":"Whitney, K.M., Vivoni, E.R., Duniway, M.C., Bradford, J.B., Reed, S.C., and Belnap, J., 2017, Ecohydrological role of biological soil crusts across a gradient in levels of development: Ecohydrology, v. 10, no. 7, Article e1875; 18 p., https://doi.org/10.1002/eco.1875.","productDescription":"Article e1875; 18 p.","ipdsId":"IP-077787","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":343759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","city":"Moab","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.51515197753906,\n              38.652807047773784\n            ],\n            [\n              -109.34829711914062,\n              38.652807047773784\n            ],\n            [\n              -109.34829711914062,\n              38.76318574559655\n            ],\n            [\n              -109.51515197753906,\n              38.76318574559655\n            ],\n            [\n              -109.51515197753906,\n              38.652807047773784\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-26","publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7be","contributors":{"authors":[{"text":"Whitney, Kristen M.","contributorId":194535,"corporation":false,"usgs":false,"family":"Whitney","given":"Kristen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":704573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vivoni, Enrique R.","contributorId":139052,"corporation":false,"usgs":false,"family":"Vivoni","given":"Enrique","email":"","middleInitial":"R.","affiliations":[{"id":12634,"text":"School of Earth and Space Exploration and School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":704574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":704577,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189423,"text":"70189423 - 2017 - The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake","interactions":[],"lastModifiedDate":"2017-07-12T17:58:31","indexId":"70189423","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effects of varying injection rates in Osage County, Oklahoma, on the 2016 <i>M</i><sub>w</sub>5.8 Pawnee earthquake","title":"The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake","docAbstract":"<p><span>The 2016&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;5.8 Pawnee earthquake occurred in a region with active wastewater injection into a basal formation group. Prior to the earthquake, fluid injection rates at most wells were relatively steady, but newly collected data show significant increases in injection rate in the years leading up to earthquake. For the same time period, the total volumes of injected wastewater were roughly equivalent between variable‐rate and constant‐rate wells. To understand the possible influence of these changes in injection, we simulate the variable‐rate injection history and its constant‐rate equivalent in a layered poroelastic half‐space to explore the interplay between pore‐pressure effects and poroelastic effects on the fault leading up to the mainshock. In both cases, poroelastic stresses contribute a significant proportion of Coulomb failure stresses on the fault compared to pore‐pressure increases alone, but the resulting changes in seismicity rate, calculated using a rate‐and‐state frictional model, are many times larger when poroelastic effects are included, owing to enhanced stressing rates. In particular, the variable‐rate simulation predicts more than an order of magnitude increase in seismicity rate above background rates compared to the constant‐rate simulation with equivalent volume. The observed cumulative density of earthquakes prior to the mainshock within 10&nbsp;km of the injection source exhibits remarkable agreement with seismicity predicted by the variable‐rate injection case.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170003","usgsCitation":"Barbour, A., Norbeck, J.H., and Rubinstein, J.L., 2017, The effects of varying injection rates in Osage County, Oklahoma, on the 2016 Mw5.8 Pawnee earthquake: Seismological Research Letters, v. 88, no. 4, p. 1040-1053, https://doi.org/10.1785/0220170003.","productDescription":"14 p.","startPage":"1040","endPage":"1053","ipdsId":"IP-082545","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":343760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"5967353ee4b0d1f9f05dd7bb","contributors":{"authors":[{"text":"Barbour, Andrew J. 0000-0002-6890-2452 abarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":140443,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew J.","email":"abarbour@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":704578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norbeck, Jack H.","contributorId":194536,"corporation":false,"usgs":true,"family":"Norbeck","given":"Jack","email":"","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":704580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":704579,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70190049,"text":"70190049 - 2017 - The estimation of growth dynamics for Pomacea maculata from hatchling to adult","interactions":[],"lastModifiedDate":"2017-08-07T16:58:46","indexId":"70190049","displayToPublicDate":"2017-07-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The estimation of growth dynamics for <i>Pomacea maculata</i> from hatchling to adult","title":"The estimation of growth dynamics for Pomacea maculata from hatchling to adult","docAbstract":"<p><i>Pomacea maculata</i><span><span>&nbsp;</span>is a relatively new invasive species to the Gulf Coast region and potentially threatens local agriculture (rice) and ecosystems (aquatic vegetation). The population dynamics of<span>&nbsp;</span></span><i>P.&nbsp;maculata</i><span><span>&nbsp;</span>have largely been unquantified, and therefore, scientists and field-workers are ill-equipped to accurately project population sizes and the resulting impact of this species. We studied the growth of<span>&nbsp;</span></span><i>P.&nbsp;maculata</i><span><span>&nbsp;</span>ranging in weights from 6 to 105&nbsp;g, identifying the sex of the animals when possible. Our studied population had a 4:9 male:female sex ratio. We present the findings from initial analysis of the individual growth data of males and females, from which it was apparent that females were generally larger than males and that small snails grew faster than larger snails. Since efforts to characterize the male and female growth rates from individual data do not yield statistically supported estimates, we present the estimation of several parameterized growth rate functions within a population-level mathematical model. We provide a comparison of the results using these various growth functions and discuss which best characterizes the dynamics of our observed population. We conclude that both males and females exhibit biphasic growth rates, and thus, their growth is size-dependent. Further, our results suggest that there are notable differences between males and females that are important to take into consideration in order to accurately model this species' population dynamics. Lastly, we include preliminary analyses of ongoing experiments to provide initial estimates of growth in the earliest life stages (hatchling to ≈6&nbsp;g).</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1840","usgsCitation":"Sutton, K.L., Zhao, L., and Carter, J., 2017, The estimation of growth dynamics for Pomacea maculata from hatchling to adult: Ecosphere, v. 8, no. 7, e01840: 22 p., https://doi.org/10.1002/ecs2.1840.","productDescription":"e01840: 22 p.","ipdsId":"IP-081732","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469683,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1840","text":"Publisher Index Page"},{"id":438268,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23XFZ","text":"USGS data release","linkHelpText":"Data for the estimation of growth dynamics for Pomacea maculata from hatchling to adult, 10/10/13 to 9/25/15"},{"id":344621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-28","publicationStatus":"PW","scienceBaseUri":"59897c15e4b09fa1cb0c2bff","contributors":{"authors":[{"text":"Sutton, Karyn L.","contributorId":195516,"corporation":false,"usgs":false,"family":"Sutton","given":"Karyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":707324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhao, Lihong","contributorId":187552,"corporation":false,"usgs":false,"family":"Zhao","given":"Lihong","email":"","affiliations":[],"preferred":false,"id":707325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":707323,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187574,"text":"sim3380 - 2017 - Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","interactions":[],"lastModifiedDate":"2017-07-11T16:39:14","indexId":"sim3380","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3380","title":"Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016","docAbstract":"<p>The inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, was mapped in 2011. Since that time, the saltwater interface has continued to move inland. The interface is near several active well fields; therefore, an updated approximation of the inland extent of saltwater and an improved understanding of the rate of movement of the saltwater interface are necessary. A geographic information system was used to create a map using the data collected by the organizations that monitor water salinity in this area. An average rate of saltwater interface movement of 140 meters per year was estimated by dividing the distance between two monitoring wells (TPGW-7L and Sec34-MW-02-FS) by the travel time. The travel time was determined by estimating the dates of arrival of the saltwater interface at the wells and computing the difference. This estimate assumes that the interface is traveling east to west between the two monitoring wells. Although monitoring is spatially limited in this area and some of the wells are not ideally designed for salinity monitoring, the monitoring network in this area is improving in spatial distribution and most of the new wells are well designed for salinity monitoring. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3380","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2017, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016: U.S. Geological Survey Scientific Investigations Map 3380, 8-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3380.","productDescription":"Pamphlet: vi, 8 p.; Sheet: 20.00 x 19.64 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080722","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":343395,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R78CF8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data pertaining to mapping the approximate inland extent of saltwater at the base of the Biscayne aquifer in the Model Land Area of Miami-Dade County, Florida, 2016"},{"id":343258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3380/coverthb.jpg"},{"id":343259,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3380/sim3380.pdf","text":"Map","size":"867 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380"},{"id":343260,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3380/sim3380_pamphlet.pdf","text":"Pamphlet","size":"503 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3380 Pamphlet"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Biscayne Aquifer, Model Land Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.595703125,\n              25.243453810607868\n            ],\n            [\n              -80.25787353515625,\n              25.243453810607868\n            ],\n            [\n              -80.25787353515625,\n              25.58456258101669\n            ],\n            [\n              -80.595703125,\n              25.58456258101669\n            ],\n            [\n              -80.595703125,\n              25.243453810607868\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_cf@usgs.gov\" data-mce-href=\"mailto:dc_cf@usgs.gov\">Director</a>, <a href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a><br>U.S. Geological Survey<br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559&nbsp;<br></p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-07-11","noUsgsAuthors":false,"publicationDate":"2017-07-11","publicationStatus":"PW","scienceBaseUri":"5965b1b7e4b0d1f9f05b3798","contributors":{"authors":[{"text":"Prinos, Scott T. 0000-0002-5776-8956 stprinos@usgs.gov","orcid":"https://orcid.org/0000-0002-5776-8956","contributorId":4045,"corporation":false,"usgs":true,"family":"Prinos","given":"Scott","email":"stprinos@usgs.gov","middleInitial":"T.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694618,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189326,"text":"70189326 - 2017 - Revised tephra volumes for Cascade Range volcanoes","interactions":[],"lastModifiedDate":"2017-07-11T13:07:21","indexId":"70189326","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","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":"Revised tephra volumes for Cascade Range volcanoes","docAbstract":"<p><span>Isopach maps from tephra eruptions from Mount St. Helens were reported in Carey et al. (1995) and for tephra eruptions from Glacier Peak in Gardner et al. (1998). For exponential thinning, the isopach data only define a single slope on a log thickness versus square root of area plot. Carey et al. (1995) proposed a model that was used to estimate a second slope, and volumes were presented in both studies using this model. A study by Sulpizio (2005) for estimating the second slope and square root of area where the lines intersect involves a systematic analysis of many eruptions to provide correlation equations. The purpose of this paper is to recalculate the volumes of Cascades eruptions and compare results from the two methods. In order to gain some perspective on the methods for estimating the second slope, we use data for thickness versus distance beyond the last isopach that are available for some of the larger eruptions in the Cascades. The thickness versus square root of area method is extended to thickness versus distance by developing an approximate relation between the two assuming elliptical isopachs with the source at one of the foci. Based on the comparisons made between the Carey et al. (1995) and Sulpizio (2005) methods, it is felt that the later method provides a better estimate of the second slope. For Mount St. Helens, the estimates of total volume using the Sulpizio (2005) method are generally smaller than those using the Carey et al. (1995) method. For the volume estimates of Carey et al. (1995), the volume of the May 18, 1980, eruption of Mount St. Helens is smaller than six of the eight previous eruptions. With the new volumes using the Sulpizio (2005) method, the 1980 eruption is smaller in volume than the upper end of the range for only three of the layers (Wn, Ye, and Yn) and is the same size as layer We. Thus the 1980 eruption becomes representative of the mid-range of volumes rather than being in the lower range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.04.021","usgsCitation":"Nathenson, M., 2017, Revised tephra volumes for Cascade Range volcanoes: Journal of Volcanology and Geothermal Research, v. 341, p. 42-52, https://doi.org/10.1016/j.jvolgeores.2017.04.021.","productDescription":"11 p.","startPage":"42","endPage":"52","ipdsId":"IP-082574","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascade Range volcanoes","volume":"341","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1b4e4b0d1f9f05b378e","contributors":{"authors":[{"text":"Nathenson, Manuel 0000-0002-5216-984X mnathnsn@usgs.gov","orcid":"https://orcid.org/0000-0002-5216-984X","contributorId":1358,"corporation":false,"usgs":true,"family":"Nathenson","given":"Manuel","email":"mnathnsn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":704187,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189313,"text":"70189313 - 2017 - Landscape context and the biophysical response of rivers to dam removal in the United States","interactions":[],"lastModifiedDate":"2018-08-10T16:32:39","indexId":"70189313","displayToPublicDate":"2017-07-11T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Landscape context and the biophysical response of rivers to dam removal in the United States","docAbstract":"<p><span>Dams have been a fundamental part of the U.S. national agenda over the past two hundred years. Recently, however, dam removal has emerged as a strategy for addressing aging, obsolete infrastructure and more than 1,100 dams have been removed since the 1970s. However, only 130 of these removals had any ecological or geomorphic assessments, and fewer than half of those included before- and after-removal (BAR) studies. In addition, this growing, but limited collection of dam-removal studies is limited to distinct landscape settings. We conducted a meta-analysis to compare the landscape context of existing and removed dams and assessed the biophysical responses to dam removal for 63 BAR studies. The highest concentration of removed dams was in the Northeast and Upper Midwest, and most have been removed from 3</span><sup>rd</sup><span><span>&nbsp;</span>and 4</span><sup>th</sup><span><span>&nbsp;</span>order streams, in low-elevation (&lt; 500 m) and low-slope (&lt; 5%) watersheds that have small to moderate upstream watershed areas (10–1000 km</span><sup>2</sup><span>) with a low risk of habitat degradation. Many of the BAR-studied removals also have these characteristics, suggesting that our understanding of responses to dam removals is based on a limited range of landscape settings, which limits predictive capacity in other environmental settings. Biophysical responses to dam removal varied by landscape cluster, indicating that landscape features are likely to affect biophysical responses to dam removal. However, biophysical data were not equally distributed across variables or clusters, making it difficult to determine which landscape features have the strongest effect on dam-removal response. To address the inconsistencies across dam-removal studies, we provide suggestions for prioritizing and standardizing data collection associated with dam removal activities.</span></p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0180107","usgsCitation":"Foley, M.M., Magilligan, F.J., Torgersen, C.E., Major, J.J., Anderson, C.W., Connolly, P., Wieferich, D.J., Shafroth, P.B., Evans, J.E., Infante, D.M., and Craig, L., 2017, Landscape context and the biophysical response of rivers to dam removal in the United States: PLoS ONE, v. 7, no. 12, e0180107: 24 p., https://doi.org/10.1371/journal.pone.0180107.","productDescription":"e0180107: 24 p.","ipdsId":"IP-084261","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":469686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0180107","text":"Publisher Index Page"},{"id":343554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70180011,"text":"sir20165082 - 2017 - Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007","interactions":[],"lastModifiedDate":"2017-07-11T09:09:19","indexId":"sir20165082","displayToPublicDate":"2017-07-10T15:00:00","publicationYear":"2017","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":"2016-5082","title":"Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007","docAbstract":"<p>Laurel Hill Creek is considered one of the most pristine waterways in southwestern Pennsylvania and has high recreational value as a high-quality cold-water fishery; however, the upper parts of the basin have documented water-quality impairments. Groundwater and surface water are withdrawn for public water supply and the basin has been identified as a Critical Water Planning Area (CWPA) under the State Water Plan. The U.S. Geological Survey, in cooperation with the Somerset County Conservation District, collected data and developed modeling tools to support the assessment of water-quality and water-quantity issues for a basin designated as a CWPA. Streams, springs, and groundwater wells were sampled for water quality in 2007. Streamflows were measured concurrent with water-quality sampling at main-stem sites on Laurel Hill Creek and tributaries in 2007. Stream temperatures were monitored continuously at five main-stem sites from 2007 to 2010. Water usage in the basin was summarized for 2003 and 2009 and a Water-Analysis Screening Tool (WAST) developed for the Pennsylvania State Water Plan was implemented to determine whether the water use in the basin exceeded the “safe yield” or “<i>the amount of water that can be withdrawn from a water resource over a period of time without impairing the long-term utility of a water resource</i>.” A groundwater and surface-water flow (GSFLOW) model was developed for Laurel Hill Creek and calibrated to the measured daily streamflow from 1991 to 2007 for the streamflow-gaging station near the outlet of the basin at Ursina, Pa. The CWPA designation requires an assessment of current and future water use. The calibrated GSFLOW model can be used to assess the hydrologic effects of future changes in water use and land use in the basin.</p><p>Analyses of samples collected for surface-water quality during base-flow conditions indicate that the highest nutrient concentrations in the main stem of Laurel Hill Creek were at sites in the northeastern part of the basin where agricultural activity is prominent. All of the total nitrogen (N) and a majority of the total phosphorus (P) concentrations in the main stem exceeded regional nutrient criteria levels of 0.31 and 0.01 milligrams per liter (mg/L), respectively. The highest total N and total P concentrations in the main stem were 1.42 and 0.06 mg/L, respectively. Tributary sites with the highest nutrient concentrations are in subbasins where treated wastewater is discharged, such as Kooser Run and Lost Creek. The highest total N and total P concentrations in subbasins were 3.45 and 0.11 mg/L, respectively. Dissolved chloride and sodium concentrations were highest in the upper part of the basin downstream from Interstate 76 because of road deicing salts. The mean base-flow concentrations of dissolved chloride and sodium were 117 and 77 mg/L, respectively, in samples from the main stem just below Interstate 76, and the mean concentrations in Clear Run were 210 and 118 mg/L, compared to concentrations less than 15 mg/L in tributaries that were not affected by highway runoff. Water quality in forested tributary subbasins underlain by the Allegheny and Pottsville Formations was influenced by acidic precipitation and, to a lesser extent, the underlying geology as indicated by pH values less than 5.0 and corresponding specific conductance ranging from 26 to 288 microsiemens per centimeter at 25 degrees Celsius for some samples; in contrast, pH values for main stem sites ranged from 6.6 to 8.5. Manganese (Mn) was the only dissolved constituent in the surface-water samples that exceeded the secondary maximum contaminant level (SMCL). More than one-half the samples from the main stem had Mn concentrations exceeding the SMCL level of 50 micrograms per liter (μg/L), whereas only 19 percent of samples from tributaries exceeded the SMCL for Mn.</p><p>Stream temperatures along the main stem of Laurel Hill Creek became higher moving downstream. During the summer months of June through August, the daily mean temperatures at the five sites exceeded the limit of 18.9 degrees Celsius (°C) for a cold-water fishery. The maximum instantaneous values for each site ranged from 27.2 to 32.8 °C.</p><p>Water-quality samples collected at groundwater sites (wells and springs) indicate that wells developed within the Mauch Chunk Formation had the best water quality, whereas wells developed within the Allegheny and Pottsville Formations yielded the poorest water quality. Waters from the Mauch Chunk Formation had the highest median pH (7.6) and alkalinity (80 mg/L calcium carbonate) values. The lowest pH and alkalinity median values were in waters from the Allegheny and Pottsville Formations. Groundwater samples collected from wells in the Allegheny and Pottsville Formations also had the highest concentrations of dissolved iron (Fe) and dissolved Mn. Seventy-eight percent of the groundwater samples collected from the Allegheny Formation exceeded the SMCL of 300 μg/L for Fe and 50 μg/L for Mn. Forty-three and 62 percent of the groundwater samples collected from the Pottsville Formation exceeded the SMCL for iron and Mn, respectively. The highest Fe and Mn concentrations for surface waters were measured for tributaries draining the Pottsville Formation. The highest median Fe concentration for tributaries was in samples from streams draining the Allegheny Formation.</p><p>During base-flow conditions, the streamflow per unit area along the main stem of Laurel Hill Creek was lowest in the upper parts of the basin [farthest upstream site 0.07 cubic foot per second per square mile (ft<sup>3</sup>/s/mi<sup>2</sup>)] and highest (two sites averaging about 0.20 (ft<sup>3</sup>/s/mi<sup>2</sup>) immediately downstream from Laurel Hill Lake in the center of the basin. Tributaries with the highest streamflow per unit area were those subbasins that drain the western ridge of the Laurel Hill Creek Basin. The mean streamflow per unit area for tributaries draining areas that extend into the western ridge and draining eastern or central sections was 0.24 and 0.05 ft<sup>3</sup>/s/mi<sup>2</sup>, respectively. In general, as the drainage area increased for tributary basins, the streamflow per unit area increased.</p><p>Criteria established by the Pennsylvania Department of Environmental Protection indicate that the safe yield of water withdrawals from the Laurel Hill Creek Basin is 1.43 million gallons per day (Mgal/d). Water-use data for 2009 indicate that net (water withdrawals subtracted by water discharges) water withdrawals from groundwater and surface-water sources in the basin were approximately 1.93 Mgal/d. Water withdrawals were concentrated in the upper part of the basin with approximately 80 percent of the withdrawals occurring in the upper 36 mi<sup>2</sup> of the basin. Three subbasins—Allen Creek, Kooser Run, and Shafer Run— in the upper part were affected the most by water withdrawals such that safe yields were exceeded by more than 1,000 percent in the first two and more than 500 percent in the other. In the subbasin of Shafer Run, intermittent streamflow characterizes sections that historically have been perennial.</p><p>The GSFLOW model of the Laurel Hill Creek Basin is a simple one-layer representation of the groundwater flow system. The GSFLOW model was primarily calibrated to reduce the error term associated with base-flow periods. The total amount of observed streamflow at the Laurel Hill Creek at Ursina, Pa. streamflow-gaging station and the simulated streamflow were within 0.1 percent over the entire modeled period; however, annual differences between simulated and observed streamflow showed a range of -27 to 24 percent from 1992 to 2007 with nine of the years having less than a 10-percent difference. The primary source of simulated streamflow in the GSFLOW model was the subsurface (interflow; 62 percent), followed by groundwater (25 percent) and surface runoff (13 percent). Most of the simulated subsurface flow that reached the stream was in the form of slow flow as opposed to preferential (fast) interflow.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165082","collaboration":"Prepared in cooperation with the Somerset County Conservation District","usgsCitation":"Galeone, D.G., Risser, D.W., Eicholtz, L.W., and Hoffman, S.A., 2017, Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007: U.S. Geological Survey Scientific Investigations Report 2016–5082, 85 p., https://doi.org/10.3133/sir20165082.","productDescription":"Report: vii, 85 p.; Appendices 1, 4","startPage":"1","endPage":"85","numberOfPages":"97","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-006526","costCenters":[{"id":532,"text":"Pennsylvania Water Science 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-78.86398315429686,\n              40.214538129296336\n            ],\n            [\n              -78.88320922851562,\n              40.25228042623786\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_pa@usgs.gov\" data-mce-href=\"mailto:dc_pa@usgs.gov\">Director</a>, <a href=\"http://pa.water.usgs.gov/\" data-mce-href=\"http://pa.water.usgs.gov/\">Pennsylvania Water Science Center</a><br> U.S. Geological Survey <br> 215 Limekiln Road <br> New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Methods</li><li>Characterization of Water Quality and Quantity&nbsp;</li><li>Simulation of Surface-Water and Groundwater Flow</li><li>GSFLOW Model Results and Water Quality</li><li>Summary and Conclusions&nbsp;</li><li>References Cited</li><li>Appendix 1. Concentrations of selected water-quality constituents and values of selected physical characteristics in surface-water samples collected during low-flow conditions in the Laurel Hill Creek Basin, southwestern, Pennsylvania, June and September 2007. (Appendix 1 available online as Excel file at <a href=\"https://doi.org/10.3133/sir20165082\" data-mce-href=\"https://doi.org/10.3133/sir20165082\">https://doi.org/10.3133/sir20165082</a>)</li><li>Appendix 2.&nbsp;Monthly maximum stream temperature criteria established by the Common&nbsp;wealth of Pennsylvania (2009), and monthly daily maximum, minimum, and mean &nbsp;stream temperatures for five sites along the main stem of Laurel Hill Creek Basin,&nbsp;south-western, Pennsylvania, 2007–10&nbsp;</li><li>Appendix 3.&nbsp;Daily mean streamflow values for station 03080000, Laurel Hill Creek at&nbsp;Ursina, Pennsylvania, July 17, 2007, through <br>July 8, 2010&nbsp;</li><li>Appendix 4.&nbsp;Concentrations of selected water-quality constituents and values of selected&nbsp;physical characteristics in groundwater samples collected in the Laurel Hill Creek&nbsp;Basin, southwestern, Pennsylvania, summer and fall 2007. (Appendix 4 available&nbsp;online as Excel file at <a href=\"https://doi.org/10.3133/sir20165082\" data-mce-href=\"https://doi.org/10.3133/sir20165082\"> https://doi.org/10.3133/sir20165082</a>)</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2017-07-10","noUsgsAuthors":false,"publicationDate":"2017-07-10","publicationStatus":"PW","scienceBaseUri":"5964922fe4b0d1f9f05acd07","contributors":{"authors":[{"text":"Galeone, Daniel G. 0000-0002-8007-9278 dgaleone@usgs.gov","orcid":"https://orcid.org/0000-0002-8007-9278","contributorId":2301,"corporation":false,"usgs":true,"family":"Galeone","given":"Daniel","email":"dgaleone@usgs.gov","middleInitial":"G.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Risser, Dennis W. 0000-0001-9597-5406 dwrisser@usgs.gov","orcid":"https://orcid.org/0000-0001-9597-5406","contributorId":898,"corporation":false,"usgs":true,"family":"Risser","given":"Dennis","email":"dwrisser@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eicholtz, Lee W. eicholtz@usgs.gov","contributorId":3928,"corporation":false,"usgs":true,"family":"Eicholtz","given":"Lee W.","email":"eicholtz@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoffman, Scott A. shoffman@usgs.gov","contributorId":2634,"corporation":false,"usgs":true,"family":"Hoffman","given":"Scott","email":"shoffman@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659755,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189304,"text":"70189304 - 2017 - Examples of storm impacts on barrier islands","interactions":[],"lastModifiedDate":"2020-08-20T19:05:19.217398","indexId":"70189304","displayToPublicDate":"2017-07-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Examples of storm impacts on barrier islands","docAbstract":"<p><span>This chapter focuses on the morphologic variability of barrier islands and on the differences in storm response. It describes different types of barrier island response to individual storms, as well as the integrated response of barrier islands to many storms. The chapter considers case study on the Chandeleur Island chain, where a decadal time series of island elevation measurements have documented a wide range of barrier island responses to storms and long-term processes that are representative of barrier island behaviour at many other locations. These islands are low elevation, extremely vulnerable to storms and exhibit a diversity of storm responses. Additionally, this location experiences a moderately high rate of relative sea-level rise, increasing its vulnerability to the combined impacts of storms and long-term erosional processes. Understanding how natural processes, including storm impacts and intervening recovery periods interact with man-made restoration processes is also broadly relevant to understand the natural and human response to future storms.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal storms: Processes and impacts","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Wiley","doi":"10.1002/9781118937099.ch4","usgsCitation":"Plant, N.G., Doran, K.S., and Stockdon, H.F., 2017, Examples of storm impacts on barrier islands, chap. 4 <i>of</i> Coastal storms: Processes and impacts, p. 65-79, https://doi.org/10.1002/9781118937099.ch4.","productDescription":"15 p.","startPage":"65","endPage":"79","ipdsId":"IP-068948","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-08","publicationStatus":"PW","scienceBaseUri":"59649231e4b0d1f9f05acd13","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":148059,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":704049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189305,"text":"70189305 - 2017 - Increased Arctic sea ice drift alters adult female polar bear movements and energetics","interactions":[],"lastModifiedDate":"2017-08-03T08:50:41","indexId":"70189305","displayToPublicDate":"2017-07-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Increased Arctic sea ice drift alters adult female polar bear movements and energetics","docAbstract":"<p><span>Recent reductions in thickness and extent have increased drift rates of Arctic sea ice. Increased ice drift could significantly affect the movements and the energy balance of polar bears (</span><i>Ursus maritimus</i><span>) which forage, nearly exclusively, on this substrate. We used radio-tracking and ice drift data to quantify the influence of increased drift on bear movements, and we modeled the consequences for energy demands of adult females in the Beaufort and Chukchi seas during two periods with different sea ice characteristics. Westward and northward drift of the sea ice used by polar bears in both regions increased between 1987–1998 and 1999–2013. To remain within their home ranges, polar bears responded to the higher westward ice drift with greater eastward movements, while their movements north in the spring and south in fall were frequently aided by ice motion. To compensate for more rapid westward ice drift in recent years, polar bears covered greater daily distances either by increasing their time spent active (7.6%–9.6%) or by increasing their travel speed (8.5%–8.9%). This increased their calculated annual energy expenditure by 1.8%–3.6% (depending on region and reproductive status), a cost that could be met by capturing an additional 1–3&nbsp;seals/year. Polar bears selected similar habitats in both periods, indicating that faster drift did not alter habitat preferences. Compounding reduced foraging opportunities that result from habitat loss; changes in ice drift, and associated activity increases, likely exacerbate the physiological stress experienced by polar bears in a warming Arctic.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13746","usgsCitation":"Durner, G.M., Douglas, D.C., Albeke, S., Whiteman, J.P., Amstrup, S.C., Richardson, E., Wilson, R.H., and Ben-David, M., 2017, Increased Arctic sea ice drift alters adult female polar bear movements and energetics: Global Change Biology, v. 23, no. 9, p. 3460-3473, https://doi.org/10.1111/gcb.13746.","productDescription":"14 p.","startPage":"3460","endPage":"3473","ipdsId":"IP-075197","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":343520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-06","publicationStatus":"PW","scienceBaseUri":"59649231e4b0d1f9f05acd0f","contributors":{"authors":[{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":704053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":704054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albeke, Shannon","contributorId":194426,"corporation":false,"usgs":false,"family":"Albeke","given":"Shannon","affiliations":[],"preferred":false,"id":704055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whiteman, John P.","contributorId":194427,"corporation":false,"usgs":false,"family":"Whiteman","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":704056,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":704057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richardson, Evan","contributorId":194428,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","affiliations":[],"preferred":false,"id":704058,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":704059,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ben-David, Merav","contributorId":190901,"corporation":false,"usgs":false,"family":"Ben-David","given":"Merav","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":704060,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70189301,"text":"70189301 - 2017 - Thermal regimes of Rocky Mountain lakes warm with climate change","interactions":[],"lastModifiedDate":"2017-07-10T12:55:24","indexId":"70189301","displayToPublicDate":"2017-07-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Thermal regimes of Rocky Mountain lakes warm with climate change","docAbstract":"<p><span>Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade</span><sup>-1</sup><span>increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade</span><sup>-1</sup><span>, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade</span><sup>-1</sup><span>. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0179498","usgsCitation":"Roberts, J., Fausch, K., Schmidt, T., and Walters, D.M., 2017, Thermal regimes of Rocky Mountain lakes warm with climate change: PLoS ONE, v. 12, no. 7, p. 1-17, https://doi.org/10.1371/journal.pone.0179498.","productDescription":"e0179498, 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-076491","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":469687,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0179498","text":"Publisher Index Page"},{"id":343510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Rocky Mountains","volume":"12","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"59649232e4b0d1f9f05acd16","contributors":{"authors":[{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fausch, Kurt D. 0000-0001-5825-7560","orcid":"https://orcid.org/0000-0001-5825-7560","contributorId":29370,"corporation":false,"usgs":false,"family":"Fausch","given":"Kurt D.","affiliations":[],"preferred":false,"id":704033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David M. 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":140992,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":704035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178619,"text":"sim3372 - 2017 - Geologic map of the northern White Hills, Mohave County, Arizona","interactions":[],"lastModifiedDate":"2017-07-10T14:22:03","indexId":"sim3372","displayToPublicDate":"2017-07-10T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3372","title":"Geologic map of the northern White Hills, Mohave County, Arizona","docAbstract":"<h1>Introduction</h1><p>The northern White Hills map area lies within the Kingman Uplift, a regional structural high in which Tertiary rocks lie directly on Proterozoic rocks as a result of Cretaceous orogenic uplift and erosional stripping of Paleozoic and Mesozoic strata. The Miocene Salt Spring Fault forms the major structural boundary in the map area. This low-angle normal fault separates a footwall (lower plate) of Proterozoic gneisses on the east and south from a hanging wall (upper plate) of faulted middle Miocene volcanic and sedimentary rocks and their Proterozoic substrate. The fault is part of the South Virgin–White Hills Detachment Fault, which records significant tectonic extension that decreases from north to south. Along most of its trace, the Salt Spring Fault dips gently westward, but it also has north-dipping segments along salients. A dissected, domelike landscape on the eroded footwall, which contains antiformal salients and synformal reentrants, extends through the map area from Salt Spring Bay southward to the Golden Rule Peak area. The “Lost Basin Range” represents an upthrown block of the footwall, raised on the steeper Lost Basin Range Fault.</p><p>The Salt Spring Fault, as well as the normal faults that segment its hanging wall, deform rocks that are about 16 to 10 Ma, and younger deposits overlie the faults. Rhyodacitic welded tuff about 15 Ma underlies a succession of geochemically intermediate to progressively more mafic lavas (including alkali basalt) that range from about 14.7 to 8 Ma, interfingered with sedimentary rocks and breccias in the western part of the map area. Upper Miocene strata record further filling of the extension-formed continental basins. Basins that are still present in the modern landscape reflect the youngest stages of extensional-basin formation, expressed as the downfaulted Detrital Valley and Hualapai Wash basins in the western and eastern parts of the map area, respectively, as well as the north-centrally located, northward-sagged Temple Basin. Pliocene fluvial and piedmont alluvial fan deposits record postextensional basin incision, refilling, and reincision driven by the inception and evolution of the westward-flowing Colorado River, centered north of the map area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3372","usgsCitation":"Howard, K.A., Priest, S.S., Lundstrom, S.C., and Block, D.L., 2017, Geologic map of the northern White Hills, Mohave County, Arizona: U.S. Geological Survey Scientific Investigations Map 3372, pamphlet 31 p., scale 1:50,000, https://doi.org/10.3133/sim3372.","productDescription":"Pamphlet: iii, 31 p.; Sheet: 30.34 x 31.40 inches; Database; Metadata","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066011","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":343328,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_database.zip","text":"Database","size":"11.5 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3372 Database"},{"id":343318,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_pamphlet.pdf","text":"Pamphlet","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3372 Pamphlet"},{"id":343329,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_metadata.zip","text":"Metadata","size":"50 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3372 Pamphlet"},{"id":343240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3372/coverthb2.jpg"},{"id":343241,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3372/sim3372_map.pdf","text":"Map","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3372 Sheet"}],"country":"United States","state":"Arizona","county":"Mohave County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.5,\n              35.75\n            ],\n            [\n              -114,\n              35.75\n            ],\n            [\n              -114,\n              36\n            ],\n            [\n              -114.5,\n              36\n            ],\n            [\n              -114.5,\n              35.75\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://geomaps.wr.usgs.gov/gmeg/\" data-mce-href=\"https://geomaps.wr.usgs.gov/gmeg/\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://usgs.gov/\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road<br>Menlo Park, CA 94025-3591</p>","tableOfContents":"<ul><li>Introduction&nbsp;<br></li><li>Methods&nbsp;<br></li><li>Geologic Summary<br></li><li>Structure and Mineralization<br></li><li>Landscape Evolution<br></li><li>Interpreted Geologic History<br></li><li>Description of Map Units&nbsp;<br></li><li>Acknowledgments&nbsp;<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-07-10","noUsgsAuthors":false,"publicationDate":"2017-07-10","publicationStatus":"PW","scienceBaseUri":"59649233e4b0d1f9f05acd27","contributors":{"authors":[{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":654583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Priest, Susan S. spriest@usgs.gov","contributorId":1116,"corporation":false,"usgs":true,"family":"Priest","given":"Susan S.","email":"spriest@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":654584,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstrom, Scott C. 0000-0003-4149-2219 sclundst@usgs.gov","orcid":"https://orcid.org/0000-0003-4149-2219","contributorId":2446,"corporation":false,"usgs":true,"family":"Lundstrom","given":"Scott","email":"sclundst@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":654585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Block, Debra L. 0000-0001-7348-3064 dblock@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-3064","contributorId":3587,"corporation":false,"usgs":true,"family":"Block","given":"Debra","email":"dblock@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":654586,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232549,"text":"70232549 - 2017 - Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon","interactions":[],"lastModifiedDate":"2022-07-07T12:12:01.261898","indexId":"70232549","displayToPublicDate":"2017-07-07T07:08:45","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"chapter":"8","title":"Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon","docAbstract":"In 1992, Snake River basin fall Chinook salmon (Oncorhynchus tshawytscha) were listed for protection under the U.S. Endangered Species Act (NMFS 1992) and the population remained below 1000 individuals until 2000. Since then, returns from natural production has rebounded to over 20,000 spawners owing to a host of factors including reduced harvest (Peters et al. 2001), stable minimum spawning flows (Groves and Chandler 1999), summer flow augmentation (Connor et al. 2003), predator control (Beamesderfer et al. 1996), hatchery supplementation (Rosenberger et al. 2017), improved juvenile passage structures (Adams et al.\n2014), summer spill operations (Perry et al. 2006; Adams et al. 2008), and periods of favorable ocean conditions and food availability (Logerwell et al. 2003; Peterson et al. 2014). Given this change in abundance coincident with numerous management actions and fluctuation in environmental drivers, quantifying which factors contributed to the observed rebound in natural  \nproduction can provide critical insights into future management actions for this at-risk population.\n\nMultistage life cycle models provide a powerful analytical framework for understating how each life stage of a population contributes to population growth rate (Moussalli and Hilborn 1986; Greene and Beechie 2004). Multistage models may also be used as an analytical framework to explicitly estimate demographic parameters of a population model. This approach has an advantage over single-stage stock-recruitment models by allowing population growth rates to be partitioned among life stages rather than aggregated over an entire life cycle. Such partitioning allows for estimating 1) stage-specific density dependence, and 2) stage-specific effects of environmental factors or management actions. For example, Zabel et al. (2006) estimated parameters of a multistage model used in the context of a population viability analysis for spring/summer Chinook salmon in the Snake River, but such an approach has yet to be applied to fall Chinook salmon in the Snake River basin.\n\nTypically, data informing estimates of abundance at particular “check points” in the life cycle determines the complexity of the multistage model that can be fit to the data. For fall Chinook salmon, we are developing a two-stage model that encompasses: 1) upstream passage of spawners at Lower Granite Dam (LGR) to the subsequent downstream passage of their progeny at the dam, and 2) downstream passage of juveniles at LGR to their subsequent return from the ocean and passage at the Dam 2‒6 years later. This approach partitions the life cycle of fall Chinook salmon both spatially and temporally, which allows us to fit and compare alternative models with covariates specific to each stage. Our previous report to the ISAB (Zabel et al.\n2013) detailed methods for estimating abundance of naturally produced adults and juveniles passing Lower Granite Dam, which provides the requisite data for fitting a two-stage model.\n \nThe intent of this report is to describe the structure of the two-stage life cycle model, present preliminary results from fitting the model to data, and outline future directions and developments.\n\nAs is clear from the diversity of models presented in this report, “life cycle models” range from very simple theoretically based population models (e.g., the Beverton-Holt stock- recruitment model) to very complex spatially explicit simulation models linked to hydrosystem hydrodynamic models (e.g., the COMPASS model for a single transition in a life cycle model, Zabel et al. 2008). We chose to develop a model of intermediate complexity that casts the two- stage life cycle model in a state-space framework (Newman et al. 2014). We chose to use a state-space framework implemented in a Bayesian framework because:\n\n• It provides both a statistical estimation framework for retrospective statistical analysis and a stochastic simulation framework for prospective analysis to evaluate alternative management actions.\n• Abundance estimates are uncertain. A state-space framework accounts for observation uncertainty in the abundance estimates and other data (e.g., age structure) while simultaneously estimating process uncertainty.\n• It allows for missing data. By drawing missing data from an appropriate probability model, uncertainty owing to missing data can be propagated without having to omit data or assume fixed values for missing data.\n\nThus, a two-stage state-space life cycle model for fall Chinook salmon strikes an appropriate balance between model complexity, tractability, and applicability given the goals of performing both retrospective and prospective analysis to guide future management of this population.","language":"English","publisher":"Independent Scientific Advisory Board for the Northwest Power and Conservation Council","collaboration":"Bonneville Power Administration","usgsCitation":"Perry, R., Plumb, J., Tiffan, K., Connor, W.P., Cooney, T.D., and Young, W., 2017, Building a state-space life cycle model for naturally produced Snake River fall Chinook salmon, 32 p.","productDescription":"32 p.","ipdsId":"IP-087390","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":403131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403116,"type":{"id":15,"text":"Index Page"},"url":"https://www.nwcouncil.org/reports/review-of-noaa-fisheries-interior-columbia-basin-life-cycle-modeling-draft-report/"}],"country":"United States","state":"Idaho, Oregon, Washington, Wyoming","otherGeospatial":"Snake River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.42138671875,\n              41.623655390686395\n            ],\n            [\n              -109.3359375,\n              41.623655390686395\n            ],\n            [\n              -109.3359375,\n              47.14489748555398\n            ],\n            [\n              -119.42138671875,\n              47.14489748555398\n            ],\n            [\n              -119.42138671875,\n              41.623655390686395\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223219,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tiffan, Kenneth 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":217812,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":845937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Connor, William P.","contributorId":107589,"corporation":false,"usgs":false,"family":"Connor","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID  83544","active":true,"usgs":false}],"preferred":false,"id":845938,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooney, Thomas D.","contributorId":138838,"corporation":false,"usgs":false,"family":"Cooney","given":"Thomas","email":"","middleInitial":"D.","affiliations":[{"id":12540,"text":"National Marine Fisheries Service, Northwest Fisheries Science Center, Conservation Biology Division, 525 Northeast Oregon Street, Portland, OR  97232","active":true,"usgs":false}],"preferred":false,"id":845939,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, William","contributorId":138842,"corporation":false,"usgs":false,"family":"Young","given":"William","email":"","affiliations":[{"id":12542,"text":"Washington Dept. of Fish and Wildlife, Snake River Laboratory, 401 South Cottonwood St., Dayton WA 99328","active":true,"usgs":false}],"preferred":false,"id":845940,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189277,"text":"70189277 - 2017 - Mapping burned areas using dense time-series of Landsat data","interactions":[],"lastModifiedDate":"2022-04-22T15:43:05.359179","indexId":"70189277","displayToPublicDate":"2017-07-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping burned areas using dense time-series of Landsat data","docAbstract":"<p><span>Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the BAECV products mapped 32% and 88% more burned area, respectively. However, the BAECV products found less burned area than the GFED in regions with frequent agricultural fires. Compared to the MTBS data, the BAECV products identified 31% more burned area in the West, 312% more in the Great Plains, and 233% more in the East. Most pixels in the MTBS data were detected by the BAECV, regardless of burn severity. The BAECV products document patterns of fire similar to those in the GFED but also showed patterns of fire that are not well characterized by the existing MTBS data. We anticipate the BAECV products will be useful to studies that seek to understand past patterns of fire occurrence, the drivers that created them, and the impacts fires have on natural and human systems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.06.027","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Beal, Y.G., Takacs, J., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M., Picotte, J.J., Howard, S.M., Stitt, S., and Dwyer, J.L., 2017, Mapping burned areas using dense time-series of Landsat data: Remote Sensing of Environment, v. 198, p. 504-522, https://doi.org/10.1016/j.rse.2017.06.027.","productDescription":"19 p.","startPage":"504","endPage":"522","ipdsId":"IP-077532","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469690,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.06.027","text":"Publisher Index Page"},{"id":438275,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73B5X76","text":"USGS data release","linkHelpText":"Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015)"},{"id":343478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"continental United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n            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          -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                45.52341\n              ],\n              [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"198","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59609db5e4b0d1f9f0594c30","contributors":{"authors":[{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":703869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":703870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beal, Yen-Ju G. 0000-0002-5538-5687 ygbeal@usgs.gov","orcid":"https://orcid.org/0000-0002-5538-5687","contributorId":5328,"corporation":false,"usgs":true,"family":"Beal","given":"Yen-Ju","email":"ygbeal@usgs.gov","middleInitial":"G.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":703871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takacs, Joshua 0000-0003-1509-5498 jdtakacs@usgs.gov","orcid":"https://orcid.org/0000-0003-1509-5498","contributorId":194380,"corporation":false,"usgs":true,"family":"Takacs","given":"Joshua","email":"jdtakacs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":703872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falgout, Jeff T. 0000-0002-7108-477X jfalgout@usgs.gov","orcid":"https://orcid.org/0000-0002-7108-477X","contributorId":4957,"corporation":false,"usgs":true,"family":"Falgout","given":"Jeff","email":"jfalgout@usgs.gov","middleInitial":"T.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":703874,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Brad 0000-0002-2827-6880 bradwilliams@usgs.gov","orcid":"https://orcid.org/0000-0002-2827-6880","contributorId":194381,"corporation":false,"usgs":true,"family":"Williams","given":"Brad","email":"bradwilliams@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":703875,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brunner, Nicole M. 0000-0001-9657-2860 nbrunner@usgs.gov","orcid":"https://orcid.org/0000-0001-9657-2860","contributorId":5323,"corporation":false,"usgs":true,"family":"Brunner","given":"Nicole","email":"nbrunner@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":703876,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Caldwell, Megan K. 0000-0003-0759-2793","orcid":"https://orcid.org/0000-0003-0759-2793","contributorId":194382,"corporation":false,"usgs":false,"family":"Caldwell","given":"Megan K.","affiliations":[],"preferred":false,"id":703877,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","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":703878,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":703879,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stitt, Susan 0000-0002-0663-2696","orcid":"https://orcid.org/0000-0002-0663-2696","contributorId":194383,"corporation":false,"usgs":false,"family":"Stitt","given":"Susan","affiliations":[],"preferred":false,"id":703880,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","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":703881,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70200982,"text":"70200982 - 2017 - The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","interactions":[],"lastModifiedDate":"2018-11-20T10:46:43","indexId":"70200982","displayToPublicDate":"2017-07-06T10:46:25","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA","docAbstract":"<p>A synthesis of field, biostratigraphic, detrital zircon geochronologic, and remote sensing data across north-central Nevada, United States, defines a thick, regionally extensive sheet of Middle–Upper Ordovician Valmy Formation quartzite that structurally overlies deformed early Paleozoic units of the Roberts Mountains allochthon. Late Paleozoic regional unconformities that record tectonic disruptions have been recognized in the foreland of central and eastern Nevada and locally within the Roberts Mountains allochthon; these identify multiple, regional tectonic events between the Devonian–Mississippian initiation of the Antler orogeny and the Permian–Triassic Sonoma orogeny. However, few studies have documented the regional kinematic history of the Robert Mountains allochthon sensu stricto. In the Independence Mountains of northern Nevada, emplacement of the Roberts Mountains allochthon is restricted to the Mississippian. In the Tuscarora Mountains, the range west and southwest of the Independence Mountains, several deformation events have been identified, and emplacement of the thrust sheet containing the Valmy Formation is restricted to the Late Pennsylvanian–Early Permian. These structural and temporal relations, reflected in the Antler foreland basin adjacent to the Roberts Mountains allochthon and overlap sequences, suggest that the Roberts Mountains allochthon is a composite stratigraphic terrane assembled along the Cordilleran margin during two or more late Paleozoic contractional events.</p><p>Valmy Formation deposits likely represent the development of coalescing submarine fans below or within bypass channels in a deep slope or rise environment. Petrographic characteristics, biostratigraphy, and detrital zircon U-Pb age populations of the Valmy Formation link it to coeval slope and rise turbidites of the Vinini Formation and shelfal Eureka Quartzite; Valmy Formation detrital zircon age populations are dissimilar to the rift-to-drift facies of the Neoproterozoic–Cambrian Prospect Mountain Quartzite. Throughout north-central Nevada, the Valmy Formation is in fault contact with units of the Roberts Mountains allochthon, including the Devonian–Mississippian Slaven Chert, Silurian–Devonian Elder Sandstone, and Cambrian(?)–Ordovician Vinini Formation, which were deformed prior to, or during, emplacement of the thrust sheet containing Valmy Formation quartzite. Our mapping and data synthesis, guided by regional quartz maps based on remote sensing (Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER]) data, delineate similar structural relationships discontinuously for &gt;200 km along strike of the Roberts Mountains allochthon.</p><p>Exploration for concealed gold deposits within reach of drilling requires knowledge of the relative thicknesses of the Roberts Mountains allochthon and the Valmy Formation. Overall thicknesses of deformed Roberts Mountains allochthon units between the Valmy Formation and underlying carbonate rocks, which host large, world-class Carlin-type gold deposits, vary by hundreds of meters, but are generally less than 700 m in three of the areas studied here. Recognition of windows through and klippen of the Roberts Mountains allochthon is essential for identification of areas where deposits may be at or near the surface. Correspondingly, most ongoing exploration for Carlin-type gold deposits subjacent to the Roberts Mountains allochthon targets concealed deposits. The model proposed in this study is applicable to determining depth to rocks prospective for undiscovered deposits.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31491.1","usgsCitation":"Holm-Denoma, C.S., Hofstra, A.H., Rockwell, B., and Noble, P.J., 2017, The Valmy thrust sheet: A regional structure formed during the protracted assembly of the Roberts Mountains allochthon, Nevada, USA: GSA Bulletin, v. 129, no. 11-12, p. 1521-1536, https://doi.org/10.1130/B31491.1.","productDescription":"16 p.","startPage":"1521","endPage":"1536","ipdsId":"IP-077542","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":359600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117,\n              40\n            ],\n            [\n              -115.5,\n              40\n            ],\n            [\n              -115.5,\n              42\n            ],\n            [\n              -117,\n              42\n            ],\n            [\n              -117,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"129","issue":"11-12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"5bf52b6ae4b045bfcae28010","contributors":{"authors":[{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":203924,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Paula J.","contributorId":40455,"corporation":false,"usgs":true,"family":"Noble","given":"Paula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":751548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189242,"text":"70189242 - 2017 - Middle and Late Pleistocene glaciations in the southwestern Pamir and their effects on topography","interactions":[],"lastModifiedDate":"2017-07-06T12:36:03","indexId":"70189242","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Middle and Late Pleistocene glaciations in the southwestern Pamir and their effects on topography","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\"><p id=\"sp0110\">Glacial chronologies provide insight into the evolution of paleo-landscapes, paleoclimate, topography, and the erosion processes that shape mountain ranges. In the Pamir of Central Asia, glacial morphologies and deposits indicate extensive past glaciations, whose timing and extent remain poorly constrained. Geomorphic data and 15 new<span>&nbsp;</span><sup>10</sup>Be exposure ages from moraine boulders and roches moutonnées in the southwestern Pamir document multiple Pleistocene glacial stages. The oldest exposure ages,<span>&nbsp;</span><span id=\"mmlsi1\" class=\"mathmlsrc\"><a class=\"mathImg\" title=\"View the MathML source\" data-mathurl=\"/science?_ob=MathURL&amp;_method=retrieve&amp;_eid=1-s2.0-S0012821X17301425&amp;_mathId=si1.gif&amp;_user=111111111&amp;_pii=S0012821X17301425&amp;_rdoc=1&amp;_issn=0012821X&amp;md5=6b7166d2f5ee5f933cb0268e884c5291\"><img class=\"imgLazyJSB inlineImage\" title=\"View the MathML source\" src=\"http://ars.els-cdn.com/content/image/1-s2.0-S0012821X17301425-si1.gif\" alt=\"View the MathML source\" width=\"74\" height=\"10\" data-inlimgeid=\"1-s2.0-S0012821X17301425-si1.gif\" data-loaded=\"true\" data-mce-src=\"http://ars.els-cdn.com/content/image/1-s2.0-S0012821X17301425-si1.gif\"></a></span>, underestimate the age of the earliest preserved glacial advance and imply that the modern relief of the southwestern Pamir (peaks at ∼5000–6000 m a.s.l.; valleys at ∼2000–3000 m a.s.l.) already existed in the late Middle Pleistocene. Younger exposure ages (∼40–80 ka, ∼30 ka) complement the existing Central Asian glacial chronology and reflect successively less extensive Late Pleistocene glaciations. The topography of the Pamir and the glacial chronologies suggest that, in the Middle Pleistocene, an ice cap or ice field occupied the eastern Pamir high-altitude plateau, whereas westward flowing valley glaciers incised the southwestern Pamir. Since the Late Pleistocene deglaciation, the rivers of the southwestern Pamir adjusted to the glacially shaped landscape. Localized rapid fluvial incision and drainage network reorganization reflect the transient nature of the deglaciated landscape.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.03.012","usgsCitation":"Stubner, K., Grin, E., Hidy, A.J., Schaller, M., Gold, R.D., Ratschbacher, L., and Ehlers, T., 2017, Middle and Late Pleistocene glaciations in the southwestern Pamir and their effects on topography: Earth and Planetary Science Letters, v. 466, p. 181-194, https://doi.org/10.1016/j.epsl.2017.03.012.","productDescription":"14 p.","startPage":"181","endPage":"194","ipdsId":"IP-083967","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469692,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1351141","text":"Publisher Index Page"},{"id":343405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"466","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c35e4b0d1f9f057e2ea","contributors":{"authors":[{"text":"Stubner, Konstanze","contributorId":194301,"corporation":false,"usgs":false,"family":"Stubner","given":"Konstanze","email":"","affiliations":[],"preferred":false,"id":703676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grin, Elena","contributorId":194302,"corporation":false,"usgs":false,"family":"Grin","given":"Elena","email":"","affiliations":[],"preferred":false,"id":703677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hidy, Alan J.","contributorId":194303,"corporation":false,"usgs":false,"family":"Hidy","given":"Alan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaller, Mirjam","contributorId":194304,"corporation":false,"usgs":false,"family":"Schaller","given":"Mirjam","email":"","affiliations":[],"preferred":false,"id":703679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":703680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ratschbacher, Lothar","contributorId":194305,"corporation":false,"usgs":false,"family":"Ratschbacher","given":"Lothar","email":"","affiliations":[],"preferred":false,"id":703681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ehlers, Todd","contributorId":194306,"corporation":false,"usgs":false,"family":"Ehlers","given":"Todd","affiliations":[],"preferred":false,"id":703682,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189248,"text":"70189248 - 2017 - Trimming a hazard logic tree with a new model-order-reduction technique","interactions":[],"lastModifiedDate":"2017-09-18T15:36:41","indexId":"70189248","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","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":"Trimming a hazard logic tree with a new model-order-reduction technique","docAbstract":"<p><span>The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.</span></p>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/092616EQS158M","usgsCitation":"Porter, K., Field, E., and Milner, K.R., 2017, Trimming a hazard logic tree with a new model-order-reduction technique: Earthquake Spectra, v. 33, no. 3, p. 857-874, https://doi.org/10.1193/092616EQS158M.","productDescription":"18 p.","startPage":"857","endPage":"874","ipdsId":"IP-086311","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":343412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-01","publicationStatus":"PW","scienceBaseUri":"595f4c34e4b0d1f9f057e2e4","contributors":{"authors":[{"text":"Porter, Keith","contributorId":191074,"corporation":false,"usgs":false,"family":"Porter","given":"Keith","affiliations":[],"preferred":false,"id":703718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, Edward H. 0000-0001-8172-7882 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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":703719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189018,"text":"sir20175022C - 2017 - Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","interactions":[{"subject":{"id":70189018,"text":"sir20175022C - 2017 - Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","indexId":"sir20175022C","publicationYear":"2017","noYear":false,"chapter":"C","title":"Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington"},"predicate":"IS_PART_OF","object":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"id":1}],"isPartOf":{"id":70188710,"text":"sir20175022 - 2017 - Field-trip guides to selected volcanoes and volcanic landscapes of the western United States","indexId":"sir20175022","publicationYear":"2017","noYear":false,"title":"Field-trip guides to selected volcanoes and volcanic landscapes of the western United States"},"lastModifiedDate":"2017-07-27T12:28:33","indexId":"sir20175022C","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","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":"2017-5022","chapter":"C","title":"Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington","docAbstract":"<p>Pyroclastic density currents (PDCs) are one of the most dangerous phenomena associated with explosive volcanism. To help constrain damage potential, a combination of field studies, laboratory experiments, and numerical modeling are used to establish conditions that influence PDC dynamics and depositional processes, including runout distance. The objective of this field trip is to explore field relations that may constrain PDCs at the time of emplacement.</p><p>The PDC deposits from the May 18, 1980, eruption of Mount St. Helens are well exposed along the steep flanks (10–30° slopes) and across the pumice plain (5–12° slopes) as far as 8 km north of the volcano. The pumice plain deposits represent deposition from a series of concentrated PDCs and are primarily thick (3–12 m), massive, and poorly sorted. In contrast, the steep east-flank deposits are stratified to cross-stratified, suggesting deposition from PDCs where turbulence strongly influenced transport and depositional processes.</p><p>The PDCs that descended the west flank were largely nondepositional; they maintained a higher flow energy and carrying capacity than PDCs funneled through the main breach, as evidenced by the higher concentration of large blocks in their deposits. The PDC from the west flank collided with PDCs funneled through the breach at various points along the pumice plain. Evidence for flow collision will be explored and debated throughout the field trip.<br>Evidence for substrate erosion and entrainment is found (1) along the steep eastern flank of the volcano, which has a higher degree of rough, irregular topography relative to the west flanks where PDCs were likely nonerosive, (2) where PDCs encountered debris-avalanche hummocks across the pumice plain, and (3) where PDCs eroded and entrained material deposited by PDCs produced during earlier phases of the eruption. Two features interpreted as large-scale (tens of meters wide) levees and a large (~200 m wide) channel scour-and-fill feature provide the first evidence of self-channelization within PDCs sustained for minutes to tens of minutes (total volume of deposits is ~0.12 km<sup>3</sup>; area covered is ~15.5 km<sup>2</sup>; Rowley and others, 1981).</p><p>Our ability to interpret the deposits of PDCs is critical for understanding transport and depositional processes that control PDC dynamics. The results of extensive work on the May 18, 1980, PDC deposits show that slope and irregular topography strongly influence PDC flow path, dynamics, criticality (for example, supercritical versus subcritical), carrying capacity, and erosive capacity. However, the influence of these conditions on ultimate flow runout and damage potential warrants further exploration through the combination of field, experimental, and numerical approaches.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022C","usgsCitation":"Brand, B.D., Pollock, Nicholas, Sarocchi, Damiano, Dufek, Josef, and Clynne, M.A., 2017, Field-trip guide for exploring pyroclastic density current deposits from the May 18, 1980, eruption of Mount St. Helens, Washington: U.S. Geological Survey Scientific Investigations Report 2017–5022–C, 34 p., https://doi.org/10.3133/sir20175022C.","productDescription":"ix, 34 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-075876","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":343226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/c/coverthb.jpg"},{"id":343227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/c/sir20175022c.pdf","text":"Report","size":"22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5022-C"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.21328735351562,\n              46.1408312087306\n            ],\n            [\n              -121.9647216796875,\n              46.1408312087306\n            ],\n            [\n              -121.9647216796875,\n              46.33175800051563\n            ],\n            [\n              -122.21328735351562,\n              46.33175800051563\n            ],\n            [\n              -122.21328735351562,\n              46.1408312087306\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://volcanoes.usgs.gov/\" data-mce-href=\"http://volcanoes.usgs.gov/\">Volcano Science Center</a>&nbsp;- Menlo Park<br><a href=\"https://usgs.gov/\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>345 Middlefield Road, MS 910<br>Menlo Park, CA 94025</p>","tableOfContents":"<ul><li>Preface&nbsp;<br></li><li>Contributing Authors<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Physical-Intensity-Level Disclaimer<br></li><li>Brief Eruptive History of Mount StHelens<br></li><li>Pre-Pumice Plain Field Trip Stop<br></li><li>Events of May 18, 1980<br></li><li>Start of Road and Trail Log with Stop Descriptions<br></li><li>Discussion Points<br></li><li>Itinerary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2017-07-05","noUsgsAuthors":false,"publicationDate":"2017-07-05","publicationStatus":"PW","scienceBaseUri":"595dfaaae4b0d1f9f056a720","contributors":{"authors":[{"text":"Brand, Brittany D. brittanybrand@boisestate.edu","contributorId":193853,"corporation":false,"usgs":false,"family":"Brand","given":"Brittany","email":"brittanybrand@boisestate.edu","middleInitial":"D.","affiliations":[],"preferred":false,"id":702855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Nicholas","contributorId":193854,"corporation":false,"usgs":false,"family":"Pollock","given":"Nicholas","email":"","affiliations":[{"id":33038,"text":"Department of Geosciences, Boise State University","active":true,"usgs":false}],"preferred":false,"id":702856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sarocchi, Damiano","contributorId":194000,"corporation":false,"usgs":false,"family":"Sarocchi","given":"Damiano","email":"","affiliations":[],"preferred":false,"id":702857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufek, Josef","contributorId":194001,"corporation":false,"usgs":false,"family":"Dufek","given":"Josef","email":"","affiliations":[],"preferred":false,"id":702858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":702859,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189174,"text":"70189174 - 2017 - Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation","interactions":[],"lastModifiedDate":"2017-08-03T08:48:23","indexId":"70189174","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation","docAbstract":"<p><span>Gridded hourly precipitation observations over the conterminous U.S., from 1948 to 2002, are analyzed to determine climatological characteristics of storm precipitation totals. Despite generally lower hourly intensities, precipitation totals along the U.S. West Coast (USWC) are comparable to those in southeast U.S. (SEUS). Storm durations, more so than hourly intensities, strongly modulate precipitation-total variability over the USWC, where the correlation coefficients between storm durations and storm totals range from 0.7 to 0.9. Atmospheric rivers (ARs) contribute 30–50% of annual precipitation on the USWC and make such large contributions to extreme storms that 60–100% of the most extreme storms, i.e., storms with precipitation-total return intervals longer than 2&nbsp;years, are associated with ARs. These extreme storm totals are more strongly tied to storm durations than to storm hourly or average intensities, emphasizing the importance of AR persistence to extreme storms on the USWC.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL074193","usgsCitation":"Lamjiri, M.A., Dettinger, M.D., Ralph, F.M., and Guan, B., 2017, Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation: Geophysical Research Letters, v. 44, no. 13, p. 7020-7028, https://doi.org/10.1002/2017GL074193.","productDescription":"9 p.","startPage":"7020","endPage":"7028","ipdsId":"IP-086997","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":469695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl074193","text":"Publisher Index 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,{"id":70189164,"text":"70189164 - 2017 - A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast","interactions":[],"lastModifiedDate":"2020-09-02T13:12:10.813183","indexId":"70189164","displayToPublicDate":"2017-07-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast","docAbstract":"<p><span>We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of&nbsp;</span><i>M</i><span>≥2.5 events, conditioned on any prior<span>&nbsp;</span></span><i>M</i><span>≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as will any subsequent version or competing model, potential usefulness needs to be considered in the context of actual applications.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160173","usgsCitation":"Field, E., Milner, K.R., Hardebeck, J.L., Page, M.T., van der Elst, N., Jordan, T.H., Michael, A.J., Shaw, B., and Werner, M.J., 2017, A spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3‐ETAS): Toward an operational earthquake forecast: Bulletin of the Seismological Society of America, v. 107, no. 3, p. 1049-1081, https://doi.org/10.1785/0120160173.","productDescription":"33 p.","startPage":"1049","endPage":"1081","ipdsId":"IP-079305","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469698,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/89ca02cb-997c-46d2-ab3d-34a7f120d0cd","text":"External Repository"},{"id":343279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":703292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":703293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van der Elst, Nicholas nvanderelst@usgs.gov","contributorId":146631,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":703294,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordan, Thomas H.","contributorId":75055,"corporation":false,"usgs":true,"family":"Jordan","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703295,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":703296,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaw, Bruce E.","contributorId":93810,"corporation":false,"usgs":true,"family":"Shaw","given":"Bruce E.","affiliations":[],"preferred":false,"id":703297,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Werner, Maximillan J.","contributorId":194147,"corporation":false,"usgs":false,"family":"Werner","given":"Maximillan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703298,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70193524,"text":"70193524 - 2017 - Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata)","interactions":[],"lastModifiedDate":"2017-11-02T14:10:10","indexId":"70193524","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diel periodicity and chronology of upstream migration in yellow-phase American eels (<i>Anguilla rostrata</i>)","title":"Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata)","docAbstract":"<p><span>Yellow-phase American eel (</span><i class=\"EmphasisTypeItalic \">Anguilla rostrata</i><span>) upstream migration is temporally punctuated, yet migration chronology within diel time periods is not well-understood. This study examined diel periodicity, chronology, and total length (TL) of six multi-day, high-count (285–1,868 eels) passage events of upstream migrant yellow-phase American eels at the Millville Dam eel ladder, lower Shenandoah River, West Virginia during 2011–2014. We categorized passage by diel periods (vespertine, nocturnal, matutinal, diurnal) and season (spring, summer, late summer/early fall, fall). We depicted passage counts as time-series histograms and used time-series spectral analysis (Fast Fourier Transformation) to identify cyclical patterns and diel periodicity of upstream migration. We created histograms to examine movement patterns within diel periods for each passage event and fit normal mixture models (2–9 mixtures) to describe multiple peaks of passage counts. Periodicity of movements for each passage event followed a 24-h activity cycle with mostly nocturnal movement. Multimodal models were supported by the data; most modes represented nocturnal movements, but modes at or near the transition between twilight and night were also common. We used mixed-model methodology to examine relationships among TL, diel period, and season. An additive-effects model of diel period + season was the best approximating model. A decreasing trend of mean TL occurred across diel movement periods, with the highest mean TL occurring during fall relative to similar mean values of TL for spring, summer, and late summer/early fall. This study increased our understanding of yellow-phase American eels by demonstrating the non-random nature of their upstream migration.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0614-1","usgsCitation":"Aldinger, J.L., and Welsh, S.A., 2017, Diel periodicity and chronology of upstream migration in yellow-phase American eels (Anguilla rostrata): Environmental Biology of Fishes, v. 100, no. 7, p. 829-838, https://doi.org/10.1007/s10641-017-0614-1.","productDescription":"10 p.","startPage":"829","endPage":"838","ipdsId":"IP-079381","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Millville Dam","volume":"100","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-09","publicationStatus":"PW","scienceBaseUri":"59fc2ea4e4b0531197b27f7f","contributors":{"authors":[{"text":"Aldinger, Joni L.","contributorId":171886,"corporation":false,"usgs":false,"family":"Aldinger","given":"Joni","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":719832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":719265,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237288,"text":"70237288 - 2017 - Geomorphic processes responsible for decadal-scale arroyo changes, Rio Puerco, New Mexico","interactions":[],"lastModifiedDate":"2022-10-06T13:31:32.552288","indexId":"70237288","displayToPublicDate":"2017-07-01T08:25:17","publicationYear":"2017","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":"Geomorphic processes responsible for decadal-scale arroyo changes, Rio Puerco, New Mexico","docAbstract":"<p>The channel and arroyo of the Rio Puerco have continued to evolve since incision in the late 1800s. Resurveys of channel cross sections and aerial imagery over time indicate that between the 1970s and 1990s, the upstream reaches (type 1 morphology) of the Rio Puerco have continued to undergo construction of an incipient inner floodplain by means of vertical aggradation while simultaneously developing a narrower, but relatively shallow, channel. Downstream reaches (type 2 morphology) also show progressive channel width decrease, construction of a well-vegetated and mature inner floodplain, and deposition in the active channel, leading to an increase in the streambed elevation.</p><p>Trends in rainfall and streamflow cannot explain the observed decadal patterns in sediment deposition in the Rio Puerco. Analysis of streamflow shows that a large percentage of runoff originating in the upper watershed is entirely infiltrated into the streambed and floodplains between upstream and downstream reaches. With suspended-sediment concentrations reaching 500,000 mg/L, the loss of streamflow results in sediment deposition.</p><p>Peak streamflows are decreasing in the Rio Puerco near its mouth at Bernardo, New Mexico. Hydrographs were modeled using a 71-yr-old monumented channel cross section in the lower reaches (Highway 6) surveyed in 1936 and resurveyed in 2007. Model outputs show that attenuation of peak flow can occur from progressive changes in channel morphology and vegetation. Decreasing peak flows, transmission losses, and development of an inner floodplain within the widened arroyo all interact to increase sediment deposition over time. Consequently, increased sediment deposition has resulted in decreased sediment loads and sediment concentrations in downstream reaches. Resurveys of channels in downstream reaches confirm that the channel bed is aggrading. At the oldest surveyed cross section (Highway 6 surveyed in 1936 and resurveyed in 2007), the channel bed has aggraded 6 m, and at its long-term rate of filling, deposition of sediment could fill the entire arroyo cross section in 150 yr.</p><p>The Rio Puerco has incised and aggraded several times in the late Quaternary. Results of this study show that the twentieth-century aggradation of the Rio Puerco is driven by intrinsic processes that involve a positive feedback relation among channel morphology, vegetation, climate, streamflow, infiltration, and sediment loads.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31622.1","usgsCitation":"Gellis, A.C., Elliott, J., and Pavich, M., 2017, Geomorphic processes responsible for decadal-scale arroyo changes, Rio Puerco, New Mexico: Geological Society of America Bulletin, v. 129, no. 11-12, p. 1660-1680, https://doi.org/10.1130/B31622.1.","productDescription":"21 p.","startPage":"1660","endPage":"1680","ipdsId":"IP-080179","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":408025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Rio Puerco Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.9134521484375,\n              36.04465753921525\n            ],\n            [\n              -108.050537109375,\n              36.03577394783581\n            ],\n            [\n              -108.6602783203125,\n              35.652832827451654\n            ],\n            [\n              -108.7371826171875,\n              34.800272350556824\n            ],\n            [\n              -107.99011230468749,\n              34.288991865037524\n            ],\n            [\n              -107.215576171875,\n              34.44315867450577\n            ],\n            [\n              -106.776123046875,\n              34.384246040152185\n            ],\n            [\n              -106.644287109375,\n              34.813803317113155\n            ],\n            [\n              -106.644287109375,\n              35.0120020431607\n            ],\n            [\n              -106.820068359375,\n              35.68853320738875\n            ],\n            [\n              -106.9134521484375,\n              36.04465753921525\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"129","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2017-07-14","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":853989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, John G.","contributorId":297384,"corporation":false,"usgs":false,"family":"Elliott","given":"John G.","affiliations":[],"preferred":false,"id":853990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pavich, Milan","contributorId":297385,"corporation":false,"usgs":false,"family":"Pavich","given":"Milan","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":853991,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189327,"text":"70189327 - 2017 - Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain","interactions":[],"lastModifiedDate":"2017-07-11T13:09:40","indexId":"70189327","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain","docAbstract":"<p><span>While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues provide daily averaged near-surface winds at an appropriate spatial resolution for wave modeling within the orographically complex region of San Francisco Bay, but greater resolution in time is needed to capture the peak of storm events. Short-duration high wind speeds, on the order of hours, are usually excluded in statistically downscaled climate models and are of key importance in wave and subsequent coastal flood modeling. Here we present a temporal downscaling approach, similar to constructed analogues, for near-surface winds suitable for use in local wave models and evaluate changes in wind and wave conditions for the 21st century. Reconstructed hindcast winds (1975–2004) recreate important extreme wind values within San Francisco Bay. A computationally efficient method for simulating wave heights over long time periods was used to screen for extreme events. Wave hindcasts show resultant maximum wave heights of 2.2&nbsp;m possible within the Bay. Changes in extreme over-water wind speeds suggest contrasting trends within the different regions of San Francisco Bay, but 21th century projections show little change in the overall magnitude of extreme winds and locally generated waves.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2016EA000193","usgsCitation":"O'Neill, A., Erikson, L.H., and Barnard, P., 2017, Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain: Earth and Space Science, v. 4, no. 5, p. 314-334, https://doi.org/10.1002/2016EA000193.","productDescription":"21 p.","startPage":"314","endPage":"334","ipdsId":"IP-075780","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016ea000193","text":"Publisher Index Page"},{"id":343574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.06610107421876,\n              37.411618795843026\n            ],\n            [\n              -121.86035156249999,\n              37.411618795843026\n            ],\n            [\n              -121.86035156249999,\n              38.16911413556086\n            ],\n            [\n              -123.06610107421876,\n              38.16911413556086\n            ],\n            [\n              -123.06610107421876,\n              37.411618795843026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-24","publicationStatus":"PW","scienceBaseUri":"5965b1b8e4b0d1f9f05b379a","contributors":{"authors":[{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}