{"pageNumber":"937","pageRowStart":"23400","pageSize":"25","recordCount":165549,"records":[{"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":70188893,"text":"ds1055 - 2017 - Evidence of absence (v2.0) software user guide","interactions":[],"lastModifiedDate":"2020-08-21T22:26:18.261745","indexId":"ds1055","displayToPublicDate":"2017-07-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1055","title":"Evidence of absence (v2.0) software user guide","docAbstract":"<p class=\"p1\">Evidence of Absence software (EoA) is a user-friendly software application for estimating bird and bat fatalities at wind farms and for designing search protocols. The software is particularly useful in addressing whether the number of fatalities is below a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The software also includes tools (1) for estimating carcass persistence distributions and searcher efficiency parameters (\uD835\uDC5D and <span class=\"s1\">\uD835\uDC58</span>) from field trials, (2) for projecting future mortality based on past monitoring data, and (3) for exploring the potential consequences of various choices in the design of long-term incidental take permits for protected species. The software was designed specifically for cases where tolerance for mortality is low and carcass counts are small or even 0, but the tools also may be used for mortality estimates when carcass counts are large.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1055","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Dalthorp, Daniel, Huso, Manuela, and Dail, David, 2017, Evidence of absence (v2.0) software user guide: U.S. Geological Survey Data Series 1055, 109 p., https://doi.org/10.3133/ds1055.","productDescription":"Report: viii, 109 p.; Additional Report Pieces","onlineOnly":"Y","ipdsId":"IP-086433","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":343451,"rank":8,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/ds1055_eoa_csv-templates.zip","text":"CSV templates for data entry","size":"1 KB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 CSV templates for data entry"},{"id":343762,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/software_revision_history.txt","text":"Evidence of Absence software revision history","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"DS 1055 Evidence of Absence software revision history"},{"id":377775,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/r4_0_2/eoa_2.0.7.tar.gz","text":"Evidence of Absence software for MAC-UNIX, with R version >=4.0.2","size":"3.3 MB (tar.gz)","description":"DS 1055 Evidence of Absence software for MAC-UNIX, with R version >=4.0.2"},{"id":377774,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/r4_0_2/eoa_2.0.7.zip","text":"Evidence of Absence software for Windows, with R version >=4.0.2","size":"1.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for Windows, with R version >=4.0.2"},{"id":343450,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/eoa_2.0.7.tar.gz","text":"Evidence of Absence software for MAC-UNIX, with R versions 3.3.0 through 3.6.3","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for MAC-UNIX, with R versions 3.3.0 through 3.6.3"},{"id":343449,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/1055/eoa_2.0.7.zip","text":"Evidence of Absence software for Windows, with R versions 3.3.0 through 3.6.3","size":"1.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"DS 1055 Evidence of Absence software for Windows, with R versions 3.3.0 through 3.6.3"},{"id":343448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1055/ds1055.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1055"},{"id":343447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1055/coverthb.jpg"},{"id":343452,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/0881/","text":"Data Series 881—Evidence of Absence Software (1.0)","description":"Evidence of Absence Software User Guide (1.0)"}],"contact":"<p>Director, <a href=\"https://fresc.usgs.gov\" target=\"blank\" data-mce-href=\"https://fresc.usgs.gov\">Forest and Rangeland Ecosystem Science Center</a><br> U.S. Geological Survey<br> 777 NW 9th St., Suite 400<br> Corvallis, Oregon 97330</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Single Class Module<br></li><li>Multiple Class Module<br></li><li>Multiple Years Module<br></li><li>Design Tradeoffs<br></li><li>Scenario Explorer<br></li><li>Acknowledgments<br></li><li>References Cited<br></li><li>Appendixes A–K<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-07-06","noUsgsAuthors":false,"publicationDate":"2017-07-06","publicationStatus":"PW","scienceBaseUri":"595f4c38e4b0d1f9f057e30d","contributors":{"authors":[{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":700866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela M. 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":150012,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":700865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dail, David","contributorId":193578,"corporation":false,"usgs":false,"family":"Dail","given":"David","email":"","affiliations":[],"preferred":false,"id":700867,"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":70189157,"text":"70189157 - 2017 - Baseline assessments for coral reef community structure and demographics on West Maui","interactions":[],"lastModifiedDate":"2017-07-05T08:05:20","indexId":"70189157","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5451,"text":"NOAA Data Report","active":true,"publicationSubtype":{"id":4}},"title":"Baseline assessments for coral reef community structure and demographics on West Maui","docAbstract":"<p>The coastal and upslope terrains of West Maui have had a long history of impacts owing to more than a century of human activities. Resource extraction, agriculture, as well as residential and resort development have caused land-based pollution that impairs water quality and adversely impact the adjacent marine ecosystem. Today, West Maui’s coral reefs are chronically impacted by the effects of land-based pollution, mainly sedimentation and nutrients, with documented losses of 30 – 75% in coral cover over the last 20 years. Nonetheless, despite their current status and levels of environmental impact, these coral reef communities represent a key local resource and a counterpoint to the overall low coral reef development levels both island- and state-wide. This is of high relevance because the occurrence of coral-rich assemblages and accreted reef complexes statewide is sparse. Only limited segments along the coastlines of Maui, Hawai‘i, Lana‘i, Moloka‘i, and Kaho‘olawe, harbor mature, fringing coral reefs; and unfortunately, many of them are seriously threatened by terrestrial runoff. </p><p>This report describes the results of baseline assessment surveys of coral reef benthic structure, coral community demographics, and coral condition. These surveys are intended to provide benchmarks for continued monitoring efforts and provide a gauge for comparing and evaluating the effectiveness of management actions to reduce land-based sources of pollution in priority watersheds on West Maui. Within this context, 12 permanent, long-term monitoring sites were strategically established adjacent to the 7 primary stream drainages (Wahikuli, Honokōwai, Mahinahina, Kahana/Ka‘opala, Honokeana, Honokahua, and Honolua) within the five priority watersheds (Wahikuli, Honokōwai, Kahana, Honokahua, and Honolua). Herein, benthic cover and composition, coral demographics, and coral condition of the monitoring sites are described and contrasted in the “Benthic Characterization” and “Synthesis and Discussion” sections of this report. </p><p>The baseline assessments revealed that although some areas harbor prominent coral reef structures with high live coral cover and multispecies assemblages, others are characterized by sediment-impacted corals in impoverished and species-poor communities. Mean coral cover varied widely, from 49% at Wahikuli-shallow to 4.6% at Mahinahina-shallow. Similarly, coralline algal cover averaged 12.7% at Ka‘opala and Honokeana-north, but was altogether absent at the Mahinahina sites. Macroalgae was a minor component of the benthos across all study sites, representing only up to 2.3% at Mahinahina-south, while turf algae varied considerably, from 41% at Honokeana-north to 84% at the Honokahua site. Consequently, the Benthic Substrate Ratio (BSR) also varied considerably region wide, with the highest values (≥ 1), suggesting a healthier reef condition reported for the Wahikuli, Honokeana, and Honokōwai sites; and the lowest (≤ 0.5), suggesting impairment in structure and function, recorded at the Honolua and Honokahua sites. Adult colony densities were the highest at the Wahikuli (27 col/m<sup>2</sup>) but lowest at the Ka‘opala (7 col/m2 ) site. And, colony partial mortality peaked at the Ka‘opala (33%) and was the lowest at the Honokeana Bay (12%). Moreover, in-situ and derived estimates of water turbidity and sediment loading revealed that the Ka‘opala and Wahikuli stream sites ranked the highest for turbidity, whereas the Honokōwai and Ka‘opala sites ranked highest for sediment loading. </p><p>Chronic and episodic terrestrial sediment stress has resulted in coral reef community demise, clearly illustrated at the Honolua, Honokahua, and Ka‘opala sites, where coral benthic cover and colony abundances ranked the lowest and levels of turf algae ranked among the highest. Left unattended, land-based pollution impacts will continue to negatively affect the coral reef communities of West Maui. And, under the current turbidity and sediment loading conditions, the coral-rich habitats in the Wahikuli and Honōkowai Watersheds are probably at greatest risk, given they harbor the most prominent and well-developed reefs in the region, characterized by the highest coral cover, colony densities, and structural complexity. </p>","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.7289/V5/SP-PIFSC-17-001","usgsCitation":"Vargas-Angel, B., White, D., Storlazzi, C.D., Callender, T., and Maurin, P., 2017, Baseline assessments for coral reef community structure and demographics on West Maui: NOAA Data Report, ii, 45 p., https://doi.org/10.7289/V5/SP-PIFSC-17-001.","productDescription":"ii, 45 p.","ipdsId":"IP-086300","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science 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,{"id":70189482,"text":"70189482 - 2017 - Fifty-eighth supplement to the American Ornithologists' Union: Check-list of North American Birds","interactions":[],"lastModifiedDate":"2017-10-24T15:10:48","indexId":"70189482","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Fifty-eighth supplement to the American Ornithologists' Union: <i>Check-list of North American Birds</i>","title":"Fifty-eighth supplement to the American Ornithologists' Union: Check-list of North American Birds","docAbstract":"This is the 17th supplement since publication of the 7th edition of the Check-list of North American Birds (American Ornithologists' Union [AOU] 1998). It summarizes decisions made between April 15, 2016, and April 15, 2017, by the AOS's Committee on Classification and Nomenclature—North and Middle America. The Committee has continued to operate in the manner outlined in the 42nd Supplement","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-72.1","usgsCitation":"Chesser, T., Burns, K., Cicero, C., Dunn, J.L., Kratter, A.W., Lovette, I.J., Rasmussen, P.C., Remsen, J., Rising, J.D., Stotz, D.F., and Winker, K., 2017, Fifty-eighth supplement to the American Ornithologists' Union: Check-list of North American Birds: The Auk, v. 134, no. 3, p. 751-773, https://doi.org/10.1642/AUK-17-72.1.","productDescription":"24 p. ","startPage":"751","endPage":"773","ipdsId":"IP-088606","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469697,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1642/auk-17-72.1","text":"Publisher Index Page"},{"id":343837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"134","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d828e4b0d1f9f060a178","contributors":{"authors":[{"text":"Chesser, Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":177781,"corporation":false,"usgs":true,"family":"Chesser","given":"Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":704882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Kevin J","contributorId":145564,"corporation":false,"usgs":false,"family":"Burns","given":"Kevin J","affiliations":[{"id":5088,"text":"SDSU","active":true,"usgs":false}],"preferred":false,"id":704952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cicero, Carla","contributorId":145565,"corporation":false,"usgs":false,"family":"Cicero","given":"Carla","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":704953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Jon L.","contributorId":145566,"corporation":false,"usgs":false,"family":"Dunn","given":"Jon","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":704954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kratter, Andrew W.","contributorId":145567,"corporation":false,"usgs":false,"family":"Kratter","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":16151,"text":"Univ Fla","active":true,"usgs":false}],"preferred":false,"id":704955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lovette, Irby J.","contributorId":145573,"corporation":false,"usgs":false,"family":"Lovette","given":"Irby","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":704956,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rasmussen, Pamela C.","contributorId":145569,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Pamela","email":"","middleInitial":"C.","affiliations":[{"id":16153,"text":"Mich St Univ","active":true,"usgs":false}],"preferred":false,"id":704957,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Remsen, J.V. Jr.","contributorId":82258,"corporation":false,"usgs":true,"family":"Remsen","given":"J.V.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":704958,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rising, James D.","contributorId":145571,"corporation":false,"usgs":false,"family":"Rising","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":16155,"text":"Univ Toronto","active":true,"usgs":false}],"preferred":false,"id":704959,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stotz, Douglas F.","contributorId":145572,"corporation":false,"usgs":false,"family":"Stotz","given":"Douglas","email":"","middleInitial":"F.","affiliations":[{"id":16156,"text":"FMNH","active":true,"usgs":false}],"preferred":false,"id":704960,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Winker, Kevin","contributorId":140814,"corporation":false,"usgs":false,"family":"Winker","given":"Kevin","email":"","affiliations":[{"id":13586,"text":"University of Alaska Museum, University of Alaska Fairbanks, Fairbanks, Alaska, USA","active":true,"usgs":false}],"preferred":false,"id":704961,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70189195,"text":"70189195 - 2017 - Historical changes in organic matter input to the muddy sediments along the Zhejiang-Fujian Coast, China over the past 160 years","interactions":[],"lastModifiedDate":"2017-07-18T17:31:19","indexId":"70189195","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Historical changes in organic matter input to the muddy sediments along the Zhejiang-Fujian Coast, China over the past 160 years","docAbstract":"<p><span>The burial of sedimentary organic matter (SOM) in the large river-influenced estuarine-coastal regions is affected by hydrodynamic sorting, diagenesis and human activities. Typically, the inner shelf region of the East China Sea is a major carbon sink of the Yangtze River-derived fine-grained sediments. Most of the previous work concentrated on the studies of surface sediments or used a single-proxy in this region. In this study, two cores from the Zhejiang-Fujian Coast were analyzed using bulk (TOC, TN and δ</span><sup>13</sup><span>C</span><sub>TOC</sub><span>) and molecular biomarker (</span><i>n</i><span>-alkane, brassicasterol, dinosterol and glycerol dialkyl glycerol tetraether lipids) techniques to clarify the sources, spatiotemporal distribution and fate of SOM in the Yangtze River Estuary and adjacent shelf. Results from this study indicated that the effects of diagenesis and diffusion on different sedimentary biomarkers resulted in overestimation of the relative contribution of terrestrial organic matter (%OM</span><sub>terr</sub><span>), compared with those based on δ</span><sup>13</sup><span>C</span><sub>TOC</sub><span>. The amounts of terrestrial plant organic matter (OM</span><sub>plant</sub><span>) and%OM</span><sub>terr</sub><span><span>&nbsp;</span>in sediments decreased offshore. In contrast, the amounts of marine organic matter (OM</span><sub>marine</sub><span>) increased offshore, but closer to the Yangtze River mouth, the amounts of soil organic matter (OM</span><sub>soil</sub><span>) increased. Moreover, the amounts of TOC, OM</span><sub>plant</sub><span><span>&nbsp;</span>and OM</span><sub>marine</sub><span><span>&nbsp;</span>biomarkers increased, but OM</span><sub>soil</sub><span><span>&nbsp;</span>and%OM</span><sub>terr</sub><span>decreased over time in recent decades. Our study suggests that spatial organic matter distribution patterns in marine shelf sediments were controlled primarily by hydrodynamic sorting and nutrient concentrations, and temporally diverse patterns were controlled predominantly by anthropogenic influence (e.g., dam construction and soil conservation, reclamation and agricultural plantations, anthropogenic nutrient input, dust storms, eutrophication, etc) and climate events (e.g., interdecadal climatic jump and heavy rain events) in the geological period.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2017.06.003","usgsCitation":"Chen, L., Liu, J., Xing, L., Krauss, K.W., Wang, J., Xu, G., and Li, L., 2017, Historical changes in organic matter input to the muddy sediments along the Zhejiang-Fujian Coast, China over the past 160 years: Organic Geochemistry, v. 111, p. 13-25, https://doi.org/10.1016/j.orggeochem.2017.06.003.","productDescription":"13 p.","startPage":"13","endPage":"25","ipdsId":"IP-081183","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":343378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Zhejiang-Fujian Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              128,\n              25\n            ],\n            [\n              118,\n              25\n            ],\n            [\n              118,\n              35\n            ],\n            [\n              128,\n              35\n            ],\n            [\n              128,\n              25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"111","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595dfaa6e4b0d1f9f056a704","contributors":{"authors":[{"text":"Chen, Li-lei","contributorId":194204,"corporation":false,"usgs":false,"family":"Chen","given":"Li-lei","email":"","affiliations":[],"preferred":false,"id":703440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Jian","contributorId":194205,"corporation":false,"usgs":false,"family":"Liu","given":"Jian","email":"","affiliations":[],"preferred":false,"id":703441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xing, Lei","contributorId":194206,"corporation":false,"usgs":false,"family":"Xing","given":"Lei","email":"","affiliations":[],"preferred":false,"id":703442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","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":703439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jia-sheng","contributorId":194207,"corporation":false,"usgs":false,"family":"Wang","given":"Jia-sheng","email":"","affiliations":[],"preferred":false,"id":703443,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Gang","contributorId":194208,"corporation":false,"usgs":false,"family":"Xu","given":"Gang","email":"","affiliations":[],"preferred":false,"id":703444,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Li","contributorId":190439,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":703445,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189166,"text":"70189166 - 2017 - Acquisition of Borrelia burgdorferi infection by larval Ixodes scapularis (Acari: Ixodidae) associated with engorgement measures","interactions":[],"lastModifiedDate":"2017-07-05T07:41:43","indexId":"70189166","displayToPublicDate":"2017-07-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Acquisition of <i>Borrelia burgdorferi</i> infection by larval <i>Ixodes scapularis</i> (Acari: Ixodidae) associated with engorgement measures","title":"Acquisition of Borrelia burgdorferi infection by larval Ixodes scapularis (Acari: Ixodidae) associated with engorgement measures","docAbstract":"<p><span>Measuring rates of acquisition of the Lyme disease pathogen,&nbsp;</span><i>Borrelia burgdorferi sensu lato</i><span><span>&nbsp;</span>Johnson, Schmid, Hyde, Steigerwalt &amp; Brenner, by the larval stage of<span>&nbsp;</span></span><i>Ixodes scapularis</i><span><span>&nbsp;</span>Say is a useful tool for xenodiagnoses of<span>&nbsp;</span></span><i>B. burgdorferi</i><span><span>&nbsp;</span>in vertebrate hosts. In the nymphal and adult stages of<span>&nbsp;</span></span><i>I. scapularis</i><span>, the duration of attachment to hosts has been shown to predict both body engorgement during blood feeding and the timing of infection with<span>&nbsp;</span></span><i>B. burgdorferi</i><span>. However, these relationships have not been established for the larval stage of<span>&nbsp;</span></span><i>I. scapularis</i><span>. We sought to establish the relationship between body size during engorgement of larval<span>&nbsp;</span></span><i>I. scapularis</i><span><span>&nbsp;</span>placed on<span>&nbsp;</span></span><i>B. burgdorferi-</i><span>infected, white-footed mice (</span><i>Peromyscus leucopus</i><span><span>&nbsp;</span>Rafinesque) and the presence or absence of infection in larvae sampled from hosts over time. Body size, time, and their interaction were the best predictors of larval infection with<span>&nbsp;</span></span><i>B. burgdorferi</i><span>. We found that infected larvae showed significantly greater engorgement than uninfected larvae as early as 24 h after placement on a host. These findings may suggest that infection with<span>&nbsp;</span></span><i>B. burgdorferi</i><span><span>&nbsp;</span>affects the larval feeding process. Alternatively, larvae that engorge more rapidly on hosts may acquire infections faster. Knowledge of these relationships can be applied to improve effective xenodiagnosis of<span>&nbsp;</span></span><i>B. burgdorferi</i><span><span>&nbsp;</span>in white-footed mice. Further, these findings shed light on vector–pathogen–host interactions during an understudied part of the Lyme disease transmission cycle.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jme/tjx053","usgsCitation":"Couret, J., Dyer, M., Mather, T., Han, S., Tsao, J., LeBrun, R., and Ginsberg, H., 2017, Acquisition of Borrelia burgdorferi infection by larval Ixodes scapularis (Acari: Ixodidae) associated with engorgement measures: Journal of Medical Entomology, v. 54, no. 4, p. 1055-1060, https://doi.org/10.1093/jme/tjx053.","productDescription":"6 p.","startPage":"1055","endPage":"1060","ipdsId":"IP-083413","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469694,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/141","text":"External Repository"},{"id":343287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-18","publicationStatus":"PW","scienceBaseUri":"595dfaa8e4b0d1f9f056a714","contributors":{"authors":[{"text":"Couret, Janelle","contributorId":194159,"corporation":false,"usgs":false,"family":"Couret","given":"Janelle","affiliations":[],"preferred":false,"id":703321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyer, M.C.","contributorId":194160,"corporation":false,"usgs":false,"family":"Dyer","given":"M.C.","email":"","affiliations":[],"preferred":false,"id":703322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mather, T.N.","contributorId":194161,"corporation":false,"usgs":false,"family":"Mather","given":"T.N.","email":"","affiliations":[],"preferred":false,"id":703323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Han, S.","contributorId":60009,"corporation":false,"usgs":true,"family":"Han","given":"S.","email":"","affiliations":[],"preferred":false,"id":703324,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsao, J.I.","contributorId":194162,"corporation":false,"usgs":false,"family":"Tsao","given":"J.I.","email":"","affiliations":[],"preferred":false,"id":703325,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeBrun, R.A.","contributorId":194163,"corporation":false,"usgs":false,"family":"LeBrun","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":703326,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":703320,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"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":70263786,"text":"70263786 - 2017 - Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes","interactions":[],"lastModifiedDate":"2025-02-24T15:51:02.184943","indexId":"70263786","displayToPublicDate":"2017-07-04T09:48:16","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}},"displayTitle":"Determination of earthquake magnitude for early warning from the time-dependence of <i>P</i>-wave amplitudes","title":"Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes","docAbstract":"<p><span>We propose a method that utilizes the time dependence of&nbsp;</span><i>P</i><span>‐wave displacement amplitudes to estimate the final magnitude (</span><span class=\"inline-formula no-formula-id\">⁠M⁠</span><span>) for earthquake early warning (EEW) before the arrival of the peak amplitude. A relation between&nbsp;</span><span class=\"inline-formula no-formula-id\">M</span><span>&nbsp;and&nbsp;</span><i>P</i><span>‐wave displacement amplitude is employed for the method. Its value is set as a function of time from the&nbsp;</span><i>P</i><span>&nbsp;arrival, and is determined using a K‐NET dataset recorded in Japan from a scaling relation between&nbsp;</span><span class=\"inline-formula no-formula-id\">M</span><span>&nbsp;and the time dependence of&nbsp;</span><i>P</i><span>‐wave displacement. A test to check the performance of the proposed equation demonstrates in a statistical sense that this technique enables us to estimate&nbsp;</span><span class=\"inline-formula no-formula-id\">M</span><span>&nbsp;more rapidly than conventional methods without loss of accuracy. We conclude that the approach proposed in this article effectively gains a longer lead time as well as reduces the blind zone for EEW.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170048","usgsCitation":"Noda, S., and Ellsworth, W.L., 2017, Determination of earthquake magnitude for early warning from the time-dependence of P-wave amplitudes: Bulletin of the Seismological Society of America, v. 107, no. 4, p. 1860-1867, https://doi.org/10.1785/0120170048.","productDescription":"8 p.","startPage":"1860","endPage":"1867","ipdsId":"IP-076689","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Noda, Shunta 0000-0002-5897-3409","orcid":"https://orcid.org/0000-0002-5897-3409","contributorId":351252,"corporation":false,"usgs":true,"family":"Noda","given":"Shunta","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L. 0000-0001-8378-4979 ellsworth@usgs.gov","orcid":"https://orcid.org/0000-0001-8378-4979","contributorId":206685,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928272,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"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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,{"id":70189159,"text":"70189159 - 2017 - Adding a nitrogen footprint to Colorado State University’s sustainability plan","interactions":[],"lastModifiedDate":"2017-07-04T12:08:48","indexId":"70189159","displayToPublicDate":"2017-07-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Adding a nitrogen footprint to Colorado State University’s sustainability plan","docAbstract":"As a large land grant university with more than 32,000 students, Colorado State University has both on-campus non-agricultural and agricultural sources of nitrogen (N) released to the environment. We used the Nitrogen Footprint Tool to estimate the amount of N released from different sectors of the university for the CSU 2014 academic year. The largest on campus sources were food production, utilities (heating, cooling, electricity), and research animals. The total on-campus N footprint in 2014 was 287 metric tons. This value was equivalent to the nitrogen footprint of agricultural experiment stations and other agricultural facilities, whose nitrogen footprint was 273 metric tons. CSU has opportunities to reduce its on-campus footprint through educational programs promoting low-meat diets and commuting by bicycle or bus. There is also an opportunity to advance ideas of agricultural best management practices, including precision farming and better livestock management. This article describes the planned and ongoing efforts to educate CSU about how societal activities release nitrogen to the environment, contributing to global change.  It offers personal and institutional options for taking action, which would ultimately reduce CSU’s excess reactive nitrogen loss to the environment. The N-footprint for CSU, including scenarios of possible future nitrogen reductions, is also discussed.","language":"English","publisher":"Mary Ann Liebert, Inc","doi":"10.1089/sus.2017.29091.jk","usgsCitation":"Kimiecik, J., Baron, J., Weinmann, T., and Taylor, E., 2017, Adding a nitrogen footprint to Colorado State University’s sustainability plan: Sustainability, v. 10, no. 2, p. 89-95, https://doi.org/10.1089/sus.2017.29091.jk.","productDescription":"7 p.","startPage":"89","endPage":"95","ipdsId":"IP-085225","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":343282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595ca911e4b0d1f9f054ca10","contributors":{"authors":[{"text":"Kimiecik, Jacob","contributorId":194125,"corporation":false,"usgs":false,"family":"Kimiecik","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":703270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":703269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weinmann, Timothy","contributorId":194126,"corporation":false,"usgs":false,"family":"Weinmann","given":"Timothy","affiliations":[],"preferred":false,"id":703271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Emily","contributorId":194127,"corporation":false,"usgs":false,"family":"Taylor","given":"Emily","affiliations":[],"preferred":false,"id":703272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70190243,"text":"70190243 - 2017 - Life history constraints explain negative relationship between fish productivity and dissolved organic carbon in lakes","interactions":[],"lastModifiedDate":"2021-02-05T16:31:00.323131","indexId":"70190243","displayToPublicDate":"2017-07-03T10:26:40","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Life history constraints explain negative relationship between fish productivity and dissolved organic carbon in lakes","docAbstract":"<p><span>Resource availability constrains the life history strategies available to organisms and may thereby limit population growth rates and productivity. We used this conceptual framework to explore the mechanisms driving recently reported negative relationships between fish productivity and dissolved organic carbon (DOC) concentrations in lakes. We studied populations of bluegill (</span><i>Lepomis macrochirus</i><span>) in a set of lakes with DOC concentrations ranging from 3 to 24&nbsp;mg/L; previous work has demonstrated that primary and secondary productivity of food webs is negatively related to DOC concentration across this gradient. For each population, we quantified individual growth rate, age at maturity, age‐specific fecundity, maximum age, length‐weight and length‐egg size relationships, and other life history characteristics. We observed a strong negative relationship between maximum size and DOC concentration; for instance, fish reached masses of 150 to 260&nbsp;g in low‐DOC lakes but &lt;120&nbsp;g in high‐DOC lakes. Relationships between fecundity and length, and between egg size and length, were constant across the DOC gradient. Because fish in high‐DOC lakes reached smaller sizes but had similar fecundity and egg size at a given size, their total lifetime fecundity was as much as two orders of magnitude lower than fish in low‐DOC lakes. High DOC concentrations appeared to constrain the range of bluegill life history strategies available; populations in high‐DOC lakes always had low initial growth rates and high ages at maturity, whereas populations in low‐DOC showed higher variability in these traits. This was also the case for the intrinsic rates of natural increase of these populations, which were always low at the high end of the DOC gradient. The potentially lower capacity for fish populations in high‐DOC lakes to recover from exploitation has clear implications for the sustainable management of recreational fisheries in the face of considerable spatial heterogeneity and ongoing temporal change in lake DOC concentrations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3108","usgsCitation":"Craig, N., Jones, S., Weidel, B., and Solomon, C.T., 2017, Life history constraints explain negative relationship between fish productivity and dissolved organic carbon in lakes: Ecology and Evolution, v. 7, no. 16, p. 6201-6209, https://doi.org/10.1002/ece3.3108.","productDescription":"9 p.","startPage":"6201","endPage":"6209","ipdsId":"IP-069097","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3108","text":"Publisher Index Page"},{"id":383051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Vilas County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.9879,46.0971],[-88.9329,46.0746],[-88.9332,45.9822],[-89.0478,45.9822],[-89.0477,45.8953],[-89.1091,45.8973],[-89.1752,45.8993],[-89.1754,45.859],[-89.3008,45.8606],[-89.3007,45.9014],[-89.3628,45.8987],[-89.4256,45.8987],[-89.5498,45.8988],[-89.6741,45.8987],[-89.7571,45.8985],[-89.797,45.898],[-89.8199,45.8984],[-89.9212,45.8981],[-89.9846,45.8974],[-90.0428,45.8972],[-90.0442,45.9823],[-90.0134,45.9824],[-89.9853,45.9821],[-89.9289,45.9818],[-89.9282,46.0693],[-89.9288,46.1558],[-89.9287,46.2428],[-89.929,46.3],[-89.7599,46.268],[-89.7368,46.2636],[-89.5829,46.2347],[-89.5331,46.2252],[-89.5133,46.2215],[-89.4272,46.2048],[-89.3759,46.1949],[-89.2666,46.1737],[-89.2302,46.1662],[-89.0854,46.1365],[-88.9879,46.0971]]]},\"properties\":{\"name\":\"Vilas\",\"state\":\"WI\"}}]}","volume":"7","issue":"16","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Craig, Nicola","contributorId":150803,"corporation":false,"usgs":false,"family":"Craig","given":"Nicola","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":708109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Stuart E.","contributorId":22222,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart E.","affiliations":[{"id":6966,"text":"Department of Biological Sciences, University of Notre Dame","active":true,"usgs":false}],"preferred":false,"id":708110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":708108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":708111,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70189589,"text":"70189589 - 2017 - USGS Integration of New Science and Technology, Appendix A","interactions":[],"lastModifiedDate":"2019-07-12T14:52:13","indexId":"70189589","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"USGS Integration of New Science and Technology, Appendix A","docAbstract":"This product summarizes the USGS plans for integration of new science and technology into Asian Carp control efforts for 2017. This includes the 1) implementation and evaluation of new tactics and behavioral information for monitoring, surveillance, control and containment; 2) understanding behavior and reproduction of Asian carp in established and emerging populations to inform deterrent deployment, rapid response, and removal efforts; and 3) development and evaluation of databases, decision support tools and performance measures.","largerWorkTitle":"2017 Asian Carp Monitoring and Response Plan","language":"English","publisher":"Monitoring and Response Work Group (MRWG) of the Asian Carp Regional Coordinating Committee (ACRCC)","usgsCitation":"Brey, M.K., Knights, B.C., Cupp, A.R., Amberg, J., Chapman, D., Calfee, R.D., and Duncker, J.J., 2017, USGS Integration of New Science and Technology, Appendix A, 5 p.","productDescription":"5 p.","startPage":"A-1","endPage":"A-5","ipdsId":"IP-086655","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":344003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343969,"type":{"id":15,"text":"Index Page"},"url":"https://www.asiancarp.us/PlansReports.html"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e24e4b0d1f9f0640752","contributors":{"authors":[{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":705316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":705317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":705318,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705319,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189150,"text":"70189150 - 2017 - Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy","interactions":[],"lastModifiedDate":"2017-07-03T09:29:03","indexId":"70189150","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy","docAbstract":"<p><span>Water (H</span><sub>2</sub><span>O) is by far the most abundant volcanic volatile species and plays a predominant role in driving volcanic eruptions. However, numerous difficulties associated with making accurate measurements of water vapor in volcanic plumes have limited their use as a diagnostic tool. Here we present the first detection of water vapor in a volcanic plume using passive visible-light differential optical absorption spectroscopy (DOAS). Ultraviolet and visible-light DOAS measurements were made on 21 May 2016 at Sabancaya Volcano, Peru. We find that Sabancaya's plume contained an exceptionally high relative water vapor abundance 6&nbsp;months prior to its November 2016 eruption. Our measurements yielded average sulfur dioxide (SO</span><sub>2</sub><span>) emission rates of 800–900&nbsp;t/d, H</span><sub>2</sub><span>O emission rates of around 250,000&nbsp;t/d, and an H</span><sub>2</sub><span>O/SO</span><sub>2</sub><span><span>&nbsp;</span>molecular ratio of 1000 which is about an order of magnitude larger than typically found in high-temperature volcanic gases. We attribute the high water vapor emissions to a boiling-off of Sabancaya's hydrothermal system caused by intrusion of magma to shallow depths. This hypothesis is supported by a significant increase in the thermal output of the volcanic edifice detected in infrared satellite imagery leading up to and after our measurements. Though the measurement conditions encountered at Sabancaya were very favorable for our experiment, we show that visible-light DOAS systems could be used to measure water vapor emissions at numerous other high-elevation volcanoes. Such measurements would provide observatories with additional information particularly useful for forecasting eruptions at volcanoes harboring significant hydrothermal systems.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014020","usgsCitation":"Kern, C., Masias, P., Apaza, F., Reath, K., and Platt, U., 2017, Remote measurement of high preeruptive water vapor emissions at Sabancaya volcano by passive differential optical absorption spectroscopy: Journal of Geophysical Research B: Solid Earth, v. 122, no. 5, p. 3540-3564, https://doi.org/10.1002/2017JB014020.","productDescription":"25 p.","startPage":"3540","endPage":"3564","ipdsId":"IP-083524","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469701,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017jb014020","text":"External Repository"},{"id":343266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"122","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-21","publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536da9","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masias, Pablo","contributorId":190934,"corporation":false,"usgs":false,"family":"Masias","given":"Pablo","email":"","affiliations":[],"preferred":false,"id":703176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Apaza, Fredy","contributorId":190927,"corporation":false,"usgs":false,"family":"Apaza","given":"Fredy","email":"","affiliations":[],"preferred":false,"id":703177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reath, Kevin","contributorId":194091,"corporation":false,"usgs":false,"family":"Reath","given":"Kevin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":703178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Platt, Ulrich","contributorId":194092,"corporation":false,"usgs":false,"family":"Platt","given":"Ulrich","email":"","affiliations":[],"preferred":false,"id":703179,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189151,"text":"70189151 - 2017 - The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146","interactions":[],"lastModifiedDate":"2017-07-03T09:24:14","indexId":"70189151","displayToPublicDate":"2017-07-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The difficulty of measuring the absorption of scattered sunlight by H<sub>2</sub>O and CO<sub>2</sub> in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” <i>Remote Sens</i>. 2017, <i>9</i>, 146","title":"The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146","docAbstract":"In their recent study, Pering et al. (2017) presented a novel method for measuring volcanic water vapor fluxes. Their method is based on imaging volcanic gas and aerosol plumes using a camera sensitive to the near-infrared (NIR) absorption of water vapor. The imaging data are empirically calibrated by comparison with in situ water measurements made within the plumes. Though the presented method may give reasonable results over short time scales, the authors fail to recognize the sensitivity of the technique to light scattering on aerosols within the plume. In fact, the signals measured by Pering et al. are not related to the absorption of NIR radiation by water vapor within the plume. Instead, the measured signals are most likely caused by a change in the effective light path of the detected radiation through the atmospheric background water vapor column. Therefore, their method is actually based on establishing an empirical relationship between in-plume scattering efficiency and plume water content. Since this relationship is sensitive to plume aerosol abundance and numerous environmental factors, the method will only yield accurate results if it is calibrated very frequently using other measurement techniques.","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/rs9060534","usgsCitation":"Kern, C., 2017, The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146: Remote Sensing, v. 9, no. 6, Article 534: 11 p., https://doi.org/10.3390/rs9060534.","productDescription":"Article 534: 11 p.","ipdsId":"IP-086338","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9060534","text":"Publisher Index Page"},{"id":343265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-27","publicationStatus":"PW","scienceBaseUri":"595b5795e4b0d1f9f0536da4","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703180,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"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":70202396,"text":"70202396 - 2017 - How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications","interactions":[],"lastModifiedDate":"2019-02-27T13:02:14","indexId":"70202396","displayToPublicDate":"2017-07-01T13:02:07","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications","docAbstract":"<p><span>Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2016WR020328","usgsCitation":"McMilan, H., Seibert, J., Petersen-Overleir, A., Lang, M., White, P., Snelder, T., Rutherford, K., Krueger, T., Mason,, R., and Kiang, J.E., 2017, How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications: Water Resources Research, v. 53, no. 7, p. 5220-5228, https://doi.org/10.1002/2016WR020328.","productDescription":"9 p.","startPage":"5220","endPage":"5228","ipdsId":"IP-088336","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":469702,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2016wr020328","text":"External Repository"},{"id":361589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"McMilan, Hilary","contributorId":213624,"corporation":false,"usgs":false,"family":"McMilan","given":"Hilary","email":"","affiliations":[{"id":38824,"text":"Department of Geology; San Diego State University, USA","active":true,"usgs":false}],"preferred":false,"id":758172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":758173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen-Overleir, Asgeir","contributorId":213625,"corporation":false,"usgs":false,"family":"Petersen-Overleir","given":"Asgeir","email":"","affiliations":[{"id":38825,"text":"Market Operations Hydrology, Statkraft Energi AS, Norway","active":true,"usgs":false}],"preferred":false,"id":758174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lang, Michel","contributorId":213626,"corporation":false,"usgs":false,"family":"Lang","given":"Michel","email":"","affiliations":[{"id":38826,"text":"Irstea, UR HHLY, Hydrology-Hydraulics, Villeurbanne, France","active":true,"usgs":false}],"preferred":false,"id":758175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Paul","contributorId":213695,"corporation":false,"usgs":false,"family":"White","given":"Paul","affiliations":[],"preferred":false,"id":758176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snelder, Ton","contributorId":213627,"corporation":false,"usgs":false,"family":"Snelder","given":"Ton","email":"","affiliations":[{"id":38827,"text":"LWP Let, 145c Colombo Street, Christchurch, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rutherford, Kit","contributorId":213628,"corporation":false,"usgs":false,"family":"Rutherford","given":"Kit","email":"","affiliations":[{"id":38828,"text":"National Institute of Water and Atmospheric Research, Napier, New Zealand","active":true,"usgs":false}],"preferred":false,"id":758178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krueger, Tobias","contributorId":213629,"corporation":false,"usgs":false,"family":"Krueger","given":"Tobias","email":"","affiliations":[{"id":38829,"text":"IRI THESys, Humboldt-Universitat zu Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":758179,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mason,, Robert R. Jr. 0000-0002-3998-3468 rrmason@usgs.gov","orcid":"https://orcid.org/0000-0002-3998-3468","contributorId":176493,"corporation":false,"usgs":true,"family":"Mason,","given":"Robert R.","suffix":"Jr.","email":"rrmason@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":false,"id":758171,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":758180,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70189719,"text":"70189719 - 2017 - Chemical and isotopic evidence for CO2 charge and migration within Bravo Dome and potential CO2 leakage to the southwest","interactions":[],"lastModifiedDate":"2019-02-14T10:42:43","indexId":"70189719","displayToPublicDate":"2017-07-01T10:42:34","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5215,"text":"Energy Procedia","onlineIssn":"1876-6102","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Chemical and isotopic evidence for CO<sub>2</sub> charge and migration within Bravo Dome and potential CO<sub>2</sub> leakage to the southwest","title":"Chemical and isotopic evidence for CO2 charge and migration within Bravo Dome and potential CO2 leakage to the southwest","docAbstract":"<p><span>Gas analyses from northeastern New Mexico, USA indicate that previous interpretations of the location of gas charge into the northeastern portion of Bravo Dome are likely correct, and that there may be multiple migration pathways from the same source for different regions in northeastern New Mexico.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.egypro.2017.03.1428","usgsCitation":"Brennan, S.T., 2017, Chemical and isotopic evidence for CO2 charge and migration within Bravo Dome and potential CO2 leakage to the southwest: Energy Procedia, v. 114, p. 2996-3005, https://doi.org/10.1016/j.egypro.2017.03.1428.","productDescription":"10 p.","startPage":"2996","endPage":"3005","ipdsId":"IP-079898","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":461455,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.egypro.2017.03.1428","text":"Publisher Index Page"},{"id":361246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Bravo Dome","volume":"114","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":705917,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"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":70224921,"text":"70224921 - 2017 - Understanding and finding solutions to the problem of sedimentation in the National Wildlife Refuge System","interactions":[],"lastModifiedDate":"2021-10-05T12:35:27.928126","indexId":"70224921","displayToPublicDate":"2017-07-01T07:31:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Understanding and finding solutions to the problem of sedimentation in the National Wildlife Refuge System","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>The National Wildlife Refuge System (Refuge System) is a collection of public lands maintained by the U.S. Fish and Wildlife Service for migratory birds and other wildlife. Wetlands on individual National Wildlife Refuges (Refuges) may be at risk of increased sedimentation because of land use and water management practices. Increased sedimentation can reduce wetland habitat quality by altering hydrologic function, degrading water quality, and inhibiting growth of vegetation and invertebrates. On Refuges negatively affected by increased sedimentation, managers have to address complex questions about how to best remediate and mitigate the negative effects. The best way to account for these complexities is often not clear. On other Refuges, managers may not know whether sedimentation is a problem. Decision makers in the Refuge System may need to allocate resources to studying which Refuges could be at risk. Such analyses would help them understand where to direct support for managing increased sedimentation. In this paper, we summarize a case study demonstrating the use of decision-analytic tools in the development of a sedimentation management plan for Agassiz National Wildlife Refuge, Minnesota. Using what we learned from that process, we surveyed other Refuges in U.S. Fish and Wildlife Service Region 3 (an area encompassing the states of Illinois, Indiana, Iowa, Ohio, Michigan, Minnesota, Missouri, and Wisconsin) and Region 6 (an area encompassing the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming) about whether they experience sediment-related impacts to management. Our results show that cases of management being negatively affected by increased sedimentation are not isolated. We suggest that the Refuge System conduct a comprehensive and systematic assessment of increased sedimentation among Refuges to understand the importance of sedimentation in context with other management problems that Refuges face. The results of such an assessment could guide how the Refuge System allocates resources to studying and managing widespread stressors.</p></div>","language":"English","publisher":"Allen Press","doi":"10.3996/012016-JFWM-004","usgsCitation":"Post van der Burg, M., Jenni, K., Nieman, T.L., Eash, J., and Knutsen, G.A., 2017, Understanding and finding solutions to the problem of sedimentation in the National Wildlife Refuge System: Journal of Fish and Wildlife Management, v. 8, no. 2, p. 648-660, https://doi.org/10.3996/012016-JFWM-004.","productDescription":"13 p.","startPage":"648","endPage":"660","ipdsId":"IP-072192","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":487684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/012016-jfwm-004","text":"Publisher Index Page"},{"id":390235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Agassiz National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -96.08642578125,\n              48.193556524687395\n            ],\n            [\n              -95.77194213867188,\n              48.193556524687395\n            ],\n            [\n              -95.77194213867188,\n              48.43011178780495\n            ],\n            [\n              -96.08642578125,\n              48.43011178780495\n            ],\n            [\n              -96.08642578125,\n              48.193556524687395\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2017-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenni, Karen 0000-0001-9927-7509","orcid":"https://orcid.org/0000-0001-9927-7509","contributorId":219401,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":824613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nieman, Timothy L. 0000-0002-8585-0471","orcid":"https://orcid.org/0000-0002-8585-0471","contributorId":204543,"corporation":false,"usgs":false,"family":"Nieman","given":"Timothy","email":"","middleInitial":"L.","affiliations":[{"id":36953,"text":"Decision Applications, Inc.","active":true,"usgs":false}],"preferred":false,"id":824614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eash, Josh D.","contributorId":267175,"corporation":false,"usgs":false,"family":"Eash","given":"Josh D.","affiliations":[{"id":55428,"text":"U.S. Fish and Wildlife Service, 5600 American Blvd. W., Bloomington, MN","active":true,"usgs":false}],"preferred":false,"id":824615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knutsen, Gregory A.","contributorId":193104,"corporation":false,"usgs":false,"family":"Knutsen","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":824616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192070,"text":"70192070 - 2017 - Species’ traits help predict small mammal responses to habitat homogenization by an invasive grass","interactions":[],"lastModifiedDate":"2017-10-19T13:49:04","indexId":"70192070","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Species’ traits help predict small mammal responses to habitat homogenization by an invasive grass","docAbstract":"<p><span>Invasive plants can negatively affect native species, however, the strength, direction, and shape of responses may vary depending on the type of habitat alteration and the natural history of native species. To prioritize conservation of vulnerable species, it is therefore critical to effectively predict species’ responses to invasive plants, which may be facilitated by a framework based on species’ traits. We studied the population and community responses of small mammals and changes in habitat heterogeneity across a gradient of cheatgrass (</span><i>Bromus tectorum</i><span>) cover, a widespread invasive plant in North America. We live-trapped small mammals over two summers and assessed the effect of cheatgrass on native small mammal abundance, richness, and species-specific and trait-based occupancy, while accounting for detection probability and other key habitat elements. Abundance was only estimated for the most common species, deer mice (</span><i>Peromyscus maniculatus</i><span>). All species were pooled for the trait-based occupancy analysis to quantify the ability of small mammal traits (habitat association, mode of locomotion, and diet) to predict responses to cheatgrass invasion. Habitat heterogeneity decreased with cheatgrass cover. Deer mouse abundance increased marginally with cheatgrass. Species richness did not vary with cheatgrass, however, pocket mouse (</span><i>Perognathus</i><span><span>&nbsp;</span>spp.) and harvest mouse (</span><i>Reithrodontomys</i><span><span>&nbsp;</span>spp.) occupancy tended to decrease and increase, respectively, with cheatgrass cover, suggesting a shift in community composition. Cheatgrass had little effect on occupancy for deer mice, 13-lined ground squirrels (</span><i>Spermophilus tridecemlineatus</i><span>), and Ord's kangaroo rat (</span><i>Dipodomys ordii</i><span>). Species’ responses to cheatgrass primarily corresponded with our a priori predictions based on species’ traits. The probability of occupancy varied significantly with a species’ habitat association but not with diet or mode of locomotion. When considered within the context of a rapid habitat change, such as caused by invasive plants, relevant species’ traits may provide a useful framework for predicting species’ responses to a variety of habitat disturbances. Understanding which species are likely to be most affected by exotic plant invasion will help facilitate more efficient, targeted management and conservation of native species and habitats.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1535","usgsCitation":"Ceradini, J.P., and Chalfoun, A.D., 2017, Species’ traits help predict small mammal responses to habitat homogenization by an invasive grass: Ecological Applications, v. 27, no. 5, p. 1451-1465, https://doi.org/10.1002/eap.1535.","productDescription":"15 p.","startPage":"1451","endPage":"1465","ipdsId":"IP-073819","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-17","publicationStatus":"PW","scienceBaseUri":"59e9b994e4b05fe04cd65c7c","contributors":{"authors":[{"text":"Ceradini, Joseph P.","contributorId":197676,"corporation":false,"usgs":false,"family":"Ceradini","given":"Joseph","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":714061,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"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}]}}
,{"id":70189131,"text":"70189131 - 2017 - Monitoring water content dynamics of biological soil crusts","interactions":[],"lastModifiedDate":"2018-03-29T11:39:58","indexId":"70189131","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring water content dynamics of biological soil crusts","docAbstract":"<p><span>Biological soil crusts (hereafter, “biocrusts”) dominate soil surfaces in nearly all dryland environments. To better understand the influence of water content on carbon (C) exchange, we assessed the ability of dual-probe heat-pulse (DPHP) sensors, installed vertically and angled, to measure changes in near-surface water content. Four DPHP sensors were installed in each of two research plots (eight sensors total) that differed by temperature treatment (control and heated). Responses were compared to horizontally installed water content measurements made with three frequency-domain reflectometry (FDR) sensors in each plot at 5-cm depth. The study was conducted near Moab, Utah, from April through September 2009. Results showed significant differences between sensor technologies: peak water content differences from the DPHP sensors were approximately three times higher than those from the FDR sensors; some of the differences can be explained by the targeted monitoring of biocrust material in the shorter DPHP sensor and by potential signal loss from horizontally installed FDR sensors, or by an oversampling of deeper soil. C-exchange estimates using the DPHP sensors showed a net C loss of 69 and 76&nbsp;g&nbsp;C m</span><sup>−2</sup><span><span>&nbsp;</span>in control and heated plots, respectively. The study illustrates the potential for using the more sensitive data from shallow installations for estimating C exchange in biocrusts.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2017.03.004","usgsCitation":"Young, M.H., Fenstermaker, L.F., and Belnap, J., 2017, Monitoring water content dynamics of biological soil crusts: Journal of Arid Environments, v. 142, p. 41-49, https://doi.org/10.1016/j.jaridenv.2017.03.004.","productDescription":"9 p.","startPage":"41","endPage":"49","ipdsId":"IP-079049","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1413765","text":"Publisher Index Page"},{"id":352934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"142","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee854e4b0da30c1bfc428","contributors":{"authors":[{"text":"Young, Michael H.","contributorId":203634,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fenstermaker, Lynn F.","contributorId":194059,"corporation":false,"usgs":false,"family":"Fenstermaker","given":"Lynn","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":703102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":703100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191078,"text":"70191078 - 2017 - Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado","interactions":[],"lastModifiedDate":"2017-09-25T11:38:59","indexId":"70191078","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado","docAbstract":"<p><span>Ecological restoration treatments are being implemented at an increasing rate in ponderosa pine and other dry conifer forests across the western United States, via the USDA Forest Service’s Collaborative Forest Landscape Restoration (CFLR) program. In this program, collaborative stakeholder groups work with National Forests (NFs) to adaptively implement and monitor ecological restoration treatments intended to offset the effects of many decades of anthropogenic stressors. We initiated a novel study to expand the scope of treatment effectiveness monitoring efforts in one of the first CFLR landscapes, Colorado’s Front Range. We used a Before/After/Control/Impact framework to evaluate the short-term consequences of treatments on numerous ecological properties. We collected pre-treatment and one year post-treatment data on NF and partner agencies’ lands, in 66 plots distributed across seven treatment units and nearby untreated areas. Our results reflected progress toward several treatment objectives: treated areas had lower tree density and basal area, greater openness, no increase in exotic understory plants, no decrease in native understory plants, and no decrease in use by tree squirrels and ungulates. However, some findings suggested the need for adaptive modification of both treatment prescriptions and monitoring protocols: treatments did not promote heterogeneity of stand structure, and monitoring methods may not have been robust enough to detect changes in surface fuels. Our study highlights both the effective aspects of these restoration treatments, and the importance of initiating and continuing collaborative science-based monitoring to improve the outcomes of broad-scale forest restoration efforts.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.03.008","collaboration":"Paula Fornwalt; Jonas Feinstein","usgsCitation":"Briggs, J.S., Fornwalt, P.J., and Feinstein, J.A., 2017, Short-term ecological consequences of collaborative restoration treatments in ponderosa pine forests of Colorado: Forest Ecology and Management, v. 395, p. 69-80, https://doi.org/10.1016/j.foreco.2017.03.008.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-079089","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":469769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2017.03.008","text":"Publisher Index Page"},{"id":346044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"395","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ca15ade4b017cf314041c3","contributors":{"authors":[{"text":"Briggs, Jenny S. 0000-0001-7454-6928 jsbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-7454-6928","contributorId":3087,"corporation":false,"usgs":true,"family":"Briggs","given":"Jenny","email":"jsbriggs@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":711089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fornwalt, Paula J.","contributorId":196676,"corporation":false,"usgs":false,"family":"Fornwalt","given":"Paula","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feinstein, Jonas A.","contributorId":196677,"corporation":false,"usgs":false,"family":"Feinstein","given":"Jonas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":711091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191426,"text":"70191426 - 2017 - Nitrogenase activity by biological soil crusts in cold sagebrush steppe ecosystems","interactions":[],"lastModifiedDate":"2017-10-11T14:24:08","indexId":"70191426","displayToPublicDate":"2017-07-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogenase activity by biological soil crusts in cold sagebrush steppe ecosystems","docAbstract":"<p><span>In drylands worldwide, biological soil crusts (BSC) form a thin photosynthetic cover across landscapes, and provide vital benefits in terms of stabilizing soil and fixing nitrogen (N) and carbon (C). Numerous studies have examined the effects of climate and disturbance on BSC functions; however, few have characterized these responses in rolling BSCs typical of northern ecosystems in the Intermountain West, US. With temperature increases and shifts in precipitation projected, it is unclear how BSCs in this region will respond to climate change, and how the response could affect their capacity to perform key ecosystem functions, such as providing ‘new’ N through biological N</span><sub>2</sub><span><span>&nbsp;</span>fixation. To address this important knowledge gap, we examined nitrogenase activity (NA) associated with rolling BSCs along a climatic gradient in southwestern Idaho, US, and quantified how acetylene reduction rates changed as a function of climate, grazing (using exclosures), and shrub-canopy association. Results show that warmer, drier climates at lower elevations hosted greater cover of late successional BSC communities (e.g., mosses and lichens), and higher NA compared with colder, wetter climates at higher elevations. Highest NA (0.5–29.3&nbsp;µmol C</span><sub>2</sub><span>H</span><sub>4</sub><span><span>&nbsp;</span>m</span><sup>−2</sup><span><span>&nbsp;</span>h</span><sup>−1</sup><span>) occurred during the early summer/spring, when water was more available than in late summer/autumn. Activity was strongly associated with soil characteristics including pH and ammonium concentrations suggesting these characteristics as potentially strong controls on NA in BSCs. The relationship between grazing and NA varied with elevation. Specifically, lower elevation sites had lower NA at grazed locations, whereas higher elevation sites had higher NA with grazing. At both low and high ends of the elevation gradient, shrub-canopy associated BSCs maintained two to three times higher NA compared to BSCs in the interspace among shrubs. Taken together, our findings indicate that the controls and rates of NA in BSCs vary seasonally and strongly with climate in the Intermountain West, and that drier springs are likely to influence rates of NA more than warmer summers.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10533-017-0342-9","usgsCitation":"Schwabedissen, S.G., Lohse, K.A., Reed, S.C., Aho, K.A., and Magnuson, T.S., 2017, Nitrogenase activity by biological soil crusts in cold sagebrush steppe ecosystems: Biogeochemistry, v. 134, no. 1-2, p. 57-76, https://doi.org/10.1007/s10533-017-0342-9.","productDescription":"20 p.","startPage":"57","endPage":"76","ipdsId":"IP-076032","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":346511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":" Reynolds Creek Experimental Watershed","volume":"134","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-19","publicationStatus":"PW","scienceBaseUri":"59defbefe4b05fe04ccd3d54","contributors":{"authors":[{"text":"Schwabedissen, Stacy G.","contributorId":196994,"corporation":false,"usgs":false,"family":"Schwabedissen","given":"Stacy","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":712206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lohse, Kathleen A. 0000-0003-1779-6773","orcid":"https://orcid.org/0000-0003-1779-6773","contributorId":196995,"corporation":false,"usgs":false,"family":"Lohse","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":712205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aho, Ken A.","contributorId":196997,"corporation":false,"usgs":false,"family":"Aho","given":"Ken","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":712209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magnuson, Timothy S.","contributorId":196996,"corporation":false,"usgs":false,"family":"Magnuson","given":"Timothy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712208,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
]}